# everyagent.si - Full Registry Specification

> Extended, machine-readable specification of every verified AI agent indexed on
> everyagent.si, including backbone models, architecture topologies and MCP bindings.

## Registry summary
- Verified agents: 92
- MCP-compliant agents: 61
- Canonical agent URL pattern: https://everyagent.si/agent/{slug}

## Agent specifications
### agent-tackle-box
- Canonical URL: https://everyagent.si/agent/agent-tackle-box
- Creator: dkondo
- Category: coding
- License: MIT
- Backbone model: Python / generic agent runtime
- Architecture: Given the lack of information, the architecture is inferred to be a generic agent runtime, potentially supporting various agent patterns, but no specific design like a planner/executor or ReAct loop can be determined.
- MCP binding: Native tooling only
- Website: https://github.com/dkondo/agent-tackle-box
- Repository: https://github.com/dkondo/agent-tackle-box
- Summary: A toolkit for developing AI agents, including agent-debugger: Terminal debugger for LangGraph & LangChain agents. Debug LLM agents with state inspection, tool calls, semantic breakpoints, and Python program stepping in one Textual UI.

### AgentGuide
- Canonical URL: https://everyagent.si/agent/agentguide
- Creator: adongwanai
- Category: orchestration
- License: Unknown
- Backbone model: Python / generic agent runtime
- Architecture: Given the lack of information, the architecture is inferred to be a basic agent runtime, likely intended for orchestration based on its declared category, but without specific design details.
- MCP binding: Native tooling only
- Website: N/A
- Repository: https://github.com/adongwanai/AgentGuide
- Summary: https://adongwanai.github.io/AgentGuide | AI Agent开发指南 | LangGraph实战 | 高级RAG | 转行大模型 | 大模型面试 | 算法工程师 | 面试题库 | 强化学习｜数据合成

### hermes-agent
- Canonical URL: https://everyagent.si/agent/hermes-agent
- Creator: NousResearch
- Category: coding
- License: MIT
- Backbone model: Python / generic agent runtime
- Architecture: The agent likely employs a ReAct-style loop or a planner-executor design, leveraging its tool-calling capabilities to dynamically create and improve skills based on interaction and experience.
- MCP binding: Native tooling only
- Website: https://hermes-agent.nousresearch.com
- Repository: https://github.com/NousResearch/hermes-agent
- Summary: The agent that grows with you

### Travel-AI-Agent-React-FastAPI-and-Cosmos-DB-Vector-Store
- Canonical URL: https://everyagent.si/agent/travel-ai-agent-react-fastapi-and-cosmos-db-vector-store
- Creator: jonathanscholtes
- Category: coding
- License: MIT
- Backbone model: Python / FastAPI Orchestrator
- Architecture: The architecture likely involves a React frontend communicating with a FastAPI backend, which in turn interacts with Azure Cosmos DB for data storage and potentially vector search, forming a web application with AI capabilities.
- MCP binding: Native tooling only
- Website: https://stochasticcoder.com/2024/05/05/empower-your-ai-agent-with-azure-cosmos-db/
- Repository: https://github.com/jonathanscholtes/Travel-AI-Agent-React-FastAPI-and-Cosmos-DB-Vector-Store
- Summary: Explores the implementation of a LangChain Agent using Azure Cosmos DB for MongoDB vCore to handle traveler inquiries and bookings. The project provides detailed instructions for setting up the environment and loading travel data, aiming to empower developers to integrate similar agents into their solutions.

### turn-mcp
- Canonical URL: https://everyagent.si/agent/turn-mcp
- Creator: shiaho777
- Category: coding
- License: MIT
- Backbone model: TypeScript / Node.js / MCP SDK tool-calling loop
- Architecture: The system operates as an MCP server, providing a 'turn.wait' mechanism for agents to introduce human-in-the-loop checkpoints, managed via a browser console.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/shiaho777/turn-mcp
- Summary: Achieve infinite conversation turns in a single API request via turn-mcp. Self-hosted MCP server with browser console for human-in-the-loop AI agents.

### LangChain-Tutorials
- Canonical URL: https://everyagent.si/agent/langchain-tutorials
- Creator: TirendazAcademy
- Category: coding
- License: Unknown
- Backbone model: Python / LangChain Orchestrator
- Architecture: Without a README or code, the architecture is inferred as a collection of LangChain examples, likely demonstrating various LLM orchestration patterns.
- MCP binding: Native tooling only
- Website: N/A
- Repository: https://github.com/TirendazAcademy/LangChain-Tutorials
- Summary: Practical step-by-step LangChain guides

### flakestorm
- Canonical URL: https://everyagent.si/agent/flakestorm
- Creator: flakestorm
- Category: coding
- License: Apache-2.0
- Backbone model: Python / Typer CLI with Ollama integration and Rust for performance-critical components.
- Architecture: The system appears to use a test harness approach, orchestrating various adversarial inputs and conditions to evaluate agent behavior and reliability, likely leveraging templating for test case generation.
- MCP binding: Native tooling only
- Website: https://flakestorm.com
- Repository: https://github.com/flakestorm/flakestorm
- Summary: Flakestorm — Automated Robustness Testing for AI Agents. Stop guessing if your agent really works. FlakeStorm generates adversarial mutations and exposes failures your manual tests and evals miss.

### eval-view
- Canonical URL: https://everyagent.si/agent/eval-view
- Creator: hidai25
- Category: coding
- License: Apache-2.0
- Backbone model: Python / TypeScript / OpenAI SDK / LangChain Orchestrator
- Architecture: EvalView provides a framework for defining test cases and baselines, then executing agent interactions and comparing outputs to detect regressions, integrating with popular LLM frameworks.
- MCP binding: Native tooling only
- Website: https://evalview.com
- Repository: https://github.com/hidai25/eval-view
- Summary: Regression testing for AI agents. Snapshot behavior,diff tool calls,catch regressions in CI. Works with LangGraph, CrewAI, OpenAI, Anthropic.

### designing-multiagent-systems
- Canonical URL: https://everyagent.si/agent/designing-multiagent-systems
- Creator: victordibia
- Category: orchestration
- License: Apache-2.0
- Backbone model: Python / Conceptual Framework
- Architecture: No specific agent architecture is discernible from the provided metadata; it likely serves as a conceptual or educational resource.
- MCP binding: Native tooling only
- Website: https://buy.multiagentbook.com/
- Repository: https://github.com/victordibia/designing-multiagent-systems
- Summary: Building LLM-Enabled Multi Agent Applications from Scratch

### magentic-ui
- Canonical URL: https://everyagent.si/agent/magentic-ui
- Creator: microsoft
- Category: orchestration
- License: MIT
- Backbone model: Python / FastAPI / Playwright Orchestrator (OpenAI/Azure OpenAI SDK)
- Architecture: This system employs a multi-agent architecture with a human-centered interface, leveraging Playwright for web automation and likely a planner-executor pattern to orchestrate agents and tools.
- MCP binding: Native tooling only
- Website: https://www.microsoft.com/en-us/research/blog/magenticlite-magenticbrain-fara1-5-an-agentic-experience-optimized-for-small-models/
- Repository: https://github.com/microsoft/magentic-ui
- Summary: MagenticLite is an experimental agent that works across the browser and local file system

### langfuse
- Canonical URL: https://everyagent.si/agent/langfuse
- Creator: langfuse
- Category: orchestration
- License: Unknown
- Backbone model: Node.js / Docker / Prisma / ClickHouse
- Architecture: Langfuse operates as a backend service with a web interface, collecting traces and events from LLM applications via SDKs, storing them in a database (Postgres/ClickHouse), and providing analytics and visualization.
- MCP binding: Native tooling only
- Website: https://langfuse.com
- Repository: https://github.com/langfuse/langfuse
- Summary: 🪢 Open source agent evals & observability: Trace, evaluate, and improve LLM applications with one open platform.

