import { Layout } from '@/layout'; import { MDX_DATA } from '@/mdx'; export default Layout(MDX_DATA.LLMDocumentation); # Mantine with LLMs Mantine provides LLM-friendly documentation to help AI tools like **Cursor**, **Windsurf**, **GitHub Copilot**, **ChatGPT**, and **Claude** understand and work with the Mantine UI library. `llms.txt` documentation is updated with every Mantine release. ## Documentation Links: - [llms.txt](/llms.txt) – compact - [Download](/llms-full.txt) full documentation in single document (~1.8MB) The LLM documentation includes: - **Getting Started** - Installation and setup guides - **Components** - All Mantine components with props, examples, and usage - **Hooks** - Complete hooks documentation with examples - **Theming** - Theme customization and MantineProvider setup - **Styles** - CSS modules, CSS variables, and styling approaches - **Frequently Asked Questions** - Common questions and solutions ## Cursor In Cursor, you can reference the documentation using the `@Docs` feature: 1. Type `@Docs` in your prompt 2. Reference the Mantine documentation URL: `https://mantine.dev/llms.txt` 3. Ask questions about Mantine components, styling, or implementation ## Windsurf For Windsurf users: 1. Reference the documentation using `@https://mantine.dev/llms.txt` 2. Or add it to your `.windsurfrules` file for persistent access ## ChatGPT and Claude When using ChatGPT or Claude: 1. Mention that you're using Mantine v8 2. Reference the documentation URL: `https://mantine.dev/llms.txt` 3. The AI will fetch and use the documentation to provide accurate answers ### GitHub Copilot While Copilot doesn't directly support external documentation, you can: 1. Include relevant documentation snippets in your comments 2. Reference component names and props accurately for better suggestions ## Skills Mantine also provides skills for AI coding agents in the [`mantinedev/skills`](https://github.com/mantinedev/skills) repository. Currently available skills: - `mantine-combobox` – Build custom select/autocomplete/multiselect components with `Combobox` - `mantine-form` – Build forms with `@mantine/form`, validation, nested fields, and form context - `mantine-custom-components` – Create custom components with Mantine factory APIs and Styles API ### Install skills Install each skill from the repository: ```bash npx skills add https://github.com/mantinedev/skills --skill mantine-combobox npx skills add https://github.com/mantinedev/skills --skill mantine-form npx skills add https://github.com/mantinedev/skills --skill mantine-custom-components ``` ### Use skills In your AI prompt, explicitly tell the agent to use one of the installed skills. Examples: - "Use `$mantine-form` and build a profile form with validation and nested fields" - "Use `$mantine-combobox` and create a searchable multi-select with custom option rendering" - "Use `$mantine-custom-components` and scaffold a polymorphic component with Styles API support" If your agent does not support `$skill-name` mentions, reference the skill name in plain text and ask the agent to follow it. ## MCP server (experimental) Mantine also provides an MCP server package: - `@mantine/mcp-server` The server reads Mantine static MCP data published on `mantine.dev` and exposes tools that AI agents can call directly: - `list_items` - `get_item_doc` - `get_item_props` - `search_docs` ### MCP server configuration Most MCP-compatible tools support adding servers with a JSON configuration. Use this server definition: ```json { "mcpServers": { "mantine": { "command": "npx", "args": ["-y", "@mantine/mcp-server"] } } } ``` To use a different data source (for example, alpha docs or local static files), add env variables: ```json { "mcpServers": { "mantine": { "command": "npx", "args": ["-y", "@mantine/mcp-server"], "env": { "MANTINE_MCP_DATA_URL": "https://mantine.dev/mcp" } } } } ``` ### Using MCP server with different tools #### Claude Desktop 1. Open MCP settings in Claude Desktop 2. Add the `mantine` server configuration above 3. Start a new chat and ask for Mantine guidance, for example: "Find Button props and give me a usage example" #### Cursor 1. Open Cursor MCP/server settings 2. Add the same `mantine` server config 3. Use agent mode and ask Mantine-specific questions – Cursor will call MCP tools automatically #### Windsurf 1. Open Windsurf MCP/server settings 2. Register `@mantine/mcp-server` with the same config 3. Ask for component docs, props, and examples directly in chat #### Other MCP clients (VS Code/Cline and others) If the client supports custom MCP servers, add the same command and args: - command: `npx` - args: `["-y", "@mantine/mcp-server"]` Then use prompts like: - "List Mantine items related to input fields" - "Get full docs for Button" - "Search Mantine docs for color scheme and dark mode" ## Example prompts Here are some example prompts you can use with AI tools: - "Using Mantine v8, how do I create a dark mode toggle?" - "Show me how to use the AppShell component with a collapsible navbar" - "How can I customize the theme colors in MantineProvider?" - "Create a form with validation using Mantine's form hooks" - "How to align input with a button in a flex container?" ## Documentation Generation The LLM documentation is automatically generated from our source files using a compilation script. It includes: - Component documentation from MDX files - Props tables and types - Code examples and demos - Styles API documentation - FAQ content from help.mantine.dev There are two generated formats: - `llms.txt` – the default compact index that links to per-page `.md` files under the `/llms` path - `llms-full.txt` – a single large file with all documentation content To ensure you have the latest documentation, we regenerate these files with each release. The files follow the [LLMs.txt](https://llmstxt.org/) standard for better compatibility with AI tools. ## Contributing If you find any issues with the LLM documentation or have suggestions for improvement, please [open an issue](https://github.com/mantinedev/mantine/issues) on our GitHub repository.