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Moondream MCP Server Notes

System Overview

Core Components

  1. MCP Server Layer (TypeScript)

    • Handles MCP protocol communication
    • Manages tool interfaces
    • Processes requests/responses

  2. Python Backend

    • Moondream model server
    • Image analysis processing
    • HTTP API endpoints (port 3475)

Key Dependencies

  • UV Package Manager
  • Node.js (v18+)
  • Python 3.8+
  • Moondream Python package
  • MCP SDK

Installation Requirements

System Requirements

  1. Node.js v18 or higher
  2. Python 3.8+
  3. UV package manager
  4. Sufficient disk space (~1GB for model and environments)

Environment Setup

  1. UV installation (automatic)
  2. Python virtual environment (managed by UV)
  3. Moondream package installation
  4. Model download (~500MB)

Integration Points

Claude Desktop

Configuration in ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "moondream": {
      "command": "node",
      "args": ["/path/to/moondream-server/build/index.js"]
    }
  }
}

Cline

Configuration in ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json:

{
  "mcpServers": {
    "moondream": {
      "command": "node",
      "args": ["/path/to/moondream-server/build/index.js"]
    }
  }
}

Available Tools

analyze_image

  • Purpose: Image analysis using Moondream model
  • Capabilities:
    1. Image captioning
    2. Object detection
    3. Visual question answering
  • Input Schema: 
    {
  image_path: string,  // Path to image file
  prompt: string       // Analysis command
}

Technical Implementation

Server Architecture

  1. Main Server (index.ts)

    • MCP protocol handling
    • Tool registration
    • Request routing

  2. Python Setup (python-setup.ts)

    • UV installation
    • Virtual environment management
    • Model download and setup
    • Moondream server process management

Model Details

  • Name: moondream-0_5b-int4.mf.gz
  • Size: ~500MB
  • Type: 8-bit quantized
  • Source: Hugging Face
  • Location: models/ directory

API Endpoints

  • Base URL: http://127.0.0.1:3475
  • Endpoints:
    1. /caption - Image captioning
    2. /detect - Object detection
    3. /query - Visual Q&A

Maintenance Notes

Common Issues

  1. Model Download

    • Check network connectivity
    • Verify Hugging Face accessibility
    • Ensure sufficient disk space

  2. Server Startup

    • Port 3475 conflicts
    • Python environment issues
    • Model file accessibility

  3. UV Setup

    • Installation verification
    • Path configuration
    • Permission issues

Performance Considerations

  1. Model Loading

    • First request may be slower
    • Subsequent requests benefit from caching
    • Memory usage peaks during analysis

  2. Concurrent Requests

    • Server handles multiple requests
    • Resource intensive operations
    • Monitor memory usage

Future Improvements

Potential Enhancements

  1. Model Options

    • Support for larger models
    • Alternative model architectures
    • Custom model integration

  2. Performance

    • Response time optimization
    • Memory usage improvements
    • Caching strategies

  3. Features

    • Batch processing
    • Image preprocessing options
    • Additional analysis modes

Development Tasks

  • Add support for larger models
  • Implement batch processing
  • Optimize memory usage
  • Add error recovery mechanisms
  • Improve documentation