LLM Tooling

LLM tooling for ZenML - MCP servers, llms.txt, and Agent Skills

ZenML provides multiple ways to enhance your AI-assisted development workflow:

• MCP servers for real-time doc queries and server interaction

• llms.txt for grounding LLMs with ZenML documentation

• Agent Skills for guided implementation of ZenML features

About llms.txt

The llms.txt file format was proposed by llmstxt.org as a standard way to provide information to help LLMs answer questions about a product/website. From their website:

We propose adding a /llms.txt markdown file to websites to provide LLM-friendly content. This file offers brief background information, guidance, and links to detailed markdown files. llms.txt markdown is human and LLM readable, but is also in a precise format allowing fixed processing methods (i.e. classical programming techniques such as parsers and regex).

ZenML's llms.txt

ZenML's documentation is now made available to LLMs at the following link:

https://docs.zenml.io/llms.txt

This file contains a comprehensive summary of the ZenML documentation (containing links and descriptions) that LLMs can use to answer questions about ZenML's features, functionality, and usage.

How to use the llms.txt file

When working with LLMs (like ChatGPT, Claude, or others), you can use this file to help the model provide more accurate answers about ZenML:

• Point the LLM to the docs.zenml.io/llms.txt URL when asking questions about ZenML

• While prompting, instruct the LLM to only provide answers based on information contained in the file to avoid hallucinations

• For best results, use models with sufficient context window to process the entire file

Use llms-full.txt for complete documentation context

The llms-full.txt file contains the entire ZenML documentation in a single, concatenated markdown file optimized for LLMs. Use it when you want to load all docs as context at once (for example, a one-shot grounding pass) rather than querying individual pages. Access it here: https://docs.zenml.io/llms-full.txt. For interactive, selective queries from your IDE, the built-in MCP server is still the recommended option.

Use the built-in GitBook MCP server (recommended)

ZenML docs are also exposed through a native GitBook MCP server that IDE agents can query in real time.

• Endpoint: https://docs.zenml.io/~gitbook/mcp

Quick setup

Claude Code (VS Code)

Run the following command in your terminal to add the server:

claude mcp add zenmldocs --transport http https://docs.zenml.io/~gitbook/mcp

Cursor

Add the server via Cursor's JSON settings (Settings → search "MCP" → Configure via JSON):

{
  "mcpServers": {
    "zenmldocs": {
      "transport": {
        "type": "http",
        "url": "https://docs.zenml.io/~gitbook/mcp"
      }
    }
  }
}

Why use it

• Live doc queries directly from your IDE agent

• Syntax-aware, source-of-truth answers with fewer hallucinations

• Faster feature discovery across guides, APIs, and examples

The MCP server indexes the latest released documentation, not the develop branch.

Looking to chat with your ZenML server data? ZenML also provides its own MCP server that connects directly to your ZenML server, allowing you to query pipelines, analyze runs, and trigger executions through natural language. See the MCP Chat with Server guide for setup instructions.

Prefer the native GitBook MCP server above for the best experience; if you prefer working directly with llms.txt or need alternative workflows, the following tools are helpful:

To use the llms.txt file in partnership with an MCP client, you can use the following tools:

• GitMCP - A way to quickly create an MCP server for a github repository (e.g. for zenml-io/zenml)

• mcp-llms - This shows how to use an MCP server to iteratively explore the llms.txt file with your MCP client

• mcp-llms-txt-explorer - A tool to help you explore and discover websites that have llms.txt files

ZenML Agent Skills

Agent Skills are modular capabilities that help AI coding agents perform specific tasks. ZenML publishes skills through a plugin marketplace that works with many popular agentic coding tools.

Supported tools

ZenML skills work with tools that support the Agent Skills format:

Tool	Type	Skills support
Claude Code	Anthropic's CLI agent	Native plugin marketplace
OpenAI Codex CLI	OpenAI's terminal agent	Native skills support
GitHub Copilot	IDE coding assistant	Agent Skills integration
OpenCode	Open source AI agent	Native skills support
Amp	AI coding assistant	Agent Skills integration
Cursor	AI-powered IDE	Via settings configuration
Gemini CLI	Google's terminal agent	Skills support

Installing ZenML skills

Claude Code

# Add the ZenML marketplace (one-time setup)
/plugin marketplace add zenml-io/skills

# Install available skills
/plugin install zenml-quick-wins@zenml

OpenAI Codex CLI

# Add the ZenML marketplace
codex plugin add zenml-io/skills

# Install skills
codex plugin install zenml-quick-wins@zenml

Available skills

zenml-quick-wins

Guides you through discovering and implementing high-impact ZenML features. The skill investigates your current setup, recommends priorities based on your stack, and helps implement improvements interactively.

Use when:

• You want to improve your ZenML setup

• You're looking for MLOps best practices to adopt

• You need help with features like experiment tracking, alerting, scheduling, or model governance

What it does:

1. Investigate - Analyzes your stack configuration and codebase

2. Recommend - Prioritizes quick wins based on your current setup

3. Implement - Helps you apply selected improvements

4. Verify - Confirms the implementation works

Example prompts:

Use zenml-quick-wins to analyze this repo and recommend the top 3 quick wins.

Implement metadata logging and tags across my pipelines.

Set up Slack alerts for pipeline failures.

See the Quick Wins guide for the full catalog of improvements this skill can help implement.

Coming soon

We're developing additional skills to help with common ZenML workflows:

• Pipeline creation - Scaffolding new pipelines from templates

• Stack setup - Guided stack component configuration

• Debugging - Investigating pipeline failures and performance issues

• Migration - Migrating from other MLOps platforms and orchestrators to ZenML

Combining MCP + Skills

For the best AI-assisted ZenML development experience, combine:

1. GitBook MCP server (https://docs.zenml.io/~gitbook/mcp) - For doc-grounded answers

2. ZenML server MCP (setup guide) - For querying your live pipelines, runs, and stacks

3. Agent Skills - For guided implementation of features

This gives your AI assistant access to documentation, your actual ZenML data, and structured workflows for making changes.