RapidChart MCP Server

RapidChart MCP Server

Generate and manage diagrams (class, ER, sequence, architecture) directly from code in Cursor IDE using RapidChart's AI-powered diagramming service with support for multiple AI models.

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RapidChart MCP Server

Model Context Protocol (MCP) server for RapidChart - Generate and manage diagrams directly from Cursor IDE.

Features

  • šŸŽØ Generate diagrams from code (Class, ER, Sequence, Architecture, etc.)
  • šŸ”„ Update existing diagrams with new code
  • šŸ“ Organize diagrams in workspaces and folders
  • šŸ¤– Support for multiple AI models (GPT-5, Claude, Gemini)
  • šŸ” Secure Bearer token authentication
  • šŸ’³ Respects your RapidChart credits and API keys

Installation

pip install rapidchart-mcp

Or install from source:

git clone https://github.com/Samicostox/rapidchart-mcp.git
cd rapidchart-mcp
pip install -e .

Configuration

1. Generate API Token

  1. Go to RapidChart Settings
  2. Navigate to "API Tokens"
  3. Click "Generate New Token"
  4. Copy the token (starts with rc_)

2. Configure Cursor

Add to your Cursor MCP settings (~/.cursor/mcp.json or workspace .cursor/mcp.json):

{
  "mcpServers": {
    "rapidchart": {
      "command": "python",
