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Marimo Documentation MCP Server: Integrate & Scale AI Contexts - MCP Implementation

Marimo Documentation MCP Server: Integrate & Scale AI Contexts

Streamline access to Marimo Documentation with our MCP server—easily integrate, manage, and scale AI model contexts programmatically.

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About Marimo Documentation MCP Server

What is Marimo Documentation MCP Server: Integrate & Scale AI Contexts?

Marimo Documentation MCP Server is a TypeScript-based middleware designed to streamline access to Marimo's comprehensive API documentation. It acts as a structured interface for developers to query, search, and integrate Marimo UI components and core features into AI-driven applications. By abstracting complex documentation navigation, this server enables efficient retrieval of API details, parameters, and usage examples through standardized endpoints.

How to use Marimo Documentation MCP Server: Integrate & Scale AI Contexts?

Integration follows a straightforward workflow:

  1. Install dependencies via npm
  2. Build the server using npm run build
  3. Configure the MCP server path in your IDE (Claude Desktop or VSCode)
  4. Invoke tools like get_element_api or search_api through your application

See platform-specific instructions for path configuration in IDE settings files.

Marimo Documentation MCP Server Features

Key Features of Marimo Documentation MCP Server: Integrate & Scale AI Contexts?

  • Granular API Access: Retrieve detailed specs for components like sliders, buttons, and data inputs via get_element_api
  • Cross-Documentation Search: search_api enables keyword-based discovery across all Marimo sections
  • Section-Specific Coverage: Supports Inputs (forms, files), Layouts (accordion, routes), Media (audio/video), and Core Features (state management, plotting)
  • Error Intelligence: Clear validation messages with HTTP codes and element availability lists
  • Performance Optimizations: Built-in caching and efficient HTML parsing with Cheerio

Use Cases of Marimo Documentation MCP Server: Integrate & Scale AI Contexts?

Primary applications include:

  • Automating documentation checks during CI/CD pipelines
  • Building intelligent IDE plugins with real-time API suggestions
  • Powering chatbot knowledge bases for Marimo component troubleshooting
  • Creating cross-platform documentation sync tools

Its recursive search capability makes it ideal for large-scale documentation audits and pattern analysis.

Marimo Documentation MCP Server FAQ

FAQ from Marimo Documentation MCP Server: Integrate & Scale AI Contexts?

  • How do I debug connection issues? Use the MCP Inspector tool and check stderr logs for detailed tracebacks
  • Does it support Windows environments? Fully compatible through JSON config adjustments and node execution
  • Is caching configurable? Current implementation uses optimal defaults but may allow parameter tuning in future releases
  • What error codes can occur? 404 for missing elements, 400 for malformed requests, 500 for parsing failures
  • Can I add custom documentation? Currently focused on Marimo's official content, but extension APIs are planned

Content

Marimo Documenation MCP Server

A Model Context Protocol (MCP) server that provides access to the Marimo Documentation.

This TypeScript-based MCP server lets you fetch and search through Marimo's API documentation, providing structured access to components, interfaces, and examples across all documentation sections.

Features

Tools

get_element_api

Get detailed API documentation for any Marimo UI element or component.

  • Input: element (string) - Name of the element to get documentation for (e.g., "slider", "button")
  • Output: Structured API documentation including:
    • Title and description
    • Parameters with types and defaults
    • Code examples
    • Usage patterns

search_api

Search across all Marimo API documentation.

  • Input: query (string) - Search term to find in documentation
  • Output: Array of matching documentation entries from any section

Documentation Sections

The server provides access to documentation for all Marimo components:

Inputs

  • Form elements (button, checkbox, dropdown, etc.)
  • Data inputs (array, dataframe, dictionary)
  • File handling (file, file_browser)
  • Interactive elements (slider, range_slider, tabs)

Layouts

  • Structural components (accordion, sidebar, tree)
  • Organization tools (callout, carousel)
  • Content management (lazy, routes)

Media

  • Media elements (audio, video, image)
  • File handling (download, pdf)
  • Text display (plain_text)

Core Features

  • Markdown
  • Control Flow
  • Plotting
  • HTML
  • State Management
  • And more...

Development

Install dependencies:

npm install

Build the server:

npm run build

For development with auto-rebuild:

npm run watch

Installation

With Claude Desktop

Add to:

  • MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json

  • Windows: %APPDATA%/Claude/claude_desktop_config.json

    {
    "mcpServers": {
    "marimo-docs": {
    "command": "/path/to/marimo-docs/build/index.js"
    }
    }
    }

With VSCode Cline Extension

Add to:

  • MacOS: ~/Library/Application Support/Code/User/globalStorage/rooveterinaryinc.roo-cline/settings/cline_mcp_settings.json

  • Windows: %APPDATA%/Code/User/globalStorage/rooveterinaryinc.roo-cline/settings/cline_mcp_settings.json

    {
    "mcpServers": {
    "marimo-docs": {
    "command": "node",
    "args": ["/path/to/marimo-docs/build/index.js"]
    }
    }
    }

Debugging

Since MCP servers communicate over stdio, debugging can be challenging. For development, the server outputs detailed logs to stderr.

You can also use the MCP Inspector:

npm run inspector

The Inspector will provide a URL to access debugging tools in your browser.

Error Handling

The server provides organized error messages that:

  • List all available elements grouped by section
  • Provide clear feedback on invalid requests
  • Include proper HTTP error codes

Implementation Details

  • Uses Cheerio for HTML parsing of documentation pages
  • Implements caching to reduce documentation fetch requests
  • Handles proper URL construction for all documentation sections
  • Supports recursive search across all documentation content

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