Is io.github.zenml-io/mcp-zenml safe to use?

io.github.zenml-io/mcp-zenml has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments.

How do I install io.github.zenml-io/mcp-zenml?

io.github.zenml-io/mcp-zenml supports copy-paste install configs on its MCPpedia page for Claude Desktop, Cursor, and Claude Code. Scroll to the Quick Install section and select your client.

What can io.github.zenml-io/mcp-zenml do?

io.github.zenml-io/mcp-zenml provides 17 tools: Users, Stacks, Flavors, Pipelines, Schedules and 12 more. See the full tools list on the server page for descriptions and parameters.

What AI clients work with io.github.zenml-io/mcp-zenml?

io.github.zenml-io/mcp-zenml is compatible with claude-desktop, cursor, claude-code. It uses stdio and sse and http transport.

Is io.github.zenml-io/mcp-zenml actively maintained?

io.github.zenml-io/mcp-zenml is actively maintained — last commit was 21 days ago. It has 44 GitHub stars.

io.github.zenml-io/mcp-zenml

cloudflared

MCP server for ZenML - browse stacks, pipelines, runs, artifacts & trigger pipeline runs via API

44 111.7k/wk 17 tools GitHub npm

No known CVEs

No license

Actively maintained

Last commit 21d ago

Works with most clients

Transport: stdio, sse, http

17 tools · ~467 tok

Grade A · 0.2% of 200K ctx

Edit this pageView history

AI / ML DevOps

Step 1

Install in your client

Config is the same across clients — only the file and path differ.

Supported in Claude Desktopstdio, sse, http · Node 18+

Paste into ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "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?

Add this badge to your README to show your security score and help users find safe servers.

Embed in your READMEAbout badges →

[![MCPpedia Score](https://mcppedia.org/api/badge/io-github-zenml-io-mcp-zenml)](https://mcppedia.org/s/io-github-zenml-io-mcp-zenml)

Read me

What io.github.zenml-io/mcp-zenml does

This project implements a Model Context Protocol (MCP) server for interacting with the ZenML API.

Test This Server

Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.

npx -y 'cloudflared' 2>&1 | head -1 && echo "✓ Server started successfully"

After testing, let us know if it worked:

Loading README…

Scored, not listed

Why this score

Five weighted categories — click any category to see the underlying evidence.

Score breakdown

90/100across 5 weighted dimensions

How we score →

0255075100

−10

Security

Maintenance

Efficiency

Documentation

Compatibility

Categoriesclick a row to see evidence

Security

OSV.dev

No known CVEs.

Checked cloudflared against OSV.dev.

Inventory

Tools (17)

Click any tool to inspect its schema.

~467 tokens total

Community

Reviews

Be the first to review

Have you used this server?

Share your experience — it helps other developers decide.

How easy was setup?Did it work reliably?How was the documentation?

Frequently Asked Questions

Is io.github.zenml-io/mcp-zenml safe to use?: io.github.zenml-io/mcp-zenml has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments.
How do I install io.github.zenml-io/mcp-zenml?: io.github.zenml-io/mcp-zenml supports copy-paste install configs on its MCPpedia page for Claude Desktop, Cursor, and Claude Code. Scroll to the Quick Install section and select your client.
What can io.github.zenml-io/mcp-zenml do?: io.github.zenml-io/mcp-zenml provides 17 tools: Users, Stacks, Flavors, Pipelines, Schedules and 12 more. See the full tools list on the server page for descriptions and parameters.
What AI clients work with io.github.zenml-io/mcp-zenml?: io.github.zenml-io/mcp-zenml is compatible with claude-desktop, cursor, claude-code. It uses stdio and sse and http transport.
Is io.github.zenml-io/mcp-zenml actively maintained?: io.github.zenml-io/mcp-zenml is actively maintained — last commit was 21 days ago. It has 44 GitHub stars.

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Community

Discussion

Start a conversation

Ask a question, share a tip, or report an issue.

Has anyone used this with Cursor?How do you handle auth?Any alternatives?

Edit this pageView history

AI / ML DevOps

Step 1

Install in your client

Config is the same across clients — only the file and path differ.

