Enables local AI analysis of images and multimodal data processing through Ollama integration.
Provides an interactive REPL for executing Python code, performing data exploration, and introspecting functions within a persistent Pixeltable session.
Supports running YOLOX object detection on images and photos managed within the Pixeltable infrastructure.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Pixeltable MCP Server (Developer Edition)Create a table for my images and run object detection on them"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Pixeltable MCP Server (Developer Edition)
⚠️ WARNING: THIS IS AN EXPERIMENTAL DEVELOPMENT TOOL. DO NOT USE WITH IMPORTANT DATA. THIS IS FOR DEMO PURPOSES ONLY UNTIL FURTHER NOTICE.
Claude meets Pixeltable. Multimodal AI data infrastructure - not (just) a database - now available as an MCP server.
⚡ Quick Start
Prerequisites
You must have uv installed. If you don't have it or aren't sure, run:
Or consult the uv installation guide.
Claude Code Installation (Easiest!)
Just tell Claude:
"Install https://github.com/pixeltable/mcp-server-pixeltable-developer as a uv tool and add it to your MCPs"
That's it! Claude will handle the installation and configuration for you.
Manual Installation with uv tool
Installation from source (For development)
Configuration for Claude Desktop
⚠️ Note: If you experience issues with Claude Desktop configuration, you may need to restart Claude Desktop after adding the MCP server configuration.
Add to your Claude Desktop config:
Or if running from source:
Configuration for Cursor
Cursor users can add the Pixeltable MCP server to their .cursorrules file or configure it through Cursor's MCP settings:
Via Cursor Settings:
Open Cursor Settings
Navigate to "Features" → "Model Context Protocol"
Add a new MCP server with command:
mcp-server-pixeltable-developer
Via JSON Configuration: Add to your Cursor MCP configuration:
{ "mcpServers": { "pixeltable": { "command": "mcp-server-pixeltable-developer", "env": { "PIXELTABLE_HOME": "/Users/{your-username}/.pixeltable", "PIXELTABLE_FILE_CACHE_SIZE_G": "10" } } } }For development/source installations:
{ "mcpServers": { "pixeltable": { "command": "uv", "args": [ "run", "--directory", "{path-to-your-repo}", "python", "-m", "mcp_server_pixeltable_stio" ], "env": { "PIXELTABLE_HOME": "/Users/{your-username}/.pixeltable", "PIXELTABLE_FILE_CACHE_SIZE_G": "10" } } } }
💡 Examples
Create and populate a table:
Local AI analysis:
Data workflows:
🚀 New Features
Configurable Datastore Path
Change where Pixeltable stores its data:
The datastore path can be configured through:
Environment variable
PIXELTABLE_HOME(highest priority)Persistent configuration file (survives restarts)
System default
~/.pixeltable
Interactive Python REPL
Execute Python code with PixelTable pre-loaded in a persistent session:
Bug Logging & Testing
Structured logging for testing and bug discovery:
Bug logs are saved to pixeltable_testing_logs/ in both Markdown and JSON formats.
Why These Features?
REPL: Explore PixelTable dynamically without rebuilding the MCP
Introspection: Discover functions and get docs on-demand
Bug Logging: Document issues systematically during development
Future-proof: Adapts to PixelTable API changes automatically
🔧 Troubleshooting
Claude Desktop Issues
If you're having trouble with Claude Desktop:
Restart Claude Desktop after adding the MCP server configuration
Check that the path to your Pixeltable home directory is correct
Ensure you have the latest version of Claude Desktop
Verify that
uvis installed and accessible from your PATH
Cursor Issues
If Cursor isn't recognizing the MCP server:
Make sure you have MCP support enabled in Cursor settings
Restart Cursor after configuration changes
Check the Cursor logs for any error messages
Installation Issues
If installation fails:
Ensure you have Python 3.10+ installed
Make sure
uvis installed:curl -LsSf https://astral.sh/uv/install.sh | shTry installing from source if the GitHub installation fails
Getting Help
If you encounter issues:
Use the built-in bug logging:
Claude: log_bug("description", severity="high")Check the generated bug report:
Claude: generate_bug_report()File an issue on the GitHub repository
Built while having coffee. ☕