MindManager

MindManager MCP Server for Automation and Integration on Win + macOS

python

10

GitHub Stars

python

Language

6 months ago

First Indexed

2 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "robertzaufall-mindm-mcp": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "mindm>=0.0.5.3",
        "--with",
        "fastmcp",
        "--with",
        "markdown-it-py",
        "/Users/master/git/mindm-mcp/mindm_mcp/server.py"
      ]
    }
  }
}

You can run a MindManager MCP Server to interact with MindManager documents programmatically, enabling you to extract, manipulate, and serialize mindmaps from your applications or AI workflows. This server uses the mindm library to control MindManager on Windows and macOS and exposes a set of tools via the Model Context Protocol (MCP) so you can integrate MindManager capabilities with your LLMs and automation flows.

How to use

You connect to the MindManager MCP Server from an MCP-compatible client by launching the server process and then communicating with its exposed tools. The server runs locally through a standard command line entry (stdio) and accepts commands to retrieve mindmaps, serialize data, transform maps from Mermaid, and create new maps in MindManager. Use the client to fetch the current mindmap, inspect the central topic and subtopics, and perform transformations or exports for your AI workflows. If you plan to extend or automate MindManager through coding or an AI assistant, this server provides the programmatic surface you need.

How to install

Prerequisites you need before installing the MCP server:

Python 3.12 or higher installed on your system.
MindManager installed on Windows or macOS (supported versions: 23–).
A tool to run MCP servers locally, such as UV (used to execute Python-based MCP servers). You will run commands shown in the examples to start the server.

Step-by-step setup for macOS:

Clone the project repository.

git clone https://github.com/robertZaufall/mindm-mcp.git

Change to the project directory.

cd mindm-mcp

Create a Python virtual environment and install dependencies.

uv pip install -r pyproject.toml

Install necessary modules (examples shown in common usage). You can install via uvx or equivalent package tools as demonstrated:

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

Step-by-step setup for Windows (Command Prompt):

Clone the repository.

git clone https://github.com/robertZaufall/mindm-mcp.git

Change to the project directory.

cd mindm-mcp

Create a Python virtual environment and install dependencies.

pip install uv

uv pip install -r pyproject.toml

Install Node.js and necessary tooling (if you plan to use CLI or JS-based tooling):

choco install nodejs

refreshenv

npm install -g npx

Available tools

get_mindmap

Retrieves the current mindmap structure from MindManager.

get_selection

Retrieves the currently selected topics in MindManager.

get_library_folder

Gets the path to the MindManager library folder.

get_mindmanager_version

Gets the installed MindManager version.

get_grounding_information

Extracts grounding information (central topic and selected subtopics) from the mindmap.

serialize_current_mindmap_to_mermaid

Serializes the current mindmap to Mermaid format.

serialize_current_mindmap_to_markdown

Serializes the current mindmap to Markdown format.

serialize_current_mindmap_to_json

Serializes the current mindmap to a detailed JSON object with ID mapping.

create_mindmap_from_mermaid

Build a MindManager map from Mermaid (full syntax with IDs and metadata).

create_mindmap_from_mermaid_simple

Build a MindManager map from simplified Mermaid text.

get_versions

Returns the mindm-mcp and mindm package versions for debugging.