Supported in Claude Desktopstdio, sse, http · Node 18+

Paste into ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "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?

Add this badge to your README to show your security score and help users find safe servers.

Embed in your READMEAbout badges →

[![MCPpedia Score](https://mcppedia.org/api/badge/io-github-zenml-io-mcp-zenml)](https://mcppedia.org/s/io-github-zenml-io-mcp-zenml)

Read me

What io.github.zenml-io/mcp-zenml does

This project implements a Model Context Protocol (MCP) server for interacting with the ZenML API.

Test This Server

Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.

npx -y 'cloudflared' 2>&1 | head -1 && echo "✓ Server started successfully"

After testing, let us know if it worked:

README

MCP Server for ZenML

This project implements a Model Context Protocol (MCP) server for interacting with the ZenML API.

What is MCP?

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:

MCP Hosts: Programs like Claude Desktop or IDEs that want to access data through MCP
MCP Clients: Protocol clients that maintain 1:1 connections with servers
MCP Servers: Lightweight programs that expose specific capabilities through the standardized protocol
Local Data Sources: Your computer's files, databases, and services that MCP servers can securely access
Remote Services: External systems available over the internet that MCP servers can connect to

What is ZenML?

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.

Features

The server provides MCP tools to access core read functionality from the ZenML server, providing a way to get live information about:

Core Entities

Users - user accounts and permissions
Stacks - infrastructure configurations
Stack Components - individual stack building blocks
Flavors - available component types
Service Connectors - cloud authentication

Pipeline Execution

Pipelines - pipeline definitions
Pipeline Runs - execution history and status
Pipeline Steps - individual step details, code, and logs
Schedules - automated run schedules
Artifacts - metadata about data artifacts (not the data itself)

Deployment & Serving

Snapshots - frozen pipeline configurations (the "what to run/serve" artifact)
Deployments - runtime serving instances with status, URL, and logs
Services - model serving endpoints

Organization & Discovery

Projects - organizational containers for ZenML resources
Tags - cross-cutting metadata labels for discovery
Builds - pipeline build artifacts with image and code info

Models

Models - ML model registry entries
Model Versions - versioned model artifacts

Deprecated (migration recommended)

~~Pipeline run templates~~ → use Snapshots instead (see Migration Guide)

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!

Available Tools

The MCP server exposes the following tools, grouped by category:

Pipeline Execution (New in v1.2)

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)

Organization (New in v1.2)

Tool	Description
`get_active_project`	Get the currently active project
`get_pro

... View full README on GitHub

Loading README…

Scored, not listed

Why this score

Five weighted categories — click any category to see the underlying evidence.

Score breakdown

90/100across 5 weighted dimensions

How we score →

0255075100

−10

Security

Maintenance

Efficiency

Documentation

Compatibility

Categoriesclick a row to see evidence

Security

OSV.dev

No known CVEs.

Checked cloudflared against OSV.dev.

Inventory

Tools (17)

Click any tool to inspect its schema.

~467 tokens total

Community

Reviews

Be the first to review

Have you used this server?

Share your experience — it helps other developers decide.

How easy was setup?Did it work reliably?How was the documentation?

Frequently Asked Questions

Is io.github.zenml-io/mcp-zenml safe to use?: io.github.zenml-io/mcp-zenml has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments.
How do I install io.github.zenml-io/mcp-zenml?: io.github.zenml-io/mcp-zenml supports copy-paste install configs on its MCPpedia page for Claude Desktop, Cursor, and Claude Code. Scroll to the Quick Install section and select your client.
What can io.github.zenml-io/mcp-zenml do?: io.github.zenml-io/mcp-zenml provides 17 tools: Users, Stacks, Flavors, Pipelines, Schedules and 12 more. See the full tools list on the server page for descriptions and parameters.
What AI clients work with io.github.zenml-io/mcp-zenml?: io.github.zenml-io/mcp-zenml is compatible with claude-desktop, cursor, claude-code. It uses stdio and sse and http transport.
Is io.github.zenml-io/mcp-zenml actively maintained?: io.github.zenml-io/mcp-zenml is actively maintained — last commit was 21 days ago. It has 44 GitHub stars.