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MindManager MCP Server

MindManager MCP Server

WARNING

Deprecated: This MCP will not be developed further. Please use the Codex/Claude skills from https://github.com/robertZaufall/mindm-skill instead.

MindManager MCP Server

A Model Context Protocol (MCP) server implementation for the mindm library, providing a standardized interface to interact with MindManager on Windows and macOS.

PyPI version PyPI version

Overview

This server allows you to programmatically interact with MindManager through the Model Context Protocol (MCP), a standardized way to provide context and tools to LLMs. It leverages the mindm library to manipulate MindManager documents, topics, relationships, and other mindmap elements.

Animated examples (using Codex in VSCode on Windows)

  • Example Refining a single topic including tags, icons for the new topics:

get the current Mindmanager mindmap as mermaid (full), refine the given topics at least two levels deep (not just topics), add a tag "Important" to the 3 top most important topics and add corresponding stock icons to every topic but the central topic and create the new MindManager mindmap

MindManager MCP in Codex

  • Example Refining a single topic including generating text in notes for the new topics: MindManager MCP in Codex

  • Example Cloning a map including all supported topic properties: MindManager MCP in Codex

Related MCP server: Mermaid MCP Server

Other examples

Client

get the current MindManager mindmap, translate every topic to German and create a new MindManager mindmap (simple).

get the current MindManager mindmap, refine each topic 2 levels and create a new MindManager mindmap (simple).

Shell:

codex exec "get the current MindManager mindmap, add a meaningful emoji to every topic and create new MindManager mindmap (simple)"

remark: emojis only work on macOS.

Features

  • Retrieve mindmap structure and central topics

  • Export mindmaps to Mermaid, Markdown, JSON formats to be used in LLM chats

  • Create MindManager mindmaps directly from Mermaid (full or simplified syntax)

  • Fetch MindManager and package versions for quick diagnostics

  • Get information about MindManager installation and library folders

  • Get current selection from MindManager

Planned Features

  • Add, modify, and manipulate topics and subtopics without Mermaid roundtrips

  • Add relationships between topics

  • Add tags to topics

  • Set document background images

Requirements

  • Python 3.12 or higher

  • mcp package (Model Context Protocol SDK)

  • mindm library (included in this project)

  • MindManager (supported versions: 23-) installed on Windows or macOS

Installation macOS

# Clone the repository (if you're using it from a repository)
git clone https://github.com/robertZaufall/mindm-mcp.git
cd mindm-mcp

# create a virtual environment for Python
brew install uv # if needed
uv pip install -r pyproject.toml

# alternative: manual installation of modules
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

Installation Windows

# Change to DOS command prompt
cmd

# Clone the repository (if you're using it from a repository)
git clone https://github.com/robertZaufall/mindm-mcp.git
cd mindm-mcp

# create a virtual environment for Python
pip install uv # if needed
uv pip install -r pyproject.toml

# install nodejs
choco install nodejs # if you have chocolatey installed. If not install nodejs otherwise
refreshenv
node -v
npm install -g npx

Usage

MCP inspector

# run mcp with inspector
uv run --with mind --with fastmcp --with markdown-it-py mcp dev mindm_mcp/server.py

Claude Desktop

Local python file

Adjust the path for the local file as needed.

{
  "mcpServers": {
    "mindm (MindManager)": {
      "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"
      ]
    }
  }
}

Module from package repository

Adjust VIRTUAL_ENV as needed.

{
    "mcpServers": {
      "mindm (MindManager)": {
        "command": "uv",
        "args": [
          "run",
          "--with",
          "mindm>=0.0.5.3",
          "--with",
          "mindm-mcp>=0.0.2.1",
          "--with",
          "fastmcp",
          "--with",
          "markdown-it-py",
          "-m",
          "mindm_mcp.server"
        ],
        "env": {
            "VIRTUAL_ENV": "/Users/master/git/mindm-mcp/.venv"
        }
      }
  }
}

Hint: If the MCP server does not show up with the hammer icon on Windows, close Claude Desktop and kill all background processes.

Codex (VSCode Extension / CLI)

Local python file

config.toml (adjust the path for the local file as needed).

[features]
rmcp_client = true

[mcp_servers.mindmanager]
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"]

Module from package repository

config.toml

[features]
rmcp_client = true

[mcp_servers.mindmanager]
command = "uv"
args = ["run", "--with", "mindm>=0.0.5.3", "--with", "fastmcp", "--with", "markdown-it-py", "--with", "mindm-mcp>=0.0.2.1", "-m", "mindm_mcp.server"]

VSCode Chat (GitHub Copilot)

Local python file:

Adjust the path for the local file as needed.

uv run --with mindm>=0.0.5.3 --with fastmcp --with markdown-it-py /Users/master/git/mindm-mcp/mindm_mcp/server.py

or server definition in mcp.json:

		"Mindmanager": {
			"type": "stdio",
			"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"
			]
		}