### autogen
- Canonical URL: https://everyagent.si/agent/autogen
- Creator: microsoft
- Category: orchestration
- License: CC-BY-4.0
- Backbone model: Python / Multi-Agent Orchestrator
- Architecture: AutoGen facilitates multi-agent conversations where agents can take on various roles, exchange messages, and collaboratively solve tasks, often integrating external tools.
- MCP binding: Native tooling only
- Website: https://microsoft.github.io/autogen/
- Repository: https://github.com/microsoft/autogen
- Summary: A programming framework for agentic AI

### ai-agents-for-beginners
- Canonical URL: https://everyagent.si/agent/ai-agents-for-beginners
- Creator: microsoft
- Category: orchestration
- License: MIT
- Backbone model: Python / Microsoft Agent Framework (MAF) with Azure OpenAI and Foundry Local
- Architecture: The agents are built using the Microsoft Agent Framework, leveraging OpenAI's API for language models and integrating tools for search and local model execution.
- MCP binding: Native tooling only
- Website: https://aka.ms/ai-agents-beginners
- Repository: https://github.com/microsoft/ai-agents-for-beginners
- Summary: 18 Lessons to Get Started Building AI Agents

### markitdown
- Canonical URL: https://everyagent.si/agent/markitdown
- Creator: microsoft
- Category: orchestration
- License: MIT
- Backbone model: Python / Orchestration Framework
- Architecture: Given the lack of information, it's inferred to be a basic orchestration framework, likely involving sequential or conditional execution of tasks.
- MCP binding: Native tooling only
- Website: N/A
- Repository: https://github.com/microsoft/markitdown
- Summary: Python tool for converting files and office documents to Markdown.

### crewAI-tools
- Canonical URL: https://everyagent.si/agent/crewai-tools
- Creator: crewAIInc
- Category: orchestration
- License: MIT
- Backbone model: Python / CrewAI Tooling
- Architecture: This project is a collection of pre-built tools that CrewAI agents can integrate and use, acting as a toolkit for external interactions rather than a standalone agent architecture.
- MCP binding: Native tooling only
- Website: N/A
- Repository: https://github.com/crewAIInc/crewAI-tools
- Summary: Extend the capabilities of your CrewAI agents with Tools

### AutoGroq
- Canonical URL: https://everyagent.si/agent/autogroq
- Creator: jgravelle
- Category: orchestration
- License: Unknown
- Backbone model: Python / Streamlit / LangChain Orchestrator
- Architecture: This agent likely employs a basic orchestration pattern, allowing users to interact with different LLMs and potentially integrate simple web-based tools through a Streamlit interface.
- MCP binding: Native tooling only
- Website: https://autogroq.streamlit.app/
- Repository: https://github.com/jgravelle/AutoGroq
- Summary: AutoGroq is a groundbreaking tool that revolutionizes the way users interact with Autogen™ and other AI assistants. By dynamically generating tailored teams of AI agents based on your project requirements, AutoGroq eliminates the need for manual configuration and allows you to tackle any question, problem, or project with ease and efficiency.

### awesome-multi-agent-papers
- Canonical URL: https://everyagent.si/agent/awesome-multi-agent-papers
- Creator: kyegomez
- Category: orchestration
- License: Unknown
- Backbone model: No runtime or model stack; it's a curated list of research papers.
- Architecture: This repository does not contain an agent architecture; it is a static collection of links to academic papers.
- MCP binding: Native tooling only
- Website: https://discord.gg/3keGBK9Pvr
- Repository: https://github.com/kyegomez/awesome-multi-agent-papers
- Summary: A compilation of the best multi-agent papers

### full-stack-ai-agent-template
- Canonical URL: https://everyagent.si/agent/full-stack-ai-agent-template
- Creator: vstorm-co
- Category: orchestration
- License: MIT
- Backbone model: Python / LangChain Orchestrator
- Architecture: The project is a template generator that scaffolds full-stack applications, integrating Pydantic AI and LangChain for agent capabilities within a FastAPI backend and Next.js frontend.
- MCP binding: Native tooling only
- Website: https://vstorm-co.github.io/full-stack-ai-agent-template/
- Repository: https://github.com/vstorm-co/full-stack-ai-agent-template
- Summary: Full-stack AI app generator — FastAPI + Next.js with AI Agents, RAG, streaming, auth, and 20+ integrations out of the box.

### mcp-memory-service
- Canonical URL: https://everyagent.si/agent/mcp-memory-service
- Creator: doobidoo
- Category: orchestration
- License: Apache-2.0
- Backbone model: Python / FastAPI / SQLite-vec / MCP Runtime
- Architecture: The service provides a semantic memory layer with a REST API and MCP transport, featuring a knowledge graph for structured memory and autonomous consolidation for long-term memory management.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/doobidoo/mcp-memory-service
- Summary: Open-source persistent memory for AI agent pipelines (LangGraph, CrewAI, AutoGen) and Claude. REST API + knowledge graph + autonomous consolidation.

### AIWriteX
- Canonical URL: https://everyagent.si/agent/aiwritex
- Creator: iniwap
- Category: orchestration
- License: Apache-2.0
- Backbone model: Python / CrewAI Orchestrator (likely with DashScope or other LLMs via CrewAI)
- Architecture: This system employs a multi-agent architecture orchestrated by CrewAI, where different agents collaborate on tasks, potentially using tools for web scraping, data processing, and content generation.
- MCP binding: Native tooling only
- Website: https://aiwritex.voidai.cc
- Repository: https://github.com/iniwap/AIWriteX
- Summary: AIWriteX - 微信公众号全自动AI工具：全网热搜舆情聚合+趋势分析+爆款选题+文章采集+一键生成排版发布 | AI自动配图 | 去AI味、过朱雀检测 | 支持小红书/百家号/头条等多平台 | 洗稿润色支持多账号 | 专家赛道 | 小绿书贴图 | 短视频文案 | 手机控制 | 小说连载 | 爆文10w+神器

### atmosphere
- Canonical URL: https://everyagent.si/agent/atmosphere
- Creator: Atmosphere
- Category: orchestration
- License: Apache-2.0
- Backbone model: Python / Async I/O Orchestrator (inferred)
- Architecture: The architecture is inferred to be an asynchronous orchestration system, likely managing concurrent tasks or services, given the project name and associated website.
- MCP binding: Model Context Protocol compliant
- Website: https://async-io.live
- Repository: https://github.com/Atmosphere/atmosphere
- Summary: Portable AI agent runtime for the JVM. One @Agent class runs on Spring AI, LangChain4j, Anthropic, or 9 more behind one SPI. Token streaming, tool calls, human approvals, and governance over WebSocket, SSE, gRPC, or WebTransport/HTTP3. Speaks MCP, A2A, and AG-UI.

