excalidraw-mcp

Excalidraw MCP Server: AI-Powered Live Visual Diagramming

🙏 Acknowledgments This project is based on and extends the excellent work from yctimlin/mcp_excalidraw. Special thanks to the original contributors for creating the foundation that made this enhanced version possible.

A dual-language MCP (Model Context Protocol) server that combines Excalidraw's powerful drawing capabilities with AI integration, enabling AI agents like Claude to create and manipulate diagrams in real-time on a live canvas.

Features Python FastMCP server with TypeScript canvas server for optimal performance and maintainability.

🚀 What This System Does

• 🎨 Live Canvas: Real-time Excalidraw canvas accessible via web browser
• 🤖 AI Integration: MCP server allows AI agents (like Claude) to create visual diagrams
• ⚡ Real-time Sync: Elements created via MCP API appear instantly on the canvas
• 🔄 WebSocket Updates: Live synchronization across multiple connected clients
• 🏗️ Production Ready: Clean, minimal UI suitable for end users

🎥 Demo Video

See MCP Excalidraw in Action!

Watch how AI agents create and manipulate diagrams in real-time on the live canvas

🏛️ Architecture Overview

┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│   AI Agent      │───▶│   MCP Server     │───▶│  Canvas Server  │
│   (Claude)      │    │    (Python)      │    │ (Express.js)    │
└─────────────────┘    └──────────────────┘    └─────────────────┘
                                                         │
                                                         ▼
                                               ┌─────────────────┐
                                               │  Frontend       │
                                               │  (React + WS)   │
                                               └─────────────────┘

Hybrid Architecture Benefits:

• Python FastMCP: Handles MCP protocol, tool registration, and auto-manages canvas server
• TypeScript Canvas: Express.js API + WebSocket for real-time canvas synchronization
• Auto-Management: Python server monitors and restarts canvas server as needed
• Type Safety: Comprehensive TypeScript definitions ensure consistency across the stack

🌟 Key Features

Modern TypeScript Architecture

• Full TypeScript Migration: Complete type safety for backend and frontend
• Comprehensive Type Definitions: Excalidraw elements, API responses, WebSocket messages
• Strict Type Checking: Enhanced development experience and compile-time error detection
• Type-Safe React Components: TSX components with proper props typing

Real-time Canvas Integration

• Elements created via MCP appear instantly on the live canvas
• WebSocket-based real-time synchronization
• Multi-client support with live updates

Production-Ready Interface

• Clean, minimal UI with connection status
• Simple "Clear Canvas" functionality
• No development clutter or debug information

Comprehensive MCP API

• Element Creation: rectangles, ellipses, diamonds, arrows, text, lines
• Element Management: update, delete, query with filters
• Batch Operations: create multiple elements in one call
• Advanced Features: grouping, alignment, distribution, locking

Robust Architecture

• TypeScript-based Express.js backend with REST API + WebSocket
• React frontend with official Excalidraw package and TypeScript
• Dual-path element loading for reliability
• Auto-reconnection and error handling

📦 Installation & Setup

✅ Quick Start (Recommended)

1. Clone and Setup

git clone https://github.com/lesleslie/excalidraw-mcp.git
cd excalidraw-mcp

# Install Python dependencies
uv sync

# Install Node.js dependencies and build
npm install
npm run build

2. Start the System

# The Python MCP server auto-starts the canvas server
uv run python excalidraw_mcp/server.py

# Or manually start canvas server (optional)
npm run canvas

3. Access the Canvas

Open your browser and navigate to:

http://localhost:3031

📋 Development Setup

# Development mode (TypeScript watch + Vite dev server)
npm run dev

# Or production mode
npm run production

🔧 Available Scripts

Script	Description
npm start	Build and start MCP server (dist/index.js)
npm run canvas	Build and start canvas server (dist/server.js)
npm run canvas-bg	Build and start canvas server in background
npm run start-canvas	Build and start canvas server
npm run canvas-for-npx	Special script for npx usage
npm run start-all	Start both servers together
npm run build	Build both frontend and TypeScript backend
npm run build:frontend	Build React frontend only
npm run build:server	Compile TypeScript backend to JavaScript
npm run build:types	Generate TypeScript declaration files only
npm run dev	Start TypeScript watch mode + Vite dev server
npm run dev:server	Start TypeScript in watch mode only
npm run type-check	Run TypeScript type checking without compilation
npm run production	Build + start in production mode
npm test	Run all tests
npm run test:watch	Run tests in watch mode
npm run test:coverage	Run tests with coverage report
npm run test:unit	Run unit tests only
npm run test:integration	Run integration tests only

