Apple RAG MCP

SSE

by BingoWon

322 downloads Not rated yet
GitHub SSE

About

Transform your AI agents into Apple development experts! Apple RAG MCP gives you instant access to official Swift docs, design guidelines, and comprehensive Apple platform knowledge through cutting-edge RAG technology. With professional AI reranking and hybrid search across iOS,

Details

Transport
SSE

Explore

- 🔍 Semantic Search for RAG - Vector similarity with semantic understanding for intelligent retrieval
- 🔎 Keyword Search - Precise technical term matching for API names and specific terminology
- 🎯 Hybrid Search - Combined semantic and keyword search with AI reranking for optimal results
- 📚 Complete Coverage - iOS, macOS, watchOS, tvOS, visionOS documentation
- 📺 Video Content - Apple Developer YouTube channel with WWDC sessions and tutorials
- ⚡ Fast Response - Optimized for speed across all content types
- 🚀 High Performance - Multi-instance cluster deployment for maximum throughput
- 🔄 Always Current - Synced with Apple's latest docs and video content
- 🛡️ Secure & Private - Your queries stay private
- 🌐 Universal MCP - Works with any MCP-compatible client

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:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name Apple RAG MCP
    Command (node, npx, python, etc.)

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

From the repository

Install MCP Server

Click the button above and Cursor will automatically configure everything for you in seconds.

JSON Configuration (Copy & Paste):
``json
{
"mcpServers": {
"apple-rag-mcp": {
"url": "https://mcp.apple-rag.com"
}
}
}
`

Manual Configuration Parameters:
- MCP Type:
Streamable HTTP
- URL:
https://mcp.apple-rag.com
- Authentication:
Optional` (MCP Token for higher limits)
- MCP Token: Get yours at apple-rag.com for increased quota

Want to run your own instance? See our Deployment Guide for complete setup instructions.

Quick Setup:


git clone https://github.com/your-org/apple-rag-mcp.git
cd apple-rag-mcp
pnpm install

cp .dev.vars.example .dev.vars

pnpm setup-secrets
pnpm deploy



Supported Clients: Cursor, Claude Desktop, Cline, and all MCP-compatible tools.

> Note: No MCP Token required to start! You get free queries without any authentication. Add an MCP Token later for higher usage limits.

search

Search Apple's official developer documentation and video content using advanced RAG technology. Returns relevant content from Apple's technical documentation, frameworks, APIs, design guidelines, and educational resources.

fetch

Retrieve complete cleaned content for a specific Apple developer documentation or video by URL. Returns the full processed content from Apple's official knowledge base.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "apple rag mcp": {
            "apple-rag-mcp": {
                "url": "https://mcp.apple-rag.com"
            }
        }
    }
}

McpServers

{
    "apple-rag-mcp": {
        "url": "https://mcp.apple-rag.com"
    }
}

✨ What is Apple RAG MCP?

Apple RAG MCP delivers exactly what your AI agents need: official Swift development docs, design guidelines, comprehensive Apple platform knowledge, and Apple Developer YouTube content including WWDC sessions, tutorials, and live events - current and complete. A cutting-edge Retrieval-Augmented Generation (RAG) system combining Apple's official documentation with video content from the Apple Developer YouTube channel. Features professional AI reranking with Qwen3-Reranker-8B for superior search accuracy across multiple content types. 🤖 AI-Powered Embedding & Reranking • ⚡ Semantic Search for RAG • 🔍 Keyword Search • 🎯 Hybrid Search • 📊 Precision Results
No reviews yet — be the first

Sign in to leave a review

Use Google, GitHub, or an email account so ratings stay tied to real people.

Email sign in

No reviews posted yet.