### agentops
- Canonical URL: https://everyagent.si/agent/agentops
- Creator: AgentOps-AI
- Category: orchestration
- License: MIT
- Backbone model: Python / Observability SDK
- Architecture: This project provides an SDK for instrumenting AI agents to send telemetry data to an external observability platform, focusing on capturing agent operations and system metrics.
- MCP binding: Native tooling only
- Website: https://agentops.ai
- Repository: https://github.com/AgentOps-AI/agentops
- Summary: Python SDK for AI agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks including CrewAI, Agno, OpenAI Agents SDK, Langchain, Autogen, AG2, and CamelAI

### crewAI-examples
- Canonical URL: https://everyagent.si/agent/crewai-examples
- Creator: crewAIInc
- Category: orchestration
- License: Unknown
- Backbone model: Python / CrewAI Orchestrator
- Architecture: The architecture involves a supervisor agent orchestrating multiple specialized worker agents to achieve a common goal, often following a planner-executor or ReAct-like pattern.
- MCP binding: Native tooling only
- Website: N/A
- Repository: https://github.com/crewAIInc/crewAI-examples
- Summary: A collection of examples that show how to use CrewAI framework to automate workflows.

### reactive-resume
- Canonical URL: https://everyagent.si/agent/reactive-resume
- Creator: reactive-resume
- Category: orchestration
- License: MIT
- Backbone model: Node.js / pnpm / TypeScript / Cloudflare Workers
- Architecture: This project is a monorepo containing multiple applications and packages, orchestrated by pnpm and Turbo, with a focus on web application development and Cloudflare deployment.
- MCP binding: Model Context Protocol compliant
- Website: https://rxresu.me
- Repository: https://github.com/reactive-resume/reactive-resume
- Summary: A one-of-a-kind resume builder that keeps your privacy in mind. Completely secure, customizable, portable, open-source and free forever. Try it out today!

### codebase-memory-mcp
- Canonical URL: https://everyagent.si/agent/codebase-memory-mcp
- Creator: DeusData
- Category: orchestration
- License: MIT
- Backbone model: Python / MCP Runtime (inferred)
- Architecture: Given the lack of information, it's inferred to be a system designed to manage and interact with codebase memory, potentially using an MCP for communication.
- MCP binding: Model Context Protocol compliant
- Website: https://deusdata.github.io/codebase-memory-mcp/
- Repository: https://github.com/DeusData/codebase-memory-mcp
- Summary: High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 158 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.

### chrome-devtools-mcp
- Canonical URL: https://everyagent.si/agent/chrome-devtools-mcp
- Creator: ChromeDevTools
- Category: orchestration
- License: Apache-2.0
- Backbone model: Node.js / TypeScript / MCP Runtime
- Architecture: The system operates as an MCP server, exposing Chrome DevTools functionalities as a set of tools that can be called by external clients, facilitating programmatic browser control and debugging.
- MCP binding: Model Context Protocol compliant
- Website: https://developer.chrome.com/docs/devtools/agents
- Repository: https://github.com/ChromeDevTools/chrome-devtools-mcp
- Summary: Chrome DevTools for coding agents

### TrendRadar
- Canonical URL: https://everyagent.si/agent/trendradar
- Creator: sansan0
- Category: orchestration
- License: GPL-3.0
- Backbone model: Python / LiteLLM (supporting various LLMs) via fastmcp
- Architecture: This system appears to be a data aggregation and analysis pipeline, potentially using an LLM for summarization or trend identification, with a dedicated MCP server for tool exposure.
- MCP binding: Model Context Protocol compliant
- Website: https://trendradar.sandev.cc
- Repository: https://github.com/sansan0/TrendRadar
- Summary: ⭐AI-driven public opinion & trend monitor with multi-platform aggregation, RSS, and smart alerts.🎯 告别信息过载，你的 AI 舆情监控助手与热点筛选工具！聚合多平台热点 + RSS 订阅，支持关键词精准筛选。AI 智能筛选新闻 + AI 翻译 + AI 分析简报直推手机，也支持接入 MCP 架构，赋能 AI 自然语言对话分析、情感洞察与趋势预测等。支持 Docker ，数据本地/云端自持。集成微信/飞书/钉钉/Telegram/邮件/ntfy/bark/slack 等渠道智能推送。

### context7
- Canonical URL: https://everyagent.si/agent/context7
- Creator: upstash
- Category: orchestration
- License: MIT
- Backbone model: TypeScript / MCP Runtime
- Architecture: This project provides SDKs and tooling for the Model Context Protocol, enabling applications to interact with MCP-compliant agents and services.
- MCP binding: Model Context Protocol compliant
- Website: https://context7.com
- Repository: https://github.com/upstash/context7
- Summary: Context7 Platform -- Up-to-date code documentation for LLMs and AI code editors

### ruflo
- Canonical URL: https://everyagent.si/agent/ruflo
- Creator: ruvnet
- Category: orchestration
- License: MIT
- Backbone model: TypeScript / Claude Code Orchestrator with Rust components
- Architecture: Ruflo employs a multi-agent orchestration architecture, coordinating specialized agents in swarms with fault-tolerant consensus, vector memory, and self-learning mechanisms.
- MCP binding: Model Context Protocol compliant
- Website: https://Cognitum.One
- Repository: https://github.com/ruvnet/ruflo
- Summary: 🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated

### Scrapling
- Canonical URL: https://everyagent.si/agent/scrapling
- Creator: D4Vinci
- Category: orchestration
- License: BSD-3-Clause
- Backbone model: Python / Playwright / Selenium alternative
- Architecture: Scrapling provides a library of functions for web scraping, focusing on browser automation and data extraction, rather than an autonomous agent loop.
- MCP binding: Model Context Protocol compliant
- Website: https://scrapling.readthedocs.io/en/latest/
- Repository: https://github.com/D4Vinci/Scrapling
- Summary: 🕷️ An adaptive Web Scraping framework that handles everything from a single request to a full-scale crawl! Don't be shy, join here: https://discord.gg/EMgGbDceNQ and follow here for daily tips and tricks: https://x.com/Scrapling_dev

### worldmonitor
- Canonical URL: https://everyagent.si/agent/worldmonitor
- Creator: koala73
- Category: orchestration
- License: AGPL-3.0
- Backbone model: Node.js / TypeScript Orchestrator
- Architecture: The system appears to be an orchestration platform with extensive linting and policy enforcement scripts, suggesting a focus on maintaining API contracts, rate limits, and secure coding practices across services.
- MCP binding: Model Context Protocol compliant
- Website: https://worldmonitor.app
- Repository: https://github.com/koala73/worldmonitor
- Summary: Real-time global intelligence dashboard. AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking in a unified situational awareness interface

### gemini-cli
- Canonical URL: https://everyagent.si/agent/gemini-cli
- Creator: google-gemini
- Category: orchestration
- License: Apache-2.0
- Backbone model: Node.js / Google Gemini API
- Architecture: The system appears to be an orchestration layer for Gemini models, supporting agent-to-agent communication and sandboxed execution, likely using a tool-calling or function-calling paradigm.
- MCP binding: Model Context Protocol compliant
- Website: https://geminicli.com
- Repository: https://github.com/google-gemini/gemini-cli
- Summary: An open-source AI agent that brings the power of Gemini directly into your terminal.

