Which integrations are available for this server?

Converts Markdown files to XMind mind map format, with support for structure detection and batch processing. Uses Mermaid diagrams in documentation to visualize the architecture and data flow of the XMind conversion system. Provides Python-based tools for creating, analyzing, and converting multiple file formats to XMind mind maps with AI-powered structure analysis. Converts XML files to XMind mind map format with structure preservation. Converts YAML files to XMind mind map format with structure detection.

How do I use XMind AI MCP?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@XMind AI MCP convert my meeting notes from markdown to a mind map" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

XMind AI MCP

by Master-Frank

Overview Schema Related Servers Score Discussions

Python

Hybrid

🧠 XMind AI MCP – Intelligent Mind Mapping Toolkit

A robust toolkit for converting multiple formats to XMind, with AI analysis and a UVX-deployed MCP server.

Changelog

1.3.1: Fix analyze_mind_map compatibility with new read structure (no data.structure).

License: MIT MCP Badge

Related MCP server: @processon/mcp-server-processon

🚀 Core Features

1. Universal File Converter

Multi-format conversion: Markdown, Text, HTML, Word, Excel → XMind
Smart detection: Auto-detect file types and structure
Batch processing: Convert multiple files at once
Flexible output: Custom output paths and naming

2. MCP Server (UVX)

UVX-only deployment: no direct python or pip
IDE integration: Works seamlessly with Trae and MCP tools
FastMCP and STDIO modes supported

3. AI-Powered Analysis

Structure analysis: Optimize mind map structure
Topic suggestions: AI-generated recommendations
Quality metrics: Comprehensive assessment and validation

📁 Project Structure

XmindMcp/
├── configs/                      # MCP server config
├── docs/                         # Documentation and guides
├── examples/                     # Sample inputs
├── output/                       # Generated XMind files
├── tests/                        # Test suite
├── universal_xmind_converter.py  # Standalone converter CLI
├── xmind_core_engine.py          # Core engine
├── xmind_mcp_server.py           # MCP server (FastMCP / STDIO)
├── xmind_mcp/                    # Package entry (`xmind-mcp`)
│   ├── __init__.py
│   └── __main__.py
└── configs/mcp_config.json       # MCP server configuration (env only)

🔄 Architecture Overview

graph TD
    User([User]) -->|CLI| Converter[universal_xmind_converter.py]
    User -->|MCP| MCP[xmind_mcp_server.py]
    User -->|Tests| TestRunner[tests/run_all_tests.py]

    MCP -->|Tools| Core[xmind_core_engine.py]
    Core -->|Convert| Converter
    Core -->|Validate| Validator[validate_xmind_structure.py]
    Core -->|AI| AIExt[xmind_ai_extensions.py]

    Converter -->|Read| Examples[examples/]
    Converter -->|Write| Output[output/]

    classDef userLayer fill:#e1f5fe,stroke:#01579b,stroke-width:2px
    classDef serverLayer fill:#f3e5f5,stroke:#4a148c,stroke-width:2px
    classDef engineLayer fill:#e8f5e8,stroke:#1b5e20,stroke-width:2px
    classDef fileLayer fill:#fce4ec,stroke:#880e4f,stroke-width:2px

    class User,TestRunner userLayer
    class MCP serverLayer
    class Core,AIExt engineLayer
    class Examples,Output fileLayer

🔧 Quick Start (UVX)

Install UV (if not installed)

powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

Run (published package)

uvx xmind-mcp --mode fastmcp
uvx xmind-mcp --version
uvx xmind-mcp --help

Local development (in repo root)

uvx --from . xmind-mcp --mode fastmcp
# Fallback (STDIO)
uvx xmind-mcp --stdio

🖥️ Trae MCP Integration (UVX)

Standard configuration (recommended)

{
  "mcpServers": {
    "xmind-mcp": {
      "command": "uvx",
      "args": ["xmind-mcp"],
      "env": {
        "PYTHONIOENCODING": "utf-8",
        "PYTHONUTF8": "1"
      },
      "description": "XMind MCP - UVX installed",
      "disabled": false,
      "autoApprove": []
    }
  }
}

Local development configuration (no absolute paths)

{
  "mcpServers": {
    "xmind-mcp": {
      "command": "uvx",
      "args": ["--from", ".", "xmind-mcp"],
      "env": {
        "PYTHONIOENCODING": "utf-8",
        "PYTHONUTF8": "1"
      },
      "description": "XMind MCP - local development",
      "disabled": false,
      "autoApprove": []
    }
  }
}

📦 Standalone Conversion (CLI)

Single file

python universal_xmind_converter.py examples/test_markdown.md
python universal_xmind_converter.py examples/test_document.docx --output output/my_mind_map.xmind

Batch conversion

python universal_xmind_converter.py examples/ --batch
python universal_xmind_converter.py examples/ --batch --format markdown,html,txt

🛠️ Available MCP Tools

read_xmind_file(file_path) – read XMind content
create_mind_map(title, topics_json, output_path?) – create a new map
analyze_mind_map(file_path) – analyze structure and metrics
convert_to_xmind(source_filepath, output_filepath?) – convert files to XMind
list_xmind_files(directory?, recursive?) – list XMind files
translate_xmind_titles(source_filepath, output_filepath?, target_lang?, overwrite?)

✅ Usage Examples (Trae MCP)

Convert a Markdown file

convert_to_xmind({
  "source_filepath": "examples/test_markdown.md"
  # omit output_filepath to use the server's default absolute output directory (if configured)
})

Create a mind map (use default_output_dir in config)

create_mind_map({
  "title": "Project Plan",
  "topics_json": [{"title": "Milestone 1"}, {"title": "Milestone 2"}]
  # do not pass output_path if a default absolute output directory is configured
})

Analyze an existing map

analyze_mind_map({
  "file_path": "output/test_markdown.xmind"
})

⚙️ Paths & Configuration

Examples in docs use project-relative paths for readability.
For MCP output tools, configure a default absolute output directory via MCP config env (configs/mcp_config.json) or CLI --default-output-dir.
If no default is configured, pass an explicit absolute output_path/output_filepath in tool calls; relative paths are rejected by MCP output tools.

🧪 Run Tests

python tests/run_all_tests.py
python tests/run_all_tests.py --english
python tests/test_setup.py
python tests/test_core.py

📖 Documentation

docs/TRAE_MCP_SETUP.md – IDE MCP configuration
docs/UNIVERSAL_CONVERTER_USAGE.md – standalone converter usage
docs/xmind_ai_mcp_design.md – architecture and design

🎨 Supported Formats

Markdown (.md, .markdown)
Text (.txt, .text)
HTML (.html, .htm)
Word (.docx)
Excel (.xlsx)
CSV (.csv)
JSON (.json)
XML (.xml)
YAML (.yaml, .yml)

🤝 Contributing

Fork the repository
Create a feature branch (git checkout -b feature/your-feature)
Commit (git commit -m "feat: add your feature")
Push (git push origin feature/your-feature)
Open a Pull Request

🔍 Validation & Quality

9 file formats validated for conversion
Structure integrity maintained
Content fidelity preserved
XMind format compliance ensured

📝 License

MIT License – see LICENSE for details.

🙏 Acknowledgments

XMind team for the excellent mind mapping tool
Trae IDE for the powerful development environment
All contributors who helped improve this project

This server cannot be installed

license - permissive license

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

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