Memvid MCP Server 🎥
A Model Context Protocol (MCP) server that exposes Memvid video memory functionalities to AI clients. This server allows you to encode text, PDFs, and other content into video memory format for efficient semantic search and chat interactions.
🌟 Features
- Text Encoding: Add text chunks or full text documents to video memory
- PDF Processing: Extract and encode content from PDF files
- Video Memory Building: Generate compressed video representations of your data
- Semantic Search: Query your encoded data using natural language
- Chat Interface: Have conversations with your encoded knowledge base
- Multi-Connection Support: Handle multiple concurrent client connections
- Comprehensive Logging: Detailed logging to stderr for debugging
- Graceful Shutdown: Proper resource cleanup and signal handling
📋 Requirements
- Python 3.10 or higher
- uv package manager
- memvid package
- MCP-compatible client (e.g., Claude Desktop)
🚀 Installation
1. Set up the environment
cd /memvid_mcp_server
uv venv --python 3.12 --seed
source .venv/bin/activate
2. Install dependencies
H.265 Encoding with Docker
To enable H.265 video compression, you need to build the memvid-h265 Docker container. This container provides the necessary FFmpeg environment for H.265
encoding.
- Navigate to the
memvid repository root: - Build the Docker image:
docker build -f docker/Dockerfile -t memvid-h265 docker/
memvid-h265 using the Dockerfile located in the docker/ directory.
Once the Docker image is built, memvid will automatically detect and use it when video_codec='h265' is specified in build_video.
3. Test the server (optional)
uv run python memvid_mcp_server/main.py
⚙️ Configuration
Claude Desktop Setup
- Copy the example configuration:
cp example_mcp_config.json ~/.config/claude-desktop/config.json
- Or manually add to your Claude Desktop config:
{
"mcpServers": {
"memvid-mcp-server": {
"command": "uv",
"args": [
"--directory",
"/home/ty/Repositories/memvid_mcp_server",
"run",
"python",
"memvid_mcp_server/main.py"
],
"env": {
"PYTHONPATH": "/home/ty/Repositories/memvid_mcp_server",
"PYTHONWARNINGS": "ignore"
}
}
}
}
- Restart Claude Desktop to load the server.
get_server_status
Check the current status of the memvid server including version information.
add_chunks
Add a list of text chunks to the encoder.
- chunks: List of text strings to add
add_text
Add a single text document to the encoder.
- text: Text content to add
- metadata: Optional metadata dictionary
add_pdf
Process and add a PDF file to the encoder.
- pdf_path: Path to the PDF file
build_video
Build the video memory from all added content.
- video_path: Output path for the video file
- index_path: Output path for the index file
- codec: Video codec to use ('h265' or 'h264', default: 'h265')
- show_progress: Whether to show progress during build (default: True)
- auto_build_docker: Whether to auto-build docker if needed (default: True)
- allow_fallback: Whether to allow fallback options (default: True)
search_memory
Perform semantic search on the built video memory.
- query: Natural language search query
- top_k: Number of results to return (default: 5)
chat_with_memvid
Have a conversation with your encoded knowledge base.
- message: Message to send to the chat system
📖 Usage Workflow
- Add Content: Use
add_text, add_chunks, or add_pdf to add your data - Build Video: Use
build_video to create the video memory representation - Search or Chat: Use
search_memory for queries or chat_with_memvid for conversations
🔧 Development
Testing
# Install development dependencies
uv add --dev pytest pytest-asyncio black ruff mypy
# Run tests
uv run pytest
# Format code
uv run black memvid_mcp_server/
uv run ruff check memvid_mcp_server/
Debugging
- Check logs in Claude Desktop:
~/Library/Logs/Claude/mcp*.log (macOS) or equivalent - Enable debug logging by setting
LOG_LEVEL=DEBUG in environment - Use
get_server_status tool to check server state
🔧 Troubleshooting
Common Issues
- JSON Parsing Errors: All output is properly redirected to stderr to prevent protocol interference
- Import Errors: The server gracefully handles missing memvid package with clear error messages
- Connection Issues: Check Claude Desktop logs and use
get_server_status to diagnose issues - Video Build Failures: Ensure sufficient disk space and valid paths
Logging Configuration
The server implements comprehensive stdout redirection to prevent any library output from interfering with the MCP JSON-RPC protocol:
- All memvid operations are wrapped with stdout redirection
- Progress bars, warnings, and model loading messages are captured
- Only structured JSON responses are sent to Claude Desktop
- All diagnostic information is logged to stderr
Error Messages
- "Memvid not available": Install the memvid package:
uv add memvid - "Video memory not built": Run
build_video before searching or chatting - "LLM not available": Expected warning - memvid will work without external LLM providers
📄 License
MIT License - see the LICENSE file for details.
🤝 Contributing
- Fork the repository
- Create a feature branch
- Make your changes
- Add tests if applicable
- Submit a pull request
Generated with improvements for production reliability and MCP best practices.