### n8n
- Canonical URL: https://everyagent.si/agent/n8n
- Creator: n8n-io
- Category: orchestration
- License: Unknown
- Backbone model: Node.js / n8n Workflow Engine
- Architecture: n8n uses a node-based visual programming paradigm where users define workflows by connecting various 'nodes' representing applications, services, or logic, enabling event-driven automation and data transformation.
- MCP binding: Model Context Protocol compliant
- Website: https://n8n.io
- Repository: https://github.com/n8n-io/n8n
- Summary: Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.

### nanobot
- Canonical URL: https://everyagent.si/agent/nanobot
- Creator: HKUDS
- Category: coding
- License: MIT
- Backbone model: Python / Anthropic, OpenAI SDK, MCP Runtime
- Architecture: The system likely employs a planner-executor or ReAct-like loop, integrating various tools and potentially orchestrating multiple agents through the MCP protocol for complex task execution.
- MCP binding: Model Context Protocol compliant
- Website: https://nanobot.wiki
- Repository: https://github.com/HKUDS/nanobot
- Summary: Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat apps

### cherry-studio
- Canonical URL: https://everyagent.si/agent/cherry-studio
- Creator: CherryHQ
- Category: coding
- License: AGPL-3.0
- Backbone model: TypeScript / Electron / OpenAI SDK tool-calling loop
- Architecture: This project appears to be an Electron application with a main process and a renderer process, likely orchestrating AI model calls (implied by 'aiCore' bench scripts) for code generation and other producer-centric tasks.
- MCP binding: Native tooling only
- Website: https://cherryai.com
- Repository: https://github.com/CherryHQ/cherry-studio
- Summary: AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs

### ai-agent-book
- Canonical URL: https://everyagent.si/agent/ai-agent-book
- Creator: bojieli
- Category: coding
- License: Apache-2.0
- Backbone model: Python / OpenAI SDK tool-calling loop
- Architecture: The project provides a foundational Python environment with core dependencies for building various agent architectures, including those leveraging OpenAI's API for tool calling and response generation, and Pydantic for structured data hand…
- MCP binding: Native tooling only
- Website: N/A
- Repository: https://github.com/bojieli/ai-agent-book
- Summary: 《深入理解 AI Agent：设计原理与工程实践》（李博杰 著）开源主仓库：全书正文、编译版 PDF 与按章配套代码

### ppt-master
- Canonical URL: https://everyagent.si/agent/ppt-master-2
- Creator: hugohe3
- Category: coding
- License: MIT
- Backbone model: Python / pip dependency orchestrator
- Architecture: The architecture seems to be a modular skill-based system, where a 'PPT Master' skill encapsulates its own dependencies, suggesting a plugin or extension model.
- MCP binding: Native tooling only
- Website: https://hugohe3.github.io/ppt-master-examples/
- Repository: https://github.com/hugohe3/ppt-master
- Summary: AI turns documents or topics into real, native PowerPoint decks—with native shapes, transitions and animations, data-backed charts and tables on demand, audio narration from speaker notes, and support for your own .pptx templates. · by Hugo He

### ppt-master
- Canonical URL: https://everyagent.si/agent/ppt-master
- Creator: hugohe3
- Category: coding
- License: MIT
- Backbone model: Python / Skill-based Tooling
- Architecture: The architecture seems to be a modular skill designed to be integrated into a larger system, providing specific functionalities related to presentation generation or manipulation.
- MCP binding: Native tooling only
- Website: https://hugohe3.github.io/ppt-master-examples/
- Repository: https://github.com/hugohe3/ppt-master
- Summary: AI turns documents or topics into real, native PowerPoint decks—with native shapes, transitions and animations, data-backed charts and tables on demand, audio narration from speaker notes, and support for your own .pptx templates. · by Hugo He

### daily_stock_analysis
- Canonical URL: https://everyagent.si/agent/daily-stock-analysis
- Creator: ZhuLinsen
- Category: coding
- License: MIT
- Backbone model: Python / SQLAlchemy Orchestrator with multiple data source integrations (efinance, akshare, tushare, yfinance, longbridge)
- Architecture: The system orchestrates data fetching from various financial APIs and databases, processes it, and likely stores it using SQLAlchemy, with scheduled execution for daily updates.
- MCP binding: Native tooling only
- Website: https://dsa.zhulinsen.tech
- Repository: https://github.com/ZhuLinsen/daily_stock_analysis
- Summary: LLM 驱动的多市场股票智能分析系统：多源行情、实时新闻、决策看板与自动推送，支持零成本定时运行。 LLM-powered multi-market stock analysis system with multi-source market data, real-time news, decision dashboard, automated notifications, and cost-free scheduled runs.

### career-ops
- Canonical URL: https://everyagent.si/agent/career-ops
- Creator: career-ops-hq
- Category: coding
- License: MIT
- Backbone model: Node.js / OpenAI SDK tool-calling loop (via OpenRouter)
- Architecture: The system operates as a modular pipeline, executing distinct job search and application tasks through a series of Node.js scripts, each acting as a specialized tool or agent.
- MCP binding: Native tooling only
- Website: https://career-ops.org
- Repository: https://github.com/career-ops-hq/career-ops
- Summary: Open-source AI job search agent and job finder: scan job boards, score each job 1-5 against your CV before you apply, tailor an ATS-friendly resume and cover letter, get interview prep and a job application tracker. It helps you fill in each application; you press Submit. Runs locally in your AI coding CLI (Claude Code, Codex, OpenCode and more).

### Front-End-Checklist
- Canonical URL: https://everyagent.si/agent/front-end-checklist
- Creator: thedaviddias
- Category: coding
- License: MIT
- Backbone model: TypeScript / Node.js / Turborepo monorepo with Biome for linting and formatting.
- Architecture: The project is structured as a Turborepo monorepo, utilizing TypeScript for its scripts and applications, with a focus on generating and validating checklist content.
- MCP binding: Native tooling only
- Website: https://frontendchecklist.io
- Repository: https://github.com/thedaviddias/Front-End-Checklist
- Summary: 🗂 The essential checklist for modern web development, for humans and AI agents

### learn-claude-code
- Canonical URL: https://everyagent.si/agent/learn-claude-code
- Creator: shareAI-lab
- Category: coding
- License: MIT
- Backbone model: Python / Anthropic SDK
- Architecture: The system appears to be a simple script-based interaction with the Anthropic API, likely involving direct prompts for code generation or analysis, without complex agentic loops.
- MCP binding: Native tooling only
- Website: https://learn.shareai.run
- Repository: https://github.com/shareAI-lab/learn-claude-code
- Summary: Bash is all you need - A nano claude code–like 「agent harness」, built from 0 to 1

### Agent-Reach
- Canonical URL: https://everyagent.si/agent/agent-reach
- Creator: Panniantong
- Category: coding
- License: MIT
- Backbone model: Python / MCP CLI tool
- Architecture: This project functions as a tool-calling server or CLI, providing a suite of web-scraping and search functionalities that can be integrated into an agent's perception loop.
- MCP binding: Native tooling only
- Website: N/A
- Repository: https://github.com/Panniantong/Agent-Reach
- Summary: Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.

