Docs MCP Server
About
A simple MCP server to search for documentation
Details
- Author
- gpreddy172
- Downloads
- 177
- Categories
- Knowledge Base
Jump to
- Searches latest docs for a given query and library
- Supports langchain, openai, and llama-index
- Lightweight MCP server exposing tools via standardized protocol
- Uses uv for project management and dependency handling
- Requires Python 3.10 or higher
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Docs MCP ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install Python 3.10+, MCP SDK 1.2.0+, and the uv package manager. Run uv run main.py to start the server, then configure Claude Desktop via its claude_desktop_config.json to connect.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"docs mcp server": {
"MCP-Server-for-Documentation": {
"command": "uv",
"args": [
"init",
"mcp-server"
]
}
}
}
}McpServers
{
"MCP-Server-for-Documentation": {
"command": "uv",
"args": [
"init",
"mcp-server"
]
}
}Docs MCP Server
This repository contains an implementation of a Model Context Protocol (MCP) server.
This MCP server
"""
Searchs the latest docs for a given query and library.
It Supports langchain, openai, and llama-index.
Args:
query: The query to search for (e.g. "Chroma DB")
library: The library to search in (e.g. "langchain")
Returns:
Text from the docs
"""
What is MCP?
MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications - it provides a standardized way to connect AI models to different data sources and tools.
Key Benefits
- A growing list of pre-built integrations that your LLM can directly plug into
- Flexibility to switch between LLM providers and vendors
- Best practices for securing your data within your infrastructure
Architecture Overview
MCP follows a client-server architecture where a host application can connect to multiple servers:
- MCP Hosts: Programs like Claude Desktop, IDEs, or AI tools that want to access data through MCP
- MCP Clients: Protocol clients that maintain 1:1 connections with servers
- MCP Servers: Lightweight programs that expose specific capabilities through the standardized Model Context Protocol
- Data Sources: Both local (files, databases) and remote services (APIs) that MCP servers can access
Core MCP Concepts
MCP servers can provide three main types of capabilities:
- Resources: File-like data that can be read by clients (like API responses or file contents)
- Tools: Functions that can be called by the LLM (with user approval)
- Prompts: Pre-written templates that help users accomplish specific tasks
System Requirements
- Python 3.10 or higher
- MCP SDK 1.2.0 or higher
- uv package manager
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
1. Create and initialize the project:
```bash
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