Python MCP Server & Client
by GobinFan
This project provides a Python implementation of an MCP (Model Context Protocol) server and client. It aims to provide a standardized interface for AI models to connect with external data sources and tools.
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What is Python MCP Server & Client?
This project is a Python implementation of an MCP server and client. MCP provides a standardized interface for AI models to interact with external tools and data sources, unifying function call formats and tool encapsulation.
How to use Python MCP Server & Client?
The project provides instructions for setting up the MCP server using both Stdio and SSE protocols. The Stdio protocol is for local use, while the SSE protocol is for cloud deployment. The client can be configured using Cline or Cursor. Detailed steps are provided for installation, environment setup, and running the server and client.
Key features of Python MCP Server & Client
Standardized interface for AI models
Support for Stdio and SSE transport protocols
Integration with external tools (e.g., web search for documentation)
Client implementations for Cline and Cursor
Example implementation for searching and retrieving documentation for various AI libraries
Use cases of Python MCP Server & Client
Connecting AI models to external data sources
Providing AI models with access to documentation and knowledge bases
Standardizing function calls for different large language models
Enabling AI models to interact with custom tools and APIs
FAQ from Python MCP Server & Client
What is MCP?
What is MCP?
MCP stands for Model Context Protocol. It provides a standardized interface for AI models to connect with external data sources and tools.
What are the advantages of using MCP?
What are the advantages of using MCP?
MCP unifies function call formats for different large language models and standardizes the encapsulation of tools, simplifying integration and management.
What transport protocols are supported?
What transport protocols are supported?
The project supports Stdio (for local use) and SSE (Server-Sent Events) for cloud deployment.
How do I configure the MCP client?
How do I configure the MCP client?
The client can be configured using Cline or Cursor, with detailed instructions provided in the README.
What AI libraries are supported for documentation retrieval?
What AI libraries are supported for documentation retrieval?
The example implementation supports langchain, llama-index, autogen, agno, openai-agents-sdk, mcp-doc, camel-ai, and crew-ai.