MCP Server

A minimal Model Context Protocol (MCP) server that exposes documentation-search tools for any AI agent. Use this server to fetch and search docs for popular libraries (LangChain, LlamaIndex, OpenAI) and wire them seamlessly into your agents.

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Features

• Doc Search Tool: Provides a get_docs tool to search and fetch documentation based on a query and library.
• Web Scraping: Uses Serper API for search results and BeautifulSoup for fetching page text.
• Easy Integration: Decorate functions with @mcp.tool() and run the server over stdio transport.

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Prerequisites

• Python 3.8 or higher
• A Serper API key (set in .env as SERPER_API_KEY)

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Installation

1. Clone this repo:

   git clone https://github.com/<your-username>/MCP-Server-Latest_Doc-.git
   cd MCP-Server-Latest_Doc-
   

2. Create a virtual environment & install dependencies:

   python3 -m venv .venv
   source .venv/bin/activate
   pip install -r requirements.txt
   

3. Add your Serper API key in a .env file:

   echo "SERPER_API_KEY=your_api_key_here" > .env
   

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Usage

Running the MCP Server

Execute the main script to start the MCP server on stdio:

python main.py

Using the get_docs Tool

Within any AI agent that supports MCP, the get_docs tool will automatically register. It expects two arguments:

1. query: The search term (e.g., "Chroma DB").
2. library: One of langchain, llama-index, or openai.

The tool returns the concatenated text of the top search results from the specified library docs.

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Integrating into an AI Agent

Any agent framework that implements the MCP transport can import and run this server. For example, in Python:

from mcp.server.fastmcp import FastMCP
from dotenv import load_dotenv
import os

load_dotenv()

mcp = FastMCP("docs")

# ... define @mcp.tool() functions here ...

if __name__ == "__main__":
    mcp.run(transport="stdio")

After starting this script, your agent can call the get_docs tool over the stdio channel.

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Example: Using with Claude Code CLI

First, install the Claude Code CLI:

npm install -g @anthropic-ai/claude-code

Add the MCP server to Claude:

claude mcp add

Specify the uv binary path (find with where uv):

claude mcp configure --binary-path /full/path/to/uv

Set the working directory of the server:

claude mcp configure --workdir /path/to/MCP-Server-Latest_Doc-

Run the MCP server:

python main.py

Confirm registration:

claude mcp list

For debugging, you can use the Inspector:

npx @modelcontextprotocol/inspector uv run main.py

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License

MIT ©