What is Expo Docs Mcp

expo-docs-mcp is a Model Context Protocol (MCP) server designed to provide AI assistants with access to the latest Expo documentation, including API references, guides, and tutorials.

Use cases

Use cases include integrating the server into development tools, creating chatbots that assist with Expo documentation queries, and providing support for developers during the coding process.

How to use

To use expo-docs-mcp, clone the repository, install dependencies, set up your OpenAI API key in the .env file, build the documentation index, and start the server. You can then query the Expo documentation through the provided API endpoints.

Key features

Key features include real-time access to Expo documentation, semantic search capabilities, easy setup with Node.js, and the ability to update documentation from the Expo GitHub repository.

Where to use

expo-docs-mcp can be used in software development environments where developers need quick access to documentation, particularly for applications built with Expo.

Expo Documentation MCP Server

This is a Model Context Protocol (MCP) server for Expo documentation. It provides AI assistants with access to up-to-date Expo documentation, including the API reference, guides, and tutorials.

What is MCP?

The Model Context Protocol (MCP) is a standard for providing AI models with access to external data and services. This server implements an MCP endpoint that allows AI agents to query Expo documentation.

Getting Started

Prerequisites

• Node.js (v16 or higher)
• npm or yarn
• OpenAI API key (for embeddings)

Installation

1. Clone this repository:

git clone <repository-url>
cd expo-docs-mcp

2. Install dependencies:

npm install

3. Copy .env.example to .env and add your OpenAI API key:

cp .env.example .env

Edit the .env file to add your OpenAI API key.

Building the Documentation Index

Before starting the server, you need to build the documentation index:

npm run build-index

This will process the Expo documentation in the docs-source directory and create a vector store for semantic search.

Starting the Server

Start the server:

npm start

For development mode with automatic reloading:

npm run dev

The server will start on the port specified in your .env file (default: 3000).

Testing the Server

You can test if the server is functioning correctly by running:

npm test

This will check if the server is running and test a sample query.

Updating the Documentation

To update the documentation to the latest version from the Expo GitHub repository:

npm run update-docs

This will pull the latest changes from the Expo repository and rebuild the index.

API Endpoints

/query (POST)

Query the Expo documentation.

Request Body:

{
  "query": "How do I use the Image component in Expo?",
  "maxResults": 5
}

Response:

{
  "context": [
    {
      "id": "docs/api/image.md",
      "content": "# Image\n\nA React component for displaying different types of images...",
      "metadata": {
        "source": "expo-repository",
        "path": "/path/to/docs/api/image.md",
        "type": "markdown",
        "title": "Image",
        "url": "https://github.com/expo/expo/blob/main/docs/api/image.md"
      }
    }
  ]
}

/health (GET)

Check if the server is running.

Response:

{
  "status": "ok",
  "message": "Expo Documentation MCP Server is running"
}

Integrating with AI Assistants

To use this MCP server with AI assistants like Claude or GPT, you’ll need to configure the assistant to use the MCP endpoint. The specific configuration depends on the AI platform you’re using.

Example: Using with Claude

1. Configure the MCP endpoint in your Claude developer settings
2. Point to your server’s URL (e.g., http://your-server.com/query)
3. Use the provided mcp-config.json file to define the tool’s capabilities

License

MIT