Python MCP Agent Framework Docs
支持查询主流agent框架技术文档的MCP server（支持stdio和sse两种传输协议）, 支持 langchain、llama-index、autogen、agno、openai-agents-sdk、mcp-doc、camel-ai 和 crew-ai
What is Python MCP Agent Framework Docs?
Python MCP Agent Framework Docs is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to 支持查询主流agent框架技术文档的mcp server（支持stdio和sse两种传输协议）, 支持 langchain、llama-index、autogen、agno、openai-agents-sdk、mcp-doc、camel-ai 和 crew-ai
支持查询主流agent框架技术文档的MCP server（支持stdio和sse两种传输协议）, 支持 langchain、llama-index、autogen、agno、openai-agents-sdk、mcp-doc、camel-ai 和 crew-ai
This server falls under the Coding Agents category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- 支持查询主流agent框架技术文档的MCP server（支持stdio和sse两种传输协议）, 支持 langchai
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx python-mcp-server-clientConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Python MCP Agent Framework Docs
Python MCP Agent Framework Docs is an MCP server that gives AI assistants instant, search-driven access to the official technical documentation of eight major LLM agent frameworks: LangChain, LlamaIndex, AutoGen, Agno, OpenAI Agents SDK, the MCP specification, Camel-AI, and CrewAI. Instead of hallucinating API details, the AI can query this server for accurate, up-to-date documentation snippets using a Google search backend (via Serper). The server supports both stdio and SSE transport modes, making it usable from desktop clients and custom Python agents alike.
Prerequisites
- Python 3.10+ and the uv package manager (https://astral.sh/uv)
- SERPER_API_KEY from serper.dev for the Google search backend
- OPENAI_API_KEY if using the bundled Python client (not required for MCP client integration)
- An MCP client such as Claude Desktop, Cline (VS Code), or Cursor
Install uv
The project uses uv for dependency management. Install it with the official one-liner for your platform.
# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh
# Windows PowerShell
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"Clone the repository
Clone the project to your local machine. The server runs from source using uv.
git clone https://github.com/GobinFan/python-mcp-server-client.git
cd python-mcp-server-clientSet required environment variables
Create a .env file or export the variables in your shell. SERPER_API_KEY is mandatory for the documentation search tool to work.
export SERPER_API_KEY=your-serper-key
export OPENAI_API_KEY=your-openai-key # only needed for the Python clientAdd the server to your MCP client config (stdio mode)
Configure Claude Desktop or Cursor to launch the server via uv. Replace the directory path with the absolute path where you cloned the repo.
{
"mcpServers": {
"agent-framework-docs": {
"command": "uv",
"args": ["run", "--directory", "/absolute/path/to/python-mcp-server-client", "main.py"],
"env": {
"SERPER_API_KEY": "your-serper-key"
}
}
}
}Or start the SSE server for remote/multi-client access
Launch the server in SSE mode to connect from multiple clients or a custom Python agent. The server listens on the specified host and port.
uv run main.py --host 0.0.0.0 --port 8020Query framework documentation
Ask your AI assistant about any of the eight supported frameworks. The server's get_docs tool performs a domain-targeted search and returns the relevant documentation text.
Python MCP Agent Framework Docs Examples
Client configuration
Claude Desktop stdio configuration running the server via uv from a local clone.
{
"mcpServers": {
"agent-framework-docs": {
"command": "uv",
"args": [
"run",
"--directory",
"/Users/you/projects/python-mcp-server-client",
"main.py"
],
"env": {
"SERPER_API_KEY": "your-serper-key-here"
}
}
}
}Prompts to try
Questions to ask your AI assistant to leverage this server's documentation search capability.
- "How do I build a ReAct agent with LangChain? Search the official docs"
- "Show me how to create a multi-agent workflow in AutoGen"
- "What is the correct way to define tools in the OpenAI Agents SDK?"
- "How does LlamaIndex handle document chunking and retrieval?"
- "Find the CrewAI docs on defining crew roles and task delegation"Troubleshooting Python MCP Agent Framework Docs
get_docs returns no results or errors about the search API
Verify your SERPER_API_KEY is valid and exported. The tool uses Serper's Google Search API; check your serper.dev dashboard for remaining quota.
uv: command not found when starting the server
Install uv using the one-liner for your platform (see step 1) and restart your terminal. Alternatively, ensure ~/.cargo/bin or the uv install path is on your PATH.
SSE client can't connect to the running server
Ensure the server is running with --host 0.0.0.0 and that the port is not blocked by a firewall. Connect the client with the full SSE URL: http://<host>:8020/sse
Frequently Asked Questions about Python MCP Agent Framework Docs
What is Python MCP Agent Framework Docs?
Python MCP Agent Framework Docs is a Model Context Protocol (MCP) server that 支持查询主流agent框架技术文档的mcp server（支持stdio和sse两种传输协议）, 支持 langchain、llama-index、autogen、agno、openai-agents-sdk、mcp-doc、camel-ai 和 crew-ai It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Python MCP Agent Framework Docs?
Follow the installation instructions on the Python MCP Agent Framework Docs GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Python MCP Agent Framework Docs?
Python MCP Agent Framework Docs works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Python MCP Agent Framework Docs free to use?
Yes, Python MCP Agent Framework Docs is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
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