Docs-Search-MCP-server

Anyr00d/Docs-Search-MCP-server

3.1

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The MCP Server - Docs Search & Fetch Tool is designed to facilitate documentation search and retrieval for AI and developer libraries using the Model Context Protocol.

MCP Server - Docs Search & Fetch Tool

This project implements an MCP (Model Context Protocol) server designed to provide documentation search and retrieval capabilities.
It uses the Serper API for Google search results and scrapes official documentation websites for detailed content.

Features

  • Search the web for documentation pages related to popular AI and developer libraries:
    • LangChain
    • LlamaIndex
    • OpenAI
  • Fetch and extract textual content from official documentation URLs
  • Expose tools via MCP-compatible endpoints for easy integration with AI clients

Getting Started

Prerequisites

  • Python 3.10+
  • requests, beautifulsoup4, fastmcp, and python-dotenv libraries
  • Serper API key (set in .env file as SERPER_API_KEY)

Installation

Create and activate a virtual environment, then install dependencies:

python -m venv .venv
# On Linux/macOS:
source .venv/bin/activate
# On Windows PowerShell:
.venv\Scripts\activate

pip install -r requirements.txt

Create a .env file with your Serper API key:

SERPER_API_KEY=your_serper_api_key_here

Running the Server

Run the MCP server using:

python main.py

Alternatively, you can use uv python and package manager(suggested). More about uv : https://docs.astral.sh/uv/