
Documentation Retrieval Server
Fetch relevant documentation snippets from Langchain, Llama Index, and OpenAI. Integrate seamlessly with MCP-compatible applications to enhance your search capabilities. Simplify your documentation access with a straightforward tool that retrieves information based on your queries.
Installation
Installing for Claude Desktop
Manual Configuration Required
This MCP server requires manual configuration. Run the command below to open your configuration file:
npx mcpbar@latest edit -c claude
This will open your configuration file where you can add the Documentation Retrieval Server MCP server manually.
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_docs
tool that accepts a query and library name, returning relevant documentation snippets.
How It Works
graph LR
Client[MCP Client] -->|Calls tools| Server[MCP Server]
Server -->|Searches web for docs| Serper[Serper API]
Serper -->|Returns search results| Server
Server -->|Returns documentation| Client
Getting Started
Installing uv Package Manager
On MacOS/Linux:
curl -LsSf https://astral.sh/uv/install.sh | sh
Make sure to restart your terminal afterwards to ensure that the uv
command gets picked up.
Project Setup
Create and initialize the project:
# Create a new directory for our project
uv init mcp-server
cd mcp-server
# Create virtual environment and activate it
uv venv
source .venv/bin/activate # On Windows use: .venv\Scripts\activate
# Install dependencies
uv add "mcp[cli]" httpx python-dotenv bs4
Environment Variables
Create a .env
file in the root directory and add the following:
SERPER_API_KEY=YOUR_SERPER_API_KEY
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:
uv run main.py
The server will start and be ready to accept connections.
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