Apple RAG MCP
@BingoWon
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,
Overview
What is Apple RAG MCP?
Apple RAG MCP delivers instant access to official Swift development docs, design guidelines, Apple platform knowledge, and Apple Developer YouTube content including WWDC sessions, tutorials, and live events. It is a Retrieval-Augmented Generation (RAG) system combining Apple’s official documentation with video content, featuring AI reranking with Qwen3-Reranker-8B for search accuracy. It’s designed for developers using AI agents that need Apple expertise.
How to use Apple RAG MCP?
Install with a one-click Cursor button or manually configure for any MCP-compatible client by adding the URL https://mcp.apple-rag.com (MCP Type: Streamable HTTP). Authentication is optional; an MCP Token at apple-rag.com provides higher usage limits. No token is required to start.
Key features of Apple RAG MCP
- Semantic Search for RAG with vector similarity
- Keyword Search for precise technical term matching
- Hybrid Search combining semantic and keyword search
- Complete coverage of iOS, macOS, watchOS, tvOS, visionOS docs
- Video content from Apple Developer YouTube channel
- Real-time updates synced with latest Apple resources
Use cases of Apple RAG MCP
- AI agents answering Swift code questions with examples
- Developers searching Apple design guidelines during app creation
- Finding WWDC session content or tutorials for platform learning
- Getting contextual answers from Apple documentation without manual browsing
FAQ from Apple RAG MCP
What MCP clients does Apple RAG MCP support?
Cursor, Claude Desktop, Cline, and all MCP-compatible tools.
Do I need an API key or token to use Apple RAG MCP?
No MCP Token is required to start. An MCP Token (optional) provides higher usage limits and can be obtained at apple-rag.com.
How does the search work?
It uses hybrid search combining Semantic Search (vector similarity), Keyword Search (technical term matching), and AI reranking with Qwen3-Reranker-8B for precision.
Is the documentation up to date?
Yes, the index is continuously updated to reflect the latest Apple developer resources, including official docs and Apple Developer YouTube content.
Can I self-host Apple RAG MCP?
Yes. See the Deployment Guide (DEPLOYMENT.md) for setup instructions using Cloudflare Workers.
