Overview: MCP Server for ZenML

Title

MCP Server for ZenML

How to Use

• Prerequisites: Requires access to a ZenML Cloud server, uv installed locally, and a cloned repository.
• Configuration: Set up an MCP config file with ZenML server details, API key, and paths to the server script.
• Integration: Works with MCP clients like Claude Desktop and Cursor by updating their respective config files.

Key Features

• Provides MCP tools to access ZenML server data, including users, stacks, pipelines, runs, artifacts, and more.
• Supports triggering new pipeline runs if a template exists.
• Beta release with ongoing improvements based on user feedback.

Use Cases

• AI-Assisted Development: Enables LLMs like Claude to fetch live ZenML pipeline data for better context.
• Workflow Automation: Streamlines ML pipeline management by integrating with MCP-compatible tools.
• Debugging & Monitoring: Accesses step logs and metadata for troubleshooting cloud-based pipeline runs.