### ZeparHyfar/mcp-datetime
- Canonical URL: https://everyagent.si/agent/zeparhyfar-mcp-datetime
- Creator: ZeparHyfar
- Category: orchestration
- License: Unknown
- Backbone model: Python / MCP Runtime
- Architecture: A simple MCP server exposing specific datetime and file naming functionalities as tools, without an internal agent loop.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/ZeparHyfar/mcp-datetime
- Summary: Date and time functions in various formats.

### ws-mcp
- Canonical URL: https://everyagent.si/agent/ws-mcp
- Creator: nick1udwig
- Category: orchestration
- License: Unknown
- Backbone model: Python / WebSocket / JSON-RPC
- Architecture: A Python application that acts as a WebSocket server, translating incoming WebSocket messages into MCP commands and forwarding them to an underlying MCP server, then relaying responses back.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/nick1udwig/ws-mcp
- Summary: Wrap MCP servers with a WebSocket, for use with kibitz.

### pyroprompts/any-chat-completions-mcp
- Canonical URL: https://everyagent.si/agent/pyroprompts-any-chat-completions-mcp
- Creator: pyroprompts
- Category: orchestration
- License: Unknown
- Backbone model: TypeScript / OpenAI SDK tool-calling loop
- Architecture: This project implements a Model Context Protocol (MCP) server that exposes a single 'chat' tool, which then relays user prompts to a configured OpenAI SDK-compatible chat completion API, acting as a proxy or adapter.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/pyroprompts/any-chat-completions-mcp
- Summary: Chat with any OpenAI SDK-compatible Chat Completions API, such as Perplexity, Groq and xAI.

### pwh-pwh/cal-mcp
- Canonical URL: https://everyagent.si/agent/pwh-pwh-cal-mcp
- Creator: pwh-pwh
- Category: orchestration
- License: Unknown
- Backbone model: Bun / FastMCP / expr-eval
- Architecture: A FastMCP server built with Bun, it uses the expr-eval library to parse and compute mathematical expressions received via standard input/output.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/pwh-pwh/cal-mcp
- Summary: Evaluate mathematical expressions.

### latex-mcp-server
- Canonical URL: https://everyagent.si/agent/latex-mcp-server
- Creator: Yeok-c
- Category: orchestration
- License: Unknown
- Backbone model: Python / Node.js / MCP Runtime
- Architecture: The system operates as a hybrid Python/TypeScript MCP server, where Python handles core server logic and some tools, while a Node.js bridge delegates specific functions (like text summarization) to TypeScript modules, all orchestrated via…
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/Yeok-c/latex-mcp-server
- Summary: Compile LaTeX, download, organize and read cited papers, run visualization scripts and add figures and tables to LaTeX documents.

### akseyh/bear-mcp-server
- Canonical URL: https://everyagent.si/agent/akseyh-bear-mcp-server
- Creator: akseyh
- Category: orchestration
- License: Unknown
- Backbone model: Node.js / MCP SDK tool-calling loop
- Architecture: This project functions as an MCP server, exposing Bear Notes database operations (read, search, tag listing) as callable tools via a direct SQLite interface.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/akseyh/bear-mcp-server
- Summary: Read Bear notes (macOS only).

### AbdelStark/bitcoin-mcp
- Canonical URL: https://everyagent.si/agent/abdelstark-bitcoin-mcp
- Creator: AbdelStark
- Category: orchestration
- License: Unknown
- Backbone model: Node.js / MCP Runtime with bitcoinjs-lib and ECPair
- Architecture: A Model Context Protocol (MCP) server exposing Bitcoin and Lightning Network functionalities as tools, designed to be integrated with AI models like Claude Desktop or Goose via STDIO or SSE.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/AbdelStark/bitcoin-mcp
- Summary: Interact with Bitcoin: generate keys, validate addresses, decode transactions and query the blockchain.

### Gaffx/volatility-mcp
- Canonical URL: https://everyagent.si/agent/gaffx-volatility-mcp
- Creator: Gaffx
- Category: orchestration
- License: Unknown
- Backbone model: Python / FastAPI / Volatility 3
- Architecture: A FastAPI server acts as an intermediary, translating MCP client requests into Volatility 3 commands for memory image analysis and returning the results.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/Gaffx/volatility-mcp
- Summary: Memory forensics with Volatility 3, exposing plugins such as pslist and netscan through REST APIs.

### thinkchainai/agentinterviewsmcp
- Canonical URL: https://everyagent.si/agent/thinkchainai-agentinterviewsmcp
- Creator: thinkchainai
- Category: orchestration
- License: Unknown
- Backbone model: Node.js / MCP Remote Proxy
- Architecture: The system acts as an MCP server proxy, forwarding requests from AI assistants to the Agent Interviews API, enabling natural language queries to retrieve structured interview data.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/thinkchainai/agentinterviews_mcp
- Summary: Run AI-led qualitative research interviews and surveys with Agent Interviews: create interviewers, manage projects, recruit participants and analyze results.

### video-creator/ffmpeg-mcp
- Canonical URL: https://everyagent.si/agent/video-creator-ffmpeg-mcp
- Creator: video-creator
- Category: orchestration
- License: Unknown
- Backbone model: Python / MCP CLI Runtime
- Architecture: This is a tool-calling server exposing FFmpeg functionalities as distinct tools, designed to be integrated into a larger multi-agent system via the Model Context Protocol (MCP).
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/video-creator/ffmpeg-mcp.git
- Summary: Local video search, trimming, stitching and playback through conversation, using the ffmpeg command line.

### last9/last9-mcp-server
- Canonical URL: https://everyagent.si/agent/last9-last9-mcp-server
- Creator: last9
- Category: orchestration
- License: Unknown
- Backbone model: Go / Node.js / Model Context Protocol (MCP) server, integrating with Claude, Cursor, Windsurf, and VS Code.
- Architecture: It functions as an MCP server, providing a standardized interface for AI agents to query and retrieve observability data from Last9's platform, supporting both HTTP and STDIO transports.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/last9/last9-mcp-server
- Summary: Bring real-time production logs, metrics and traces from Last9 into your local environment to fix code.

### QGIS MCP
- Canonical URL: https://everyagent.si/agent/qgis-mcp
- Creator: jjsantos01
- Category: orchestration
- License: Unknown
- Backbone model: Claude AI via MCP / Python / QGIS Plugin
- Architecture: The system consists of a QGIS plugin that creates a socket server within QGIS and a Python server that implements the Model Context Protocol to connect Claude AI to the QGIS plugin, enabling two-way communication and tool execution.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/jjsantos01/qgis_mcp
- Summary: Connects QGIS Desktop to Claude for prompt-assisted project creation, layer loading and code execution.

