MindmupGoogleDriveMcp
This server enables you to search, retrieve, and parse MindMup files stored in your Google Drive directly through the MCP interface.
MindMup2 Google Drive MCP Server
A Model Context Protocol (MCP) server that provides seamless integration between MindMup mind maps and Google Drive. This server enables you to search, retrieve, and parse MindMup files stored in your Google Drive directly through the MCP interface.
- Medium Article: https://medium.com/@shyinlim/using-google-drive-mindmup-mcp-to-review-test-cases-automatically-ee03f2e9272d
💫 Result
✨ Feature
- Search MindMup Files: Find MindMup files across your entire Google Drive (read-only)
- Google Drive Integration: List and filter files in Google Drive with various criteria
- MindMup Parsing: Parse and extract content from MindMup mind map files
- FastMCP Server: Built on FastMCP framework for high performance
- Docker Support: Containerized deployment with Docker Compose
🔧 Available MCP Tools
| Tool | Description |
|---|---|
| gdrive_tool_list_file | List files from Google Drive with optional filtering by file type or name |
| get_single_mindmup_tool | Get a single MindMup file by ID or name |
| analyze_mindmup_summary_tool | Get summary overview of a MindMup file (sections, node count, structure) |
| get_mindmup_chunk_tool | Get specific chunk of a large MindMup file with optional keyword search |
🧠 Business Value
- Unified Knowledge Management: Centralize mind map access across Google Drive through a single MCP interface
- Enhanced Productivity: Quick search and retrieval of mind maps without switching between applications
- Developer Integration: Seamlessly integrate mind mapping capabilities into existing workflows and tools
- Scalable Architecture: Handle large collections of mind maps with efficient filtering and parsing
- Cross-Platform Compatibility: Access mind maps from any MCP-compatible client or application
🏗️ Project Structure
├── deployment/
│ ├── docker-compose-dev.yml
│ ├── docker-compose-prod.yml
│ └── Dockerfile
├── src/
│ ├── core/
│ │ ├── gdrive_client.py # Google Drive API client
│ │ ├── gdrive_feature.py # Google Drive feature implementation
│ │ ├── mcp_server.py # Main MCP server implementation
│ │ └── mindmup_parser.py # MindMup file parsing
│ ├── model/
│ │ ├── common_model.py # Common data models
│ │ ├── gdrive_model.py # Google Drive data models
│ │ └── mindmup_model.py # Mind map data models
│ └── utility/
│ ├── enum.py # Enumerations and constants
│ └── logger.py # Logging utilities
├── run.py # Main entry point
├── requirements.txt # Python dependencies
└── makefile # Build and deployment commands
🚀 Getting Started
Prerequisites
- Python 3.12+
- Google Cloud Platform account
Google Drive API Setup
| Step | Description | Image |
|---|---|---|
| 1 | Go to Google Cloud Console and create a new project or select an existing one | |
| 2 | Enable Google Drive API in your project | |
| 3 | Create Service Account credentials:- Go to "IAM & Admin" → "Service Accounts"- Click "Create Service Account"- Download the JSON key file | |
| 4 | Encode the entire JSON key file to base64:- See Generate Base64 Credential section | |
| 5 | Share your Google Drive folder with the Service Account:- Right-click folder → Share- Paste the service account email- Grant Viewer access- Do NOT send invitation |
Run the Server
For development:
make run-dev-docker
For production:
make run-prod
MCP Client Configuration
Add this server to your MCP client configuration:
{ "mcpServers":{ "mindmup-gdrive":{ "type":"http", "url":"http://:9802/mcp", "headers":{ "X-Google-Credential":"BASE64_GOOGLE_SERVICE_ACCOUNT" } } } }
Generate Base64 Credential
Encode your Google service account JSON to base64:
https://www.base64encode.org/
Copy the output and paste it as the X-Google-Credential value.
Example
{ "mcpServers":{ "mindmup-gdrive":{ "type":"http", "url":"http://:9802/mcp", "headers":{ "X-Google-Credential":"ewogICJ0eXBlIjogInN" } } } }
🔍 Future Plan
- Create MindMup Files: Create new mind maps directly through MCP interface
- Edit MindMup Content: Modify existing mind map nodes and structure
- Export Features: Export mind maps to various formats (PDF, PNG, SVG)
- Sync Operations: Two-way synchronization between local and cloud mind maps
- Advanced Tagging: Add metadata and tags to mind map nodes
- Plugin System: Extensible plugin architecture for custom functionality
Contribution
This project is a collaborative effort:
- 50% developed by the project maintainer
- 50% generated with assistance from Claude AI
관련 서버
Linear
Query and search for issues in your Linear workspace.
SVG Converter
Convert SVG files to PNG, ICO, and JPG formats with high-quality rendering using the Cairo C library.
Pulsetic MCP Server
The Pulsetic MCP Server connects Pulsetic monitoring with AI agents and MCP-compatible tools, enabling direct access to uptime data, cron monitoring results, incident management workflows, and status page information through the Model Context Protocol (MCP). It allows teams to securely expose operational monitoring data in a structured format, making it easy to build AI-driven automation, monitoring assistants, and intelligent operational workflows without custom middleware.
TikTok Ads MCP Server
A Model Context Protocol (MCP) server for TikTok Ads API integration. This server enables AI assistants like Claude to interact with TikTok advertising campaigns, providing comprehensive campaign management, analytics, and optimization capabilities. Part of the AdsMCP project - MCP servers for advertising platforms.
MCPApp
A Google Apps Script-based MCP network that allows AI to securely access Google Workspace data like Gmail and Calendar.
Substack Publisher API
Query posts, analytics, and subscriber data from Substack's official Publisher API
YouTube Uploader MCP
Upload videos to YouTube using OAuth2 authentication. Requires a Google OAuth 2.0 client secret file.
Propbar
UK property data: crime stats, schools, demographics, valuations, comparables, Ofsted ratings
MCP Handoff Server
Manages AI agent handoffs with structured documentation and seamless task transitions.
Canvas MCP
Interact with Canvas LMS and Gradescope using AI agents.