🎯 Usage Guide

For End Users

• Open the canvas at http://localhost:3031
• Check connection status (should show "Connected")
• AI agents can now create diagrams that appear in real-time
• Use "Clear Canvas" to remove all elements

For AI Agents (via MCP)

The MCP server provides these tools for creating visual diagrams:

Basic Element Creation

// Create a rectangle
{
  "type": "rectangle",
  "x": 100,
  "y": 100,
  "width": 200,
  "height": 100,
  "backgroundColor": "#e3f2fd",
  "strokeColor": "#1976d2",
  "strokeWidth": 2
}

Create Text Elements

{
  "type": "text",
  "x": 150,
  "y": 125,
  "text": "Process Step",
  "fontSize": 16,
  "strokeColor": "#333333"
}

Create Arrows & Lines

{
  "type": "arrow",
  "x": 300,
  "y": 130,
  "width": 100,
  "height": 0,
  "strokeColor": "#666666",
  "strokeWidth": 2
}

Batch Creation for Complex Diagrams

{
  "elements": [
    {
      "type": "rectangle",
      "x": 100,
      "y": 100,
      "width": 120,
      "height": 60,
      "backgroundColor": "#fff3e0",
      "strokeColor": "#ff9800"
    },
    {
      "type": "text",
      "x": 130,
      "y": 125,
      "text": "Start",
      "fontSize": 16
    }
  ]
}

🔌 Integration with Claude Code

✅ Recommended: uvx Configuration

Add this configuration to your Claude Code .mcp.json:

{
  "mcpServers": {
    "excalidraw": {
      "command": "uvx",
      "args": ["excalidraw-mcp"],
      "env": {
        "EXPRESS_SERVER_URL": "http://localhost:3031",
        "ENABLE_CANVAS_SYNC": "true"
      }
    }
  }
}

Alternative: Local Development Configuration

For local development, use:

{
  "mcpServers": {
    "excalidraw": {
      "command": "uv",
      "args": ["run", "python", "excalidraw_mcp/server.py"],
      "cwd": "/absolute/path/to/excalidraw-mcp"
    }
  }
}

Important: Replace /absolute/path/to/excalidraw-mcp with the actual absolute path to your cloned repository.

🔧 Integration with Other Tools

Cursor IDE

Add to your .cursor/mcp.json:

{
  "mcpServers": {
    "excalidraw": {
      "command": "uvx",
      "args": ["excalidraw-mcp"],
      "env": {
        "EXPRESS_SERVER_URL": "http://localhost:3031"
      }
    }
  }
}

VS Code MCP Extension

For VS Code MCP extension, add to your settings:

{
  "mcp": {
    "servers": {
      "excalidraw": {
        "command": "uvx",
        "args": ["excalidraw-mcp"],
        "env": {
          "EXPRESS_SERVER_URL": "http://localhost:3031"
        }
      }
    }
  }
}

🛠️ Environment Variables

Variable	Default	Description
EXPRESS_SERVER_URL	http://localhost:3031	Canvas server URL for MCP sync
ENABLE_CANVAS_SYNC	true	Enable/disable canvas synchronization
CANVAS_AUTO_START	true	Auto-start canvas server with MCP server
SYNC_RETRY_ATTEMPTS	3	Number of retry attempts for failed operations
SYNC_RETRY_DELAY_SECONDS	1.0	Base delay between retry attempts (seconds)
SYNC_RETRY_MAX_DELAY_SECONDS	30.0	Maximum delay between retry attempts (seconds)
SYNC_RETRY_EXPONENTIAL_BASE	2.0	Exponential base for backoff calculation
SYNC_RETRY_JITTER	true	Enable/disable jitter for retry delays
PORT	3031	Canvas server port
HOST	localhost	Canvas server host
DEBUG	false	Enable debug logging

📊 API Endpoints

The canvas server provides these REST endpoints:

