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MCP server exposing Apple Foundation Models to Claude Code and Claude Desktop

Project description

Apple Foundation Models MCP Server

Expose Apple's on-device 3B parameter LLM to Claude Code and Claude Desktop via MCP. Zero API cost, fully private, runs on Neural Engine.

Requirements

  • macOS 26+ (Tahoe or later)
  • Apple Silicon (M1/M2/M3/M4)
  • Apple Intelligence enabled in System Settings
  • Python 3.10+

Install

pip install apple-fm-mcp

Configure

Add to your Claude Code config (~/.claude/mcp.json):

{
  "mcpServers": {
    "apple-fm": {
      "command": "apple-fm-mcp"
    }
  }
}

Or Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "apple-fm": {
      "command": "apple-fm-mcp"
    }
  }
}

Tools

Tool Description Latency
fm_generate Free-form text generation ~1s
fm_summarize Summarize text into bullet points ~4s
fm_classify Classify text into categories ~2s
fm_extract Extract structured data from text ~3s
fm_status Check model availability instant

Why Use This?

  • Free: No API keys, no tokens, no cloud costs
  • Private: All inference on-device, no data leaves your Mac
  • Fast: Neural Engine optimized, ~1s for generation
  • Complementary: Use alongside Claude for tasks where on-device speed matters

When to Use Apple FM vs Claude

Task Use Apple FM Use Claude
Quick classification Yes Overkill
Text summarization Yes (short text) Yes (long documents)
Code generation No Yes
Complex reasoning No Yes
Data extraction Yes (simple) Yes (complex)
Privacy-critical Yes Depends

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License

MIT

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