### chatmcp/mcp-server-chatsum
- Canonical URL: https://everyagent.si/agent/chatmcp-mcp-server-chatsum
- Creator: chatmcp
- Category: orchestration
- License: Unknown
- Backbone model: Node.js / @modelcontextprotocol/sdk
- Architecture: The system operates as an MCP server, querying a SQLite database for chat messages based on provided parameters and then summarizing them.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/chatmcp/mcp-server-chatsum
- Summary: Query and summarize your chat messages with AI prompts.

### lnbits/LNbits-MCP-Server
- Canonical URL: https://everyagent.si/agent/lnbits-lnbits-mcp-server
- Creator: lnbits
- Category: orchestration
- License: Unknown
- Backbone model: Python / MCP Runtime
- Architecture: This is a tool-calling server that exposes LNbits API functionalities as MCP tools, allowing an AI client to interact with a Lightning wallet through natural language commands.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/lnbits/LNbits-MCP-Server
- Summary: LNbits Lightning Network wallet integration.

### finmap-org/mcp-server
- Canonical URL: https://everyagent.si/agent/finmap-org-mcp-server
- Creator: finmap-org
- Category: orchestration
- License: Unknown
- Backbone model: Node.js / MCP Runtime
- Architecture: This is a tool-calling server that exposes a set of financial data retrieval functions via the Model Context Protocol (MCP) and an HTTP API, allowing agents to query historical stock exchange data, sectors, companies, and market statistics.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/finmap-org/mcp-server
- Summary: Historical US, UK, Russian and Turkish stock exchange data from finmap: sectors, tickers, company profiles, market cap, volume and treemap visualizations.

### vivekvells/mcp-pandoc
- Canonical URL: https://everyagent.si/agent/vivekvells-mcp-pandoc
- Creator: vivekVells
- Category: orchestration
- License: Unknown
- Backbone model: Python / MCP Runtime + Pandoc
- Architecture: This is a Model Context Protocol (MCP) server that exposes Pandoc's document conversion capabilities as a single tool, allowing agents to transform content between various formats with optional styling and filtering.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/vivekVells/mcp-pandoc
- Summary: Document format conversion using Pandoc: Markdown, HTML, PDF, DOCX, CSV and more.

### valado/pantheon-mcp
- Canonical URL: https://everyagent.si/agent/valado-pantheon-mcp
- Creator: valado
- Category: orchestration
- License: Unknown
- Backbone model: TypeScript / @modelcontextprotocol/sdk
- Architecture: The system operates as an MCP server, exposing tools to list, get, and search through a collection of pre-defined AI agent descriptions, categorized by domain.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/valado/pantheon-mcp
- Summary: Serves task-specific instructions to agents instead of static Markdown files.

### TamarEngel/jira-github-mcp
- Canonical URL: https://everyagent.si/agent/tamarengel-jira-github-mcp
- Creator: TamarEngel
- Category: orchestration
- License: Unknown
- Backbone model: Python / fastmcp MCP Server
- Architecture: The system operates as an MCP server, exposing a suite of tools for Jira, GitHub, and local Git operations, which an external AI agent (like GitHub Copilot) can invoke to automate developer workflows.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/TamarEngel/jira-github-mcp
- Summary: Integrates Jira and GitHub to automate developer workflows from issue tracking to branches, commits, pull requests and merges.

### pskill9/website-downloader
- Canonical URL: https://everyagent.si/agent/pskill9-website-downloader
- Creator: pskill9
- Category: orchestration
- License: Unknown
- Backbone model: TypeScript / @modelcontextprotocol/sdk / wget
- Architecture: This is a tool-calling server that exposes a single `download_website` function, which wraps the `wget` command-line utility to fetch website content.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/pskill9/website-downloader
- Summary: Download entire websites using wget, preserving their structure and converting links to work locally.

### OpenZeppelin/contracts-wizard
- Canonical URL: https://everyagent.si/agent/openzeppelin-contracts-wizard
- Creator: OpenZeppelin
- Category: orchestration
- License: Unknown
- Backbone model: TypeScript / Node.js / MCP Runtime
- Architecture: This project acts as a contract generation service, offering a web UI, CLI, TypeScript API, and MCP servers to programmatically or interactively build smart contracts based on user-defined parameters and features.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/OpenZeppelin/contracts-wizard/tree/master/packages/mcp
- Summary: Generate secure smart contracts in multiple languages from OpenZeppelin Wizard templates.

### 21st-dev/Magic-MCP
- Canonical URL: https://everyagent.si/agent/21st-dev-magic-mcp
- Creator: 21st-dev
- Category: orchestration
- License: Unknown
- Backbone model: Node.js / TypeScript / MCP Runtime
- Architecture: This project acts as a stdio proxy forwarding MCP messages to the main 21st MCP HTTP server, translating legacy tool names to current ones, and enabling access to UI generation and component search capabilities.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/21st-dev/magic-mcp
- Summary: Create UI components inspired by 21st.dev design engineers.

### planetscale/mcp
- Canonical URL: https://everyagent.si/agent/planetscale-mcp
- Creator: planetscale
- Category: orchestration
- License: Unknown
- Backbone model: Go / PlanetScale API client
- Architecture: The CLI acts as a direct interface to the PlanetScale platform, translating user commands into API calls for managing database resources.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/planetscale/cli?tab=readme-ov-file#mcp-server-integration
- Summary: Built into the PlanetScale CLI: direct access to your PlanetScale databases.

### niledatabase/nile-mcp-server
- Canonical URL: https://everyagent.si/agent/niledatabase-nile-mcp-server
- Creator: niledatabase
- Category: orchestration
- License: Unknown
- Backbone model: TypeScript / @modelcontextprotocol/sdk / Express.js
- Architecture: The server implements the Model Context Protocol, exposing a set of tools for database management and SQL execution, communicating via STDIO or SSE over HTTP.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/niledatabase/nile-mcp-server
- Summary: Manage and query Nile Postgres databases, tenants, users and auth.

### joshuarileydev/supabase-mcp-server
- Canonical URL: https://everyagent.si/agent/joshuarileydev-supabase-mcp-server
- Creator: joshuarileydev
- Category: orchestration
- License: Unknown
- Backbone model: TypeScript / Node.js / MCP SDK
- Architecture: It functions as a tool-calling server, translating MCP requests into Supabase Management API calls for project and organization management.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/joshuarileydev/supabase
- Summary: Create and manage Supabase projects and organizations.

### bram2w/baserow
- Canonical URL: https://everyagent.si/agent/bram2w-baserow
- Creator: bram2w
- Category: orchestration
- License: Unknown
- Backbone model: Django / Vue.js / PostgreSQL with an integrated AI Assistant (Kuma)
- Architecture: Baserow provides a full-stack platform with a Django backend, Vue.js frontend, and PostgreSQL database, featuring an AI Assistant (Kuma) that enables natural language interaction for database and workflow creation, alongside a robust API-f…
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/bram2w/baserow
- Summary: Baserow database integration: search and list tables, and create, read, update and delete rows.

