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Servers/Code Execution/zenml-io/mcp-zenml
Code ExecutionOfficialPython
Z

zenml-io/mcp-zenml

An MCP server to connect with your [ZenML](https://www.zenml.io) MLOps and LLMOps pipelines

0 starsUpdated Aug 28, 2026
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Overview

An MCP server to connect with your [ZenML](https://www.zenml.io) MLOps and LLMOps pipelines

Installation

docker build -t mcp-zenml:apps .

Configuration

{
    "mcpServers": {
        "zenml": {
            "command": "/usr/local/bin/uv",
            "args": ["run", "path/to/server/zenml_server.py"],
            "env": {
                "LOGLEVEL": "WARNING",
                "NO_COLOR": "1",
                "ZENML_LOGGING_COLORS_DISABLED": "true",
                "ZENML_LOGGING_VERBOSITY": "WARN",
                "ZENML_ENABLE_RICH_TRACEBACK": "false",
                "PYTHONUNBUFFERED": "1",
                "PYTHONIOENCODING": "UTF-8",
                "ZENML_STORE_URL": "https://your-zenml-server-goes-here.com",
                "ZENML_STORE_API_KEY": "your-api-key-here"
            }
        }

Capabilities

  • List and inspect pipeline runs

    retrieve execution history, status, and step-level details using `list_pipeline_runs` and `get_run_step`.

  • Trigger a new pipeline run

    start a run from a frozen snapshot configuration with `trigger_pipeline`.

  • Check deployment status and logs

    find running deployments via `list_deployments` and fetch bounded logs with `get_deployment_logs`.

  • Explore stacks and components

    list infrastructure configurations and their building blocks using `list_stacks` and `list_stack_components`.

  • Browse the model registry

    discover registered models and their versioned artifacts with `list_models` and `list_model_versions`.

  • Diagnose connection issues

    run `diagnose_zenml_setup` to validate server URL, credentials, and SDK connectivity even when misconfigured.

Tags

  • devops
  • workflow-automation
  • ai-model
  • data-analysis
  • awesome-list

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