-
securityF
license-
qualityA Model Context Protocol server utilizing Claude AI for generating intelligent queries and offering documentation assistance based on API documentation analysis.
Last updated -
3
2
TypeScript
Integrations
Supports environment variable management for storing API keys required by the MCP server, specifically for storing the Serper API key used for web searches.
Retrieves information from LangChain's official documentation, allowing users to search and access relevant documentation snippets through the get_docs tool.
Used for visualization of the server's architecture and workflow through diagrams in the documentation.
MPC Docs Server
This is a simple MCP (Model Context Protocol) server for retrieving information from the official documentation of Langchain, Llama Index, and OpenAI. It provides a tool that can be used by MCP-compatible applications to search and retrieve relevant documentation snippets.
Features
- Documentation Retrieval: Fetches content from the official documentation of Langchain, Llama Index, and OpenAI.
- MCP Compatibility: Implements an MCP server, allowing it to be easily integrated with other MCP-compatible applications.
- Simple Tool: Exposes a
get_docstool that accepts a query and library name, returning relevant documentation snippets.
How It Works
Getting Started
Installing uv Package Manager
On MacOS/Linux:
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Make sure to restart your terminal afterwards to ensure that the uv command gets picked up.
Project Setup
Create and initialize the project:
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Environment Variables
Create a .env file in the root directory and add the following:
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You'll need a SERPER API key to use the web search functionality. You can obtain one from Serper.dev. We are using the Serper API to search the web for relevant documentation.
Running the Server
Start the MCP server:
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The server will start and be ready to accept connections.
This server cannot be installed
A simple Model Context Protocol server that enables searching and retrieving relevant documentation snippets from Langchain, Llama Index, and OpenAI official documentation.
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