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

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

• 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

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

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

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)

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

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

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

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

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

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

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

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

• 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?)

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

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

• 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.

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

• 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

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

• 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

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

MIT License – see LICENSE for details.

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