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MCP Server for ZenML

@zenml-io

代码仓库主页

基本信息

分类

其他

许可证

MIT

传输方式

stdio

作者

zenml-io

提交者

Alex Strick van Linschoten

关于 MCP Server for ZenML

MCP server to connect an MCP client (Cursor, Claude Desktop etc) with your ZenML MLOps and LLMOps pipelines

#mcp#mlops#llmops#mcp-server

MCP Server for ZenML 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-zenml": {
      "command": "docker",
      "args": [
        "build",
        "-t",
        "mcp-zenml:apps",
        "."
      ]
    }
  }
}

MCP Server for ZenML 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is MCP Server for ZenML?

MCP Server for ZenML is an MCP server that provides standardized tools for Large Language Models to interact with the ZenML API. It allows AI applications to read core entities (users, stacks, pipelines, models) and trigger pipeline runs, making live ML platform data accessible through the Model Context Protocol.

How to use MCP Server for ZenML?

The easiest way is through the ZenML dashboard's MCP Settings page, which provides pre-configured snippets and one-click installation. For manual setup, you can run the server via Docker (especially for MCP Apps with Streamable HTTP transport) or using uv. Configuration requires a ZenML server URL, API key, and optionally an active project ID.

Key features of MCP Server for ZenML

  • List and get details on users, stacks, components, and flavors
  • Browse pipeline definitions, runs, steps, schedules, and artifacts
  • Read metadata about models, model versions, services, and deployments
  • Trigger new pipeline runs using snapshots or run templates
  • Diagnose server setup with environment and connectivity checks
  • Open interactive dashboards via experimental MCP Apps

Use cases of MCP Server for ZenML

  • Discover project context and find runnable snapshots for a pipeline
  • Trigger a new pipeline run and monitor its deployment status
  • Analyze recent pipeline runs and stack component usage
  • Retrieve step logs, source code, and artifact metadata for debugging
  • Diagnose ZenML server connectivity and authentication issues

常见问题

1

What is MCP?

MCP (Model Context Protocol) is an open standard that lets AI applications connect to data sources and tools in a uniform way, like a “USB-C port for AI.”

2

What is ZenML?

ZenML is an open-source platform for building and managing ML and AI pipelines, providing a unified interface for data, models, and experiments.

3

What transport does the server use for MCP Apps?

MCP Apps require Streamable HTTP transport; they cannot work via stdio.

4

Which AI clients currently support MCP Apps?

VS Code (Insiders), Goose, and ChatGPT (launching soon). Claude Desktop and Claude.ai do not yet support Apps as of late January 2026.

5

How do I migrate from Run Templates to Snapshots?

Replace `list_run_templates()` with `list_snapshots(runnable=True, named_only=True)`, `get_run_template(name)` with `get_snapshot(name, include_config_schema=True)`, and `trigger_pipeline(template_id=...)` with `trigger_pipeline(snapshot_name_or_id=...)`.

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