MindManager Model Context Protocol Gateway

This repository hosts an implementation of a Model Context Protocol (MCP) gateway, built around the mindm utility library, designed to standardize interaction with MindManager installations across both Windows and macOS environments.

Core Concept

This gateway exposes MindManager capabilities via the MCP framework, establishing a structured mechanism for providing contextual data and operations to advanced AI models. It relies fundamentally on the mindm toolkit for manipulating the underlying structure of MindManager documents, including nodes, linkages, metadata, and map components.

Example Interaction:

Functionality Summary

• Query the current state and primary subject matter of any active mindmap.
• Convert map layouts into serialization formats like Mermaid syntax, Markdown outlines, or detailed JSON object representations for LLM ingestion.
• Retrieve system configuration details pertaining to the MindManager installation directory and associated resource paths.
• Fetch the structure corresponding to the user's current focus selection within the application.

Forthcoming Enhancements

• Capacity to generate novel mindmaps from serialized input data.
• Routines for dynamic node and sub-node augmentation and modification.
• Mechanisms for establishing graphical or logical connections between disparate topics.
• Support for applying metadata labels (tags) to specific map elements.
• Functionality to set custom background imagery for the entire document canvas.

Prerequisites

• Runtime Environment: Python version 3.12 or newer is mandated.
• Dependencies: The core mcp package (Model Context Protocol Software Development Kit).
• Library: The mindm utility library (incorporated within this distribution).
• Host Application: A compatible version of MindManager (tested up to release 23) running on either Windows or macOS.

Setup Guide: macOS

# Obtain source code (if not using direct package installation)
git clone https://github.com/robertZaufall/mindm-mcp.git
cd mindm-mcp

# Environment setup using uv
brew install uv # Install uv utility if unavailable
uv pip install -r pyproject.toml

# Or, manual dependency bootstrapping
uv add "mcp[cli]"
uv add fastmcp
uv add markdown-it-py
uv add -U --index-url=https://test.pypi.org/simple/ --extra-index-url=https://pypi.org/simple/ mindm mindm-mcp

Setup Guide: Windows

# Switch to standard Command Prompt
cmd

# Obtain source code (if not using direct package installation)
git clone https://github.com/robertZaufall/mindm-mcp.git
cd mindm-mcp

# Environment setup using uv
pip install uv # Install uv utility if unavailable
uv pip install -r pyproject.toml

# Install Node.js runtime
choco install nodejs # Requires Chocolatey package manager
refreshenv # Refresh environment variables
npm install -g npx

Execution Instructions

Using the MCP Inspector Utility

# Initiate the MCP service, loading necessary components
uv run --with mind --with fastmcp --with markdown-it-py mcp dev mindm_mcp/server.py

Configuration for Claude Desktop

Direct Path Reference

Ensure the file path specified below accurately reflects your local system configuration.

{
  "mcpServers": {
    "mindm (MindManager)": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "mindm>=0.0.4.6",
        "--with",
        "fastmcp",
        "--with",
        "markdown-it-py",
        "/Users/master/git/mindm-mcp/mindm_mcp/server.py"
      ]
    }
  }
}

Package Repository Reference

Adapt the VIRTUAL_ENV variable to point to your environment's location.

{
    "mcpServers": {
      "mindm (MindManager)": {
        "command": "uv",
        "args": [
          "run",
          "--with",
          "mindm>=0.0.4.6",
          "--with",
          "mindm-mcp>=0.0.1.50",
          "--with",
          "fastmcp",
          "--with",
          "markdown-it-py",
          "-m",
          "mindm_mcp.server"
        ],
        "env": {
            "VIRTUAL_ENV": "/Users/master/git/mindm-mcp/.venv"
        }
      }
    }
}

Tip: If the connection icon fails to appear in Claude Desktop on Windows, restart the application and ensure no residual background processes related to the server are running.

Exposed MCP Toolset

The server makes the following functionalities available via the Model Context Protocol interface:

Document Exploration

• get_mindmap: Fetches the current conceptual structure of the active MindManager document.
• get_selection: Retrieves the collection of map nodes currently highlighted by the user.
• get_library_folder: Returns the file system location designated for MindManager auxiliary resources.
• get_grounding_information: Extracts critical context such as the central topic and subordinate selected nodes.

Data Transformation & Output

• serialize_current_mindmap_to_mermaid: Renders the entire map layout into the Mermaid diagram definition syntax.
• serialize_current_mindmap_to_markdown: Transforms the map hierarchy into a structured Markdown outline.
• serialize_current_mindmap_to_json: Outputs the map data as a comprehensive JSON structure, including unique identifier mappings for all elements.

Compatibility Matrix

• Windows OS: Complete feature parity covering nodes, annotations, visual markers, hierarchical data, hyperlinks, relationship links, and rich text formatting.
• macOS OS: Supports primary elements like nodes, notes, and structural linkages (functionality is somewhat reduced compared to the Windows implementation).

Integration with Cognitive Agents (Claude, etc.)

This MCP gateway facilitates external agent interaction by enabling them to:

1. Gain read-access to the graphical outline data.
2. Initiate structural modifications (future).
3. Synthesize and instantiate new maps based on generated output (future).

Common Issues Resolution

• Verify that the MindManager application is operational prior to server initiation.
• On macOS, confirm that system permissions allow the client application (e.g., Claude) to control MindManager via automation protocols.

MCP Hub Status

Verification Certificate on MCPHub

Credits

This solution is underpinned by the robust mindm library, which bridges Python to the native MindManager APIs on both major desktop operating systems. The Model Context Protocol SDK, developed by Anthropic, provides the necessary communication standardization.

Licensing

Distributed under the permissive MIT License (see LICENSE file for specifics).

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