Module from package repository

uv run --with mindm>=0.0.5.3 --with fastmcp --with markdown-it-py --with mindm-mcp>=0.0.2.1 -m mindm_mcp.server

or server definition in mcp.json:

		"Mindmanager": {
			"type": "stdio",
			"command": "uv",
			"args": [
				"run",
				"--with",
				"mindm>=0.0.5.3",
				"--with",
				"fastmcp",
				"--with",
				"markdown-it-py",
				"--with",
				"mindm-mcp>=0.0.2.1",
				"-m",
				"mindm_mcp.server"
			]
		}

MCP Tools

The server exposes the following tools through the Model Context Protocol:

Document Interaction

  • 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, selected subtopics) from the mindmap

Serialization

  • serialize_current_mindmap_to_mermaid: Serializes the currently loaded mindmap to Mermaid format

  • serialize_current_mindmap_to_markdown: Serializes the currently loaded mindmap to Markdown format

  • serialize_current_mindmap_to_json: Serializes the currently loaded mindmap to a detailed JSON object with ID mapping

Creation

  • 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

Versioning

  • get_versions: Returns the mindm-mcp and mindm package versions for debugging

Platform Support

  • Windows: Full support for topics, notes, icons, images, tags, links, relationships, and RTF formatting

  • macOS: Support for topics, notes, and relationships (limited support compared to Windows)

Integration with Claude and other LLMs

This MCP server can be installed in Claude Desktop or other MCP-compatible applications, allowing LLMs to:

  1. Access mindmap content

  2. Manipulate mindmaps (coming)

  3. Create new mindmaps based on LLM-generated content (coming)

Troubleshooting

  • Ensure MindManager is running before starting the server

  • For macOS, make sure you allow Claude Desktop to automate MindManager

MCPHub

Certified on MCPHub

Acknowledgements

This project is built upon the mindm library, providing Python interfaces to MindManager on Windows and macOS platforms. It uses the Model Context Protocol (MCP) SDK developed by Anthropic.

License

MIT License - See LICENSE file for details

Available Tools

11 tools
create_mindmap_from_mermaidB
Deserializes a Mermaid mindmap and creates a MindManager mindmap from it (caller must follow the guidance).

Args:
    mermaid (str): Mermaid text describing the desired mindmap with supported topic metadata, e.g. `[Topic] %% {"id": n, "notes": {"text": "Notes"}, "links": [{"text": "label", "url": "https://example.com"}], "references": [{"id_1": i, "id_2": j, "direction": 1}], "image": {"text": "C:\path\to\image.png"}, "icons": [{"text": "StockIcon-36", "is_stock_icon": true, "index": 36}], "tags": ["tag1"]}`

Guidance for callers constructing `mermaid`:
- Every line must be syntactically correct Mermaid code and contain at least a topic label, e.g. `[Topic]`.
- For the root topic just use the label, e.g. `[Central Topic]`
- Full syntax supports attaching metadata via JSON after `%%` on the same line, e.g.
  `[Topic] %% {"id": n, "notes": {"text": "Notes"}, "links": [{"text": "label", "url": "https://example.com"}], "references": [{"id_1": i, "id_2": j, "direction": 1}], "image": {"text": "C:\path\to\image.png"}, "icons": [{"text": "StockIcon-36", "is_stock_icon": true, "index": m}], "tags": ["tag1"]}`
- For icons, use `icons`: `[{"text": "StockIcon-<index>", "is_stock_icon": true, "index": <index>}]` where available options for stock icons are: Arrow Down(66), Arrow Left(65), Arrow Right(37), Arrow Up(36), Bomb(51), Book(67), Broken Connection(69), Calendar(8), Camera(41), Cellphone(40), Check(62), Clock(7), Coffee Cup(59), Dollar(15), Email(10), Emergency(49), Euro(16), Exclamation Mark(44), Fax(42), Flag Black(20), Flag Blue(18), Flag Green(19), Flag Orange(21), Flag Purple(23), Flag Red(17), Flag Yellow(22), Folder(71), Glasses(53), Hourglass(48), House(13), Information(70), Judge Hammer(54), Key(52), Letter(9), Lightbulb(58), Magnifying Glass(68), Mailbox(11), Marker 1(25), Marker 2(26), Marker 3(27), Marker 4(28), Marker 5(29), Marker 6(30), Marker 7(31), Meeting(61), Megaphone(12), No Entry(50), Note(63), On Hold(47), Padlock Locked(34), Padlock Unlocked(35), Phone(39), Question Mark(45), Redo(57), Resource 1(32), Resource 2(33), Rocket(55), Rolodex(14), Scales(56), Smiley Angry(5), Smiley Happy(2), Smiley Neutral(3), Smiley Sad(4), Smiley Screaming(6), Stop(43), Thumbs Down(64), Thumbs Up(46), Traffic Lights Red(24), Two End Arrow(38), Two Feet(60).

Returns:
    Dict[str, str]: Status dictionary indicating success or error details.