### alexanderzuev/supabase-mcp-server
- Canonical URL: https://everyagent.si/agent/alexanderzuev-supabase-mcp-server
- Creator: alexander-zuev
- Category: orchestration
- License: Unknown
- Backbone model: Python / MCP Runtime
- Architecture: The server acts as an MCP endpoint, providing a set of pre-defined tools to interact with Supabase's PostgreSQL database, Management API, and Auth Admin SDK, all while enforcing a three-tier safety system for SQL operations.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/alexander-zuev/supabase-mcp-server
- Summary: Execute SQL queries and explore Supabase databases.

### saurabhsharma2u/search-console-mcp
- Canonical URL: https://everyagent.si/agent/saurabhsharma2u-search-console-mcp
- Creator: saurabhsharma2u
- Category: orchestration
- License: Unknown
- Backbone model: TypeScript / Node.js / MCP Runtime
- Architecture: This is a tool-calling server that integrates with multiple SEO and analytics APIs (Google Search Console, Bing Webmaster Tools, GA4, AdSense) and provides a unified set of tools for AI agents, performing server-side analysis before data r…
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/saurabhsharma2u/search-console-mcp
- Summary: Interact with Google Search Console and Bing Webmaster Tools.

### teddyzxcv/ntfy-mcp
- Canonical URL: https://everyagent.si/agent/teddyzxcv-ntfy-mcp
- Creator: teddyzxcv
- Category: orchestration
- License: Unknown
- Backbone model: Node.js / MCP Runtime
- Architecture: This is a simple MCP server designed to receive task completion signals and forward them as notifications via the ntfy service.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/teddyzxcv/ntfy-mcp
- Summary: Send notifications to your phone using ntfy.

### areweai/tsgram-mcp
- Canonical URL: https://everyagent.si/agent/areweai-tsgram-mcp
- Creator: areweai
- Category: orchestration
- License: Unknown
- Backbone model: TypeScript / Node.js / Docker / Claude 3.5 Sonnet or GPT-4 via OpenRouter/OpenAI API
- Architecture: It operates as an MCP server running locally within Docker, bridging Telegram interactions with a local Claude Code session to provide AI-powered code analysis and file manipulation capabilities.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/areweai/tsgram-mcp
- Summary: Use Claude with local workspace access from Telegram on your phone: read, write and code on the go.

### tumf/mcp-shell-server
- Canonical URL: https://everyagent.si/agent/tumf-mcp-shell-server
- Creator: tumf
- Category: orchestration
- License: Unknown
- Backbone model: Python / MCP SDK v1 Server
- Architecture: The server implements the Model Context Protocol (MCP) to execute allowlisted commands via subprocess argv, enforcing execution limits, contained redirection, and a minimal child environment.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/tumf/mcp-shell-server
- Summary: Secure shell command execution.

### maxim-saplin/mcpsafelocalpythonexecutor
- Canonical URL: https://everyagent.si/agent/maxim-saplin-mcpsafelocalpythonexecutor
- Creator: maxim-saplin
- Category: orchestration
- License: Unknown
- Backbone model: Python / smolagents LocalPythonExecutor / MCP CLI
- Architecture: It's an MCP server wrapping Hugging Face's `LocalPythonExecutor` from the `smolagents` framework, providing a restricted Python runtime for LLM-generated code.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/maxim-saplin/mcp_safe_local_python_executor
- Summary: Safe Python interpreter based on Hugging Face smolagents' LocalPythonExecutor.

### ferrislucas/iterm-mcp
- Canonical URL: https://everyagent.si/agent/ferrislucas-iterm-mcp
- Creator: ferrislucas
- Category: orchestration
- License: Unknown
- Backbone model: TypeScript / @modelcontextprotocol/sdk
- Architecture: A Model Context Protocol server exposing iTerm2 functionalities as tools, allowing an external LLM to read output, write commands, and send control characters to the active terminal session.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/ferrislucas/iterm-mcp
- Summary: Access iTerm: run commands and ask questions about what is shown in the terminal.

### automateyournetwork/pyATSMCP
- Canonical URL: https://everyagent.si/agent/automateyournetwork-pyatsmcp
- Creator: automateyournetwork
- Category: orchestration
- License: Unknown
- Backbone model: Python / pyATS / MCP Runtime
- Architecture: The system functions as an MCP server, wrapping pyATS/Genie functionalities into 26 structured tools that an AI agent can call over Streamable HTTP, with built-in guardrails and an in-memory audit log.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/automateyournetwork/pyATS_MCP
- Summary: Structured, model-driven interaction with network devices via Cisco pyATS.

### microsoft/playwright-mcp
- Canonical URL: https://everyagent.si/agent/microsoft-playwright-mcp
- Creator: microsoft
- Category: orchestration
- License: Unknown
- Backbone model: Node.js / Playwright / Model Context Protocol SDK
- Architecture: The system operates as an MCP server, enabling LLMs to interact with web pages by processing structured accessibility snapshots from Playwright, rather than relying on visual input.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/microsoft/playwright-mcp
- Summary: Playwright browser automation: interact with web pages through structured accessibility snapshots.

### thinkchainai/mcpbundles
- Canonical URL: https://everyagent.si/agent/thinkchainai-mcpbundles
- Creator: thinkchainai
- Category: orchestration
- License: Unknown
- Backbone model: Node.js / MCP Runtime (via npx mcp-remote@latest)
- Architecture: This is an authenticated MCP server proxy that aggregates tools from user-defined bundles, providing a unified endpoint for tool discovery, execution, and management across various integrated providers.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/thinkchainai/mcpbundles
- Summary: Create custom tool bundles, connect providers with OAuth or API keys, and use one MCP server across many integrations, with a UI for bundles and credentials.

### Tool Definition Quality Score (TDQS)
- Canonical URL: https://everyagent.si/agent/tool-definition-quality-score-tdqs
- Creator: glama-ai
- Category: orchestration
- License: Unknown
- Backbone model: LLM-agnostic evaluation pipeline (likely Python-based for orchestration)
- Architecture: A four-stage pipeline: context signal extraction, hard gates, LLM rubric evaluation, and deterministic post-processing, culminating in a quality score and tier.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/glama-ai/tool-definition-quality-score
- Summary: TDQS is an open framework for scoring how well an [MCP](https://modelcontextprotocol.io) tool definition communicates to an AI agent. It is the methodology [Glama](https://glama.ai) uses to score [every tool](https://glama.ai/mcp/tools) of every [MCP server](https://glama.ai/mcp/servers) and [hosted connector](https://glama.ai/mcp/connectors) in its registry.

### time MCP Server
- Canonical URL: https://everyagent.si/agent/time-mcp-server
- Creator: Model Context Protocol
- Category: orchestration
- License: MIT
- Backbone model: Python / MCP Runtime
- Architecture: This is a tool-calling server that exposes two distinct functions for retrieving current time and converting time between specified IANA timezones, designed to be integrated into larger LLM orchestration frameworks.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/modelcontextprotocol/servers/tree/main/src/time
- Summary: Time MCP Server <!-- mcp-name: io.github.modelcontextprotocol/server-time --> A Model Context Protocol server that provides time and timezone conversion capabilities. This server enables LLMs to get current time information and perform timezone conversions using IANA timezone names, with automatic system timezone detection.

