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Add GitBook MCP server documentation (#4080)
* Add GitBook MCP server documentation Adds documentation for ZenML's built-in GitBook MCP server that enables AI code agents (Claude Code, Cursor, etc.) to query ZenML documentation in real-time while coding. Changes: - docs/book/reference/llms-txt.md: Added comprehensive MCP server section with setup instructions for Claude Code and Cursor, positioned as the recommended approach alongside existing llms.txt documentation - docs/book/toc.md: Updated page title to "MCP Docs & llms.txt" for better discoverability - AGENTS.md: Added "Documentation Access via MCP" subsection in Development Workflow - CLAUDE.md: Added "Use ZenML Docs via MCP" section with CLI setup The MCP server endpoint (https://docs.zenml.io/~gitbook/mcp) provides live documentation queries, reducing hallucinations and improving feature discovery for AI coding assistants. * Add MCP server quick-win to documentation Adds a new quick-win entry (#14) showing developers how to connect AI coding assistants to live ZenML docs via the GitBook MCP server. This complements the MCP documentation added in the main PR by providing a quick-start guide in the productivity-focused quick-wins page. The entry includes setup instructions for Claude Code and Cursor, emphasizes the 5-minute setup time, and follows the established quick-wins format with Why/Setup/Features/Practices sections.
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AGENTS.md

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- It resolves dependencies more quickly and reliably than pip
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- It can resolve dependency conflicts that pip sometimes struggles with or takes a long time to resolve
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### Documentation Access via MCP
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ZenML documentation is available via a built-in GitBook MCP server: https://docs.zenml.io/~gitbook/mcp. IDE agents like Cursor and Claude Code can add this as an HTTP MCP server named 'ZenML Docs' to answer questions directly from the docs while you code. This enables live, source-of-truth lookups with fewer hallucinations and faster feature discovery. Note that the MCP server indexes the latest released docs, not the develop branch. For full setup details and examples, see docs/book/reference/llms-txt.md.
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### Environment Variables
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- Several environment variables are useful during ZenML development:
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- `ZENML_DEBUG=true`: Enables verbose debug logging

CLAUDE.md

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Use filesystem navigation tools to explore the codebase structure as needed.
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## Use ZenML Docs via MCP
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Claude Code can query ZenML documentation via the built-in GitBook MCP server: https://docs.zenml.io/~gitbook/mcp. This enables real-time, source-of-truth lookups from the docs while you code, reducing hallucinations and speeding up feature discovery.
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Quick setup (CLI):
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```bash
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claude mcp add zenmldocs --transport http https://docs.zenml.io/~gitbook/mcp
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```
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Note: The MCP server indexes the latest released docs, not the develop branch. For full setup details and editor alternatives, see docs/book/reference/llms-txt.md.
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## Code Style & Quality Standards
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### Formatting and Linting

docs/book/reference/llms-txt.md

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---
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icon: robot
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description: The llms.txt file(s) for ZenML
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description: Access ZenML documentation via MCP server or llms.txt
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---
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## About llms.txt
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- While prompting, instruct the LLM to only provide answers based on information contained in the file to avoid hallucinations
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- For best results, use models with sufficient context window to process the entire file
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## Use llms-full.txt for complete documentation context
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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.
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## Use the built-in GitBook MCP server (recommended)
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ZenML docs are also exposed through a native GitBook MCP server that IDE agents can query in real time.
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- Endpoint: https://docs.zenml.io/~gitbook/mcp
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### Quick setup
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#### Claude Code (VS Code)
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Run the following command in your terminal to add the server:
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```bash
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claude mcp add zenmldocs --transport http https://docs.zenml.io/~gitbook/mcp
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```
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#### Cursor
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Add the server via Cursor's JSON settings (Settings → search "MCP" → Configure via JSON):
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```json
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{
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"mcpServers": {
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"zenmldocs": {
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"transport": {
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"type": "http",
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"url": "https://docs.zenml.io/~gitbook/mcp"
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}
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}
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}
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}
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```
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### Why use it
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- Live doc queries directly from your IDE agent
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- Syntax-aware, source-of-truth answers with fewer hallucinations
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- Faster feature discovery across guides, APIs, and examples
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The MCP server indexes the latest released documentation, not the develop branch.
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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:
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To use the llms.txt file in partnership with an MCP client, you can use the
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following tools:
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docs/book/toc.md

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* [Community & content](reference/community-and-content.md)
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* [Environment Variables](reference/environment-variables.md)
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* [llms.txt](reference/llms-txt.md)
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* [MCP Docs & llms.txt](reference/llms-txt.md)
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* [FAQ](reference/faq.md)
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* [Global settings](reference/global-settings.md)
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* [Legacy docs](reference/legacy-docs.md)

docs/book/user-guide/best-practices/quick-wins.md

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| [HTML reports](#id-11-simple-html-reports) | Create rich visualizations effortlessly | Beautiful stakeholder-friendly outputs |
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| [Model Control Plane](#id-12-register-models-in-the-model-control-plane) | Track models and their lifecycle | Central hub for model lineage and governance |
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| [Parent Docker images](#id-13-create-a-parent-docker-image-for-faster-builds) | Pre-configure your dependencies in a base image | Faster builds and consistent environments |
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| [ZenML docs via MCP](#id-14-enable-ide-ai-zenml-docs-via-mcp-server) | Connect your IDE assistant to live ZenML docs | Faster, grounded answers and doc lookups while coding |
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## 1 Log rich metadata on every run
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For projects with heavy dependencies like deep learning frameworks, this approach can cut build times by 80-90%, turning a 5-minute build into a 30-second one. This is especially valuable in cloud environments where you pay for build time.
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Learn more: [Containerization](https://docs.zenml.io/concepts/containerization)
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## 14 Enable IDE AI: ZenML docs via MCP server
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**Why** -- wire your IDE AI assistant into the live ZenML docs in under 5 minutes. Get grounded answers, code snippets, and API lookups without context switching or hallucinations—perfect if you already use Claude Code or Cursor.
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{% hint style="info" %}
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The MCP server works with any MCP-compatible client. Below we demonstrate popular examples using Claude Code (VS Code) and Cursor. The server indexes the latest released documentation, not the develop branch.
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{% endhint %}
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**Setup**
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### Claude Code (VS Code)
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```bash
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claude mcp add zenmldocs --transport http https://docs.zenml.io/~gitbook/mcp
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```
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### Cursor (JSON settings)
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```json
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{
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"mcpServers": {
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"zenmldocs": {
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"transport": {
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"type": "http",
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"url": "https://docs.zenml.io/~gitbook/mcp"
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}
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}
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}
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}
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```
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**Try it**
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```
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Using the zenmldocs MCP server, show me how to register an MLflow experiment tracker in ZenML and add it to my stack. Cite the source page.
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```
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**Key features**
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- **Live answers** from ZenML docs directly in your IDE assistant
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- **Fewer hallucinations** thanks to source-of-truth grounding and citations
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- **IDE-native experience** — no code changes required in your project
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- **Great for API lookups** and "how do I" questions while coding
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**Best practices**
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- Prefix prompts with: "Use the zenmldocs MCP server …" and ask for citations
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- Remember: it indexes the latest released docs, not develop; for full offline context use `llms-full.txt`, for selective interactive queries prefer MCP
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- Keep the server name consistent (e.g., `zenmldocs`) across machines/projects
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- If your IDE supports tool selection, explicitly enable/select the `zenmldocs` MCP tool
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- For bleeding-edge features on develop, consult the repo or develop docs directly
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Learn more: [Access ZenML documentation via llms.txt and MCP](https://docs.zenml.io/reference/llms-txt)

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