Inputs: mermaid (required). Returns: result

create_mindmap_from_mermaid_simpleA
Deserializes a Mermaid mindmap in simplified syntax and creates a MindManager mindmap from it.

Args:
    mermaid (str): Mermaid text describing the desired mindmap.
    turbo_mode (bool): Enable turbo mode (text-only operations). Defaults to True.

Returns:
    Dict[str, str]: Status dictionary indicating success or error details.

Inputs: mermaid (required), turbo_mode. Returns: result

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

Args:
    mode (str): Detail level ('full', 'content', 'text'). Defaults to 'full'.
    turbo_mode (bool): Enable turbo mode (text only). Defaults to False.

Returns:
    Union[List[str], Dict[str, str]]: A list containing [top_most_topic, subtopics_string] or error dictionary.

Inputs: mode, turbo_mode. Returns: result

get_library_folderB
Gets the path to the MindManager library folder.

Returns:
    Union[str, Dict[str, str]]: The library folder path or error dictionary.

Inputs: no named parameters. Returns: result

get_mindmanager_versionA
Gets the version of the MindManager application.

Returns:
    Union[str, Dict[str, str]]: The version of the MindManager application or error dictionary.

Inputs: no named parameters. Returns: result

get_mindmapB
Retrieves the current mind map structure from MindManager.

Args:
    mode (str): Detail level ('full', 'content', 'text'). Defaults to 'full'.
    turbo_mode (bool): Enable turbo mode (text only). Defaults to False.

Returns:
    Dict[str, Any]: Serialized mind map structure or error dictionary.

Inputs: mode, turbo_mode. Returns: result

get_selectionA
Retrieves the currently selected topics in MindManager.

Args:
    mode (str): Detail level ('full', 'content', 'text'). Defaults to 'full'.
    turbo_mode (bool): Enable turbo mode (text only). Defaults to False.

Returns:
    Union[List[Dict[str, Any]], Dict[str, str]]: List of serialized selected topics or error dictionary.

Inputs: mode, turbo_mode. Returns: result

get_versionsA
Get the versions of the MindManager Automation MCP Server components.

Returns:
    Dict[str, str]: A dictionary containing the versions of the components.

Inputs: no named parameters. Returns: result

serialize_current_mindmap_to_jsonA
Serializes the currently loaded mindmap to a detailed JSON object with ID mapping.

Args:
    ignore_rtf (bool): Whether to ignore RTF content. Defaults to True.
    mode (str): Detail level ('full', 'content', 'text'). Defaults to 'full'.
    turbo_mode (bool): Enable turbo mode (text only). Defaults to False.

Returns:
    Union[Dict[str, Any], Dict[str, str]]: JSON serializable dictionary or error dictionary.

Inputs: ignore_rtf, mode, turbo_mode. Returns: result

serialize_current_mindmap_to_markdownB
Serializes the currently loaded mindmap to Markdown format.

Args:
    include_notes (bool): If True, include notes in the serialization. Defaults to True.
    mode (str): Detail level ('full', 'content', 'text'). Defaults to 'content'.
    turbo_mode (bool): Enable turbo mode (text only). Defaults to False.

Returns:
    Union[str, Dict[str, str]]: Markdown formatted string or error dictionary.

Inputs: include_notes, mode, turbo_mode. Returns: result

serialize_current_mindmap_to_mermaidB
Serializes the currently loaded mindmap to Mermaid format.

Args:
    id_only (bool): If True, only include IDs without detailed attributes. Defaults to False.
    mode (str): Detail level ('full', 'content', 'text'). Defaults to 'full'.
    turbo_mode (bool): Enable turbo mode (text only). Defaults to False.

Returns:
    Union[str, Dict[str, str]]: Mermaid formatted string or error dictionary.

Inputs: id_only, mode, turbo_mode. Returns: result

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A3.7/5.0

    Scored across 11 tools

    Disambiguation4/5

    Most tools have distinct purposes, but there is some overlap between 'get_mindmap' and 'serialize_current_mindmap_to_json' as both retrieve mindmap data in structured formats. The three serialization tools (to JSON, Markdown, Mermaid) are clearly differentiated by output format, and creation vs. retrieval tools are well separated.

    Naming Consistency5/5

    All tools follow a consistent snake_case verb_noun pattern with clear action prefixes (create_, get_, serialize_). The naming is highly predictable, with 'serialize_current_mindmap_to_*' showing excellent consistency for the serialization family.

    Tool Count5/5

    11 tools is well-scoped for a MindManager automation server. The set covers creation (2 tools), retrieval (4 tools), serialization (3 tools), and utility functions (2 tools) without being overwhelming. Each tool appears to serve a distinct role in the mindmap workflow.

    Completeness4/5

    The server provides comprehensive coverage for mindmap creation, retrieval, and serialization workflows. Minor gaps exist in update/delete operations for mindmap content, but the core functionality for importing, exporting, and inspecting mindmaps is well covered. The inclusion of both simple and advanced creation tools shows thoughtful design.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

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