mindmap

This MCP server converts Markdown content into interactive mindmaps. The Mindmap MCP supports multiple runtimes, including uvx, a Python execution path, and a Docker container. With uvx or Python, you can request the mindmap content directly as HTML, which you can preview in an AI client or browser. The Docker option exposes specialized tools inside the container, namely markdown-to-mindmap-content (returns HTML) and markdown-to-mindmap-file (saves an HTML file to a mounted directory). When using the uvx or Python routes, you typically receive the mindmap content inline (HTML) or as a file path if you choose the filePath return type. The Docker approach is best if you want isolation or you need to leverage the container-provided tools for more complex workflows. Determine which method matches your environment and integrate it into your MCP client configuration accordingly.

Prerequisites:

• Python 3.8+ or a working Node.js environment if you plan to use Node-based tooling (not required for this Python/uvx setup).
• pip or uv (for uvx) installed if you plan to use Python or uvx runtimes.
• Docker installed if you plan to run the Docker container.

Installation steps:

1. Install the Mindmap MCP package (Python):
   • Command: pip install mindmap-mcp-server
2. Alternative: use uvx runtime (if you have uvx installed):
   • Command: uvx mindmap-mcp-server
3. Docker-based usage (no local install needed beyond Docker):
   • No separate installation required for the container image; you just pull and run as documented in the README.
4. Verify installation:
   • For uvx or Python: run the configured command to ensure you receive an HTML mindmap or a file path as output.
   • For Docker: ensure the container runs with a mounted volume if you plan to save files, e.g., -v /path/to/output:/output.

Notes:

• If you encounter permission or path issues on macOS/Linux, ensure volumes are mounted with correct read/write permissions.
• Windows users may prefer the Docker route if CLI tool installation via npm/uvx is problematic.

Tips and common issues:

• When using Docker, you can choose between returning HTML content or saving to a file by using the provided tools inside the container. Use the appropriate parameters as described in the README (markdown-to-mindmap-content for HTML output, markdown-to-mindmap-file for file output).
• If you need tokens to be preserved or want larger mindmaps, the file-based approach via Docker (markdown-to-mindmap-file) is recommended because it saves an HTML file to the mounted directory.
• For quick previews in AI clients, use the HTML return type from uvx or Python runtimes and view the HTML in artifacts or a browser.
• If you run into issues with npx on Windows, switch to the Docker method or use uvx/Python as described in the README.