MCP server for ZenML - browse stacks, pipelines, runs, artifacts & trigger pipeline runs via API
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io.github.zenml-io/mcp-zenml is an MCP server that MCP server for ZenML - browse stacks, pipelines, runs, artifacts & trigger pipeline runs via API. Its tool list has not been published yet over stdio, sse and http, requires no API key, and scores 91/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"zenml": {
"args": [
"run",
"-i",
"--rm",
"-e",
"ZENML_STORE_URL=https://...",
"-e",
"ZENML_STORE_API_KEY=ZENKEY_...",
"-e",
"ZENML_ACTIVE_PROJECT_ID=...",
"-e",
"LOGLEVEL=WARNING",
"-e",
"NO_COLOR=1",
"-e",
"ZENML_LOGGING_COLORS_DISABLED=true",
"-e",
"ZENML_LOGGING_VERBOSITY=WARN",
"-e",
"ZENML_ENABLE_RICH_TRACEBACK=false",
"-e",
"PYTHONUNBUFFERED=1",
"-e",
"PYTHONIOENCODING=UTF-8",
"zenmldocker/mcp-zenml:latest"
],
"command": "docker"
}
}
}Are you the author?
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This project implements a Model Context Protocol (MCP) server for interacting with the ZenML API.
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This project implements a Model Context Protocol (MCP) server for interacting with the ZenML API.

The Model Context Protocol (MCP) is an open protocol that standardizes how applications provide context to Large Language Models (LLMs). It acts like a "USB-C port for AI applications" - providing a standardized way to connect AI models to different data sources and tools.
MCP follows a client-server architecture where:
ZenML is an open-source platform for building and managing ML and AI pipelines. It provides a unified interface for managing data, models, and experiments.
For more information, see the ZenML website and our documentation.
The server provides MCP tools to access core read functionality from the ZenML server, providing a way to get live information about:
The server also allows you to trigger new pipeline runs using snapshots (preferred) or run templates (deprecated).
Note: We're continuously improving this integration based on user feedback. Please join our Slack community to share your experience and help us make it even better!
The MCP server exposes the following tools, grouped by category:
| Tool | Description |
|---|---|
get_snapshot | Get a frozen pipeline configuration by name/ID |
list_snapshots | List snapshots with filters (runnable, deployable, deployed, tag) |
get_deployment | Get a deployment's runtime status and URL |
list_deployments | List deployments with filters (status, pipeline, tag) |
get_deployment_logs | Get bounded logs from a deployment (tail=100 default, max 1000) |
trigger_pipeline | Trigger a pipeline run (prefer snapshot_name_or_id parameter) |
| Tool | Description |
|---|---|
get_active_project | Get the currently active project |
| `get_pro |