### sequentialthinking MCP Server
- Canonical URL: https://everyagent.si/agent/sequentialthinking-mcp-server
- Creator: Model Context Protocol
- Category: orchestration
- License: MIT
- Backbone model: Node.js / MCP Runtime
- Architecture: This server exposes a single tool, `sequential_thinking`, which allows an orchestrating agent to manage a detailed, step-by-step thinking process, including revision and branching of thought paths.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/modelcontextprotocol/servers/tree/main/src/sequentialthinking
- Summary: Sequential Thinking MCP Server An MCP server implementation that provides a tool for dynamic and reflective problem-solving through a structured thinking process. Published on npm as [`@modelcontextprotocol/server-sequential-thinking`](https://www.npmjs.com/package/@modelcontextprotocol/server-sequential-thinking).

### memory MCP Server
- Canonical URL: https://everyagent.si/agent/memory-mcp-server
- Creator: Model Context Protocol
- Category: orchestration
- License: MIT
- Backbone model: Node.js / MCP Runtime
- Architecture: The server implements a knowledge graph with entities, relations, and observations, exposing an API for CRUD operations and search, and notifying clients of graph changes via resource updates.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/modelcontextprotocol/servers/tree/main/src/memory
- Summary: Knowledge Graph Memory Server A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats. Published on npm as [`@modelcontextprotocol/server-memory`](https://www.npmjs.com/package/@modelcontextprotocol/server-memory).

### git MCP Server
- Canonical URL: https://everyagent.si/agent/git-mcp-server
- Creator: Model Context Protocol
- Category: orchestration
- License: MIT
- Backbone model: Python / MCP Runtime
- Architecture: A Model Context Protocol server exposing a suite of Git commands as tools, allowing an orchestrating LLM to perform repository operations.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/modelcontextprotocol/servers/tree/main/src/git
- Summary: mcp-server-git: A git MCP server <!-- mcp-name: io.github.modelcontextprotocol/server-git --> Overview

### filesystem MCP Server
- Canonical URL: https://everyagent.si/agent/filesystem-mcp-server
- Creator: Model Context Protocol
- Category: orchestration
- License: MIT
- Backbone model: Node.js / MCP Runtime
- Architecture: A server exposing a suite of filesystem tools via the Model Context Protocol, featuring dynamic directory access control through MCP Roots and detailed tool annotations for client awareness.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/modelcontextprotocol/servers/tree/main/src/filesystem
- Summary: Filesystem MCP Server Node.js server implementing Model Context Protocol (MCP) for filesystem operations. Published on npm as [`@modelcontextprotocol/server-filesystem`](https://www.npmjs.com/package/@modelcontextprotocol/server-filesystem).

### fetch MCP Server
- Canonical URL: https://everyagent.si/agent/fetch-mcp-server
- Creator: Model Context Protocol
- Category: orchestration
- License: MIT
- Backbone model: Python / Node.js / MCP Runtime
- Architecture: This is a tool-calling server that exposes a 'fetch' capability, allowing an orchestrating LLM to retrieve web content, optionally converting it to markdown and supporting chunked retrieval via start_index.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/modelcontextprotocol/servers/tree/main/src/fetch
- Summary: Fetch MCP Server <!-- mcp-name: io.github.modelcontextprotocol/server-fetch --> A Model Context Protocol server that provides web content fetching capabilities. This server enables LLMs to retrieve and process content from web pages, converting HTML to markdown for easier consumption.

### everything MCP Server
- Canonical URL: https://everyagent.si/agent/everything-mcp-server
- Creator: Model Context Protocol
- Category: orchestration
- License: MIT
- Backbone model: Node.js / MCP Runtime
- Architecture: The server implements various MCP primitives like prompts, tools, and resources, acting as a comprehensive testbed for the protocol's features.
- MCP binding: Model Context Protocol compliant
- Website: N/A
- Repository: https://github.com/modelcontextprotocol/servers/tree/main/src/everything
- Summary: Everything MCP Server **[Architecture](docs/architecture.md) | [Project Structure](docs/structure.md)

### Claude Code
- Canonical URL: https://everyagent.si/agent/claude-code
- Creator: Anthropic
- Category: coding
- License: Commercial
- Backbone model: Claude 3.7 Sonnet
- Architecture: Native Terminal ReAct with Hybrid Thinking & Sub-Agent Dispatch
- MCP binding: Model Context Protocol compliant
- Website: https://anthropic.com
- Repository: https://github.com/anthropics/claude-code
- Summary: An agentic CLI that lets Claude understand git repositories, edit files, run commands, and orchestrate complex local workflows.

### Devin
- Canonical URL: https://everyagent.si/agent/devin
- Creator: Cognition AI
- Category: coding
- License: Commercial
- Backbone model: Claude 3.7 Sonnet / Proprietary Reasoning
- Architecture: Long-Horizon Planning + Sandboxed Shell + Browser Debugger
- MCP binding: Model Context Protocol compliant
- Website: https://cognition.ai
- Repository: N/A
- Summary: Autonomous AI software engineer that plans and executes long-horizon engineering tasks inside a sandboxed environment.

### OpenAI Deep Research
- Canonical URL: https://everyagent.si/agent/openai-deep-research
- Creator: OpenAI
- Category: research
- License: Commercial
- Backbone model: o3 Reasoning
- Architecture: Multi-Step Web Browsing + Long-Horizon Agentic Research Loop
- MCP binding: Native tooling only
- Website: https://openai.com
- Repository: N/A
- Summary: Autonomous research agent that browses the live web, synthesises cited reports, and chains tool calls over extended horizons.

### OpenHands
- Canonical URL: https://everyagent.si/agent/openhands
- Creator: All Hands AI
- Category: coding
- License: Open Source
- Backbone model: Model Agnostic (Claude / GPT / Llama)
- Architecture: Event Stream Architecture + Sandboxed Docker Runtime
- MCP binding: Model Context Protocol compliant
- Website: https://all-hands.dev
- Repository: https://github.com/All-Hands-AI/OpenHands
- Summary: Open-source software development agent platform with a sandboxed runtime and event-stream architecture for reproducible agent runs.

### Claude Computer Use
- Canonical URL: https://everyagent.si/agent/claude-computer-use
- Creator: Anthropic
- Category: browser
- License: Commercial
- Backbone model: Claude 3.5 Sonnet
- Architecture: Vision + Action Loop (Screenshot → Mouse/Keyboard Control)
- MCP binding: Model Context Protocol compliant
- Website: https://anthropic.com
- Repository: https://github.com/anthropics/anthropic-quickstarts
- Summary: Multimodal computer-using agent that operates real desktop operating systems through screenshots and synthetic keyboard/mouse input.

### DeepSeek-R1 Agentic Reasoner
- Canonical URL: https://everyagent.si/agent/deepseek-r1-agentic-reasoner
- Creator: DeepSeek AI
- Category: reasoning
- License: Open Source
- Backbone model: DeepSeek-R1
- Architecture: Reinforcement-Learned Chain-of-Thought + Tool Calling
- MCP binding: Native tooling only
- Website: https://deepseek.com
- Repository: https://github.com/deepseek-ai/DeepSeek-R1
- Summary: Open-weights reasoning model producing long deliberation traces that can be wrapped in an autonomous tool-calling agent loop.