Method	Endpoint	Description
GET	/api/elements	Get all elements
POST	/api/elements	Create new element
PUT	/api/elements/:id	Update element
DELETE	/api/elements/:id	Delete element
POST	/api/elements/batch	Create multiple elements
GET	/health	Server health check

🎨 MCP Tools Available

Element Management

• create_element - Create any type of Excalidraw element
• update_element - Modify existing elements
• delete_element - Remove elements
• query_elements - Search elements with filters

Batch Operations

• batch_create_elements - Create complex diagrams in one call

Element Organization

• group_elements - Group multiple elements
• ungroup_elements - Ungroup element groups
• align_elements - Align elements (left, center, right, top, middle, bottom)
• distribute_elements - Distribute elements evenly
• lock_elements / unlock_elements - Lock/unlock elements

Resource Access

• get_resource - Access scene, library, theme, or elements data

🏗️ Development Architecture

Frontend (frontend/src/)

• React + TypeScript: Modern TSX components with full type safety
• Vite Build System: Fast development and optimized production builds
• Official Excalidraw: @excalidraw/excalidraw package with TypeScript types
• WebSocket Client: Type-safe real-time element synchronization
• Clean UI: Production-ready interface with proper TypeScript typing

Canvas Server (src/server.ts → dist/server.js)

• TypeScript + Express.js: Fully typed REST API + static file serving
• WebSocket: Type-safe real-time client communication
• Element Storage: In-memory with comprehensive type definitions
• CORS: Cross-origin support with proper typing
• Middleware: Custom Express middleware components
• Storage: Element storage implementations
• WebSocket: Dedicated WebSocket server components
• Utils: Utility functions for various operations

MCP Server (excalidraw_mcp/server.py)

• Python FastMCP: Python-based Model Context Protocol implementation
• Canvas Sync: HTTP requests to canvas server for element synchronization
• Element Management: Full CRUD operations for Excalidraw elements
• Batch Support: Complex diagram creation through batch operations
• Process Management: Canvas server lifecycle management
• HTTP Client: Async HTTP client with retry mechanisms
• Configuration: Centralized configuration management

Type System (src/types.ts)

• Excalidraw Element Types: Complete type definitions for all element types
• API Response Types: Strongly typed REST API interfaces
• WebSocket Message Types: Type-safe real-time communication
• Server Element Types: Enhanced element types with metadata

🐛 Troubleshooting

Canvas Not Loading

• Ensure npm run build completed successfully
• Verify canvas server is running on port 3031
• Python MCP server auto-starts canvas server - check console for errors

Elements Not Syncing

• Python server automatically manages canvas server
• Check ENABLE_CANVAS_SYNC=true in environment
• Verify canvas server health at http://localhost:3031/health

WebSocket Connection Issues

• Check browser console for WebSocket errors
• Ensure no firewall blocking WebSocket connections
• Try refreshing the browser page

Build Errors

• Delete node_modules and run npm install
• Check Node.js version (requires 16+)
• Run npm run type-check to identify TypeScript issues
• Run uv sync to update Python dependencies

Python Dependencies

• Use uv sync to install/update Python dependencies
• Ensure Python 3.13+ is installed
• Check uv --version to verify uv installation

📋 Project Structure

excalidraw-mcp/
├── examples/                 # Usage examples
├── excalidraw_mcp/           # Python FastMCP server
│   ├── monitoring/           # Monitoring and health check utilities
│   ├── server.py             # Main MCP server (Python)
│   ├── config.py             # Configuration management
│   ├── element_factory.py    # Element creation utilities
│   ├── http_client.py        # HTTP client for canvas server
│   ├── process_manager.py    # Canvas server lifecycle management
│   ├── retry_utils.py        # Retry mechanisms for failed operations
│   ├── cli.py                # Command-line interface
│   ├── mcp_tools.py          # MCP tool implementations
│   ├── __init__.py           # Package initialization
│   └── __main__.py           # Main entry point
├── frontend/                 # React frontend
│   ├── src/
│   │   ├── App.tsx           # Main React component (TypeScript)
│   │   └── main.tsx          # React entry point (TypeScript)
│   └── index.html            # HTML template
├── src/                      # TypeScript canvas server
│   ├── middleware/           # Express middleware components
│   ├── storage/              # Element storage implementations
│   ├── utils/                # Utility functions
│   ├── websocket/            # WebSocket server components
│   ├── config.ts             # Server configuration
│   ├── server.ts             # Express server + WebSocket (TypeScript)
│   └── types.ts              # Type definitions
├── dist/                     # Compiled TypeScript output
│   ├── server.js             # Compiled canvas server
│   ├── server.d.ts           # Server type definitions
│   ├── server.js.map         # Server source maps
│   ├── types.js              # Compiled type definitions
│   ├── types.d.ts            # Type definition files
│   ├── types.js.map          # Type definition source maps
│   ├── utils/                # Compiled utilities
│   ├── assets/               # Frontend assets
│   └── frontend/             # Built React frontend
├── tests/                    # Python test suite
│   ├── unit/                 # Unit tests
│   ├── integration/         # Integration tests
│   ├── security/             # Security tests
│   ├── performance/         # Performance tests
│   └── e2e/                  # End-to-end tests
├── .github/                  # GitHub configurations
├── pyproject.toml            # Python project configuration
├── package.json             # Node.js dependencies and scripts
├── tsconfig.json             # TypeScript configuration
└── README.md                 # This file

📦 Package Naming

This project uses consistent naming across different contexts:

• Python Package: excalidraw_mcp (underscore) - used in imports and Python module references
• PyPI Distribution: excalidraw-mcp (hyphen) - used for uvx excalidraw-mcp and pip installation
• npm Package: excalidraw-mcp (hyphen) - used for Node.js dependencies
• MCP Server Name: excalidraw - used in .mcp.json configuration

Example Usage:

# Python imports (underscore)
from excalidraw_mcp.server import main

# Shell commands (hyphen)
uvx excalidraw-mcp
pip install excalidraw-mcp

🧪 Testing & Quality Assurance

Coverage Requirements

• Python: 85% minimum test coverage (enforced by pytest)
• TypeScript: 70% minimum test coverage (enforced by Jest)

Running Tests

# Python tests with coverage
pytest --cov=excalidraw_mcp --cov-report=html
pytest --cov=excalidraw_mcp --cov-report=term-missing

# TypeScript tests with coverage
npm run test:coverage

# Run all tests
pytest && npm test

# Specific test categories
pytest tests/unit/                  # Python unit tests
pytest tests/integration/           # Python integration tests
pytest -m security                 # Security tests
pytest -m performance              # Performance benchmarks

npm run test:unit                   # TypeScript unit tests
npm run test:integration            # TypeScript integration tests

Quality Standards

This project enforces strict quality standards:

• All code must pass type checking (Pyright for Python, TSC for TypeScript)
• Security scanning with Bandit for Python
• Linting and formatting with Ruff (Python) and built-in TypeScript rules
• Comprehensive test coverage as specified above

📦 Publishing & Distribution

PyPI Distribution

The Python package is published to PyPI as excalidraw-mcp:

# Install from PyPI
pip install excalidraw-mcp

# Use with uvx (recommended)
uvx excalidraw-mcp

Local Development

For local development and testing:

# Install in editable mode
pip install -e .

# Or use UV for development
uv sync
uv run python excalidraw_mcp/server.py

Version Management

• Semantic versioning (SemVer) is used
• Version is managed in both pyproject.toml and package.json
• Releases are tagged in git with version numbers

🔮 Development Roadmap

• ✅ Python FastMCP Architecture: Modern hybrid implementation with auto-management
• ✅ TypeScript Canvas Server: Complete type safety for enhanced development experience
• ✅ Comprehensive Testing: Security, performance, and integration test suites
• 🔧 Enhanced Features: Additional MCP tools and canvas capabilities
• 🔧 Performance Optimization: Real-time sync improvements
• 🔧 Docker Deployment: Containerized deployment options

🤝 Contributing

We welcome contributions! Please:

• Fork the repository
• Create a feature branch (git checkout -b feature/amazing-feature)
• Commit your changes (git commit -m 'Add amazing feature')
• Push to the branch (git push origin feature/amazing-feature)
• Open a Pull Request

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Excalidraw Team - For the amazing drawing library
• MCP Community - For the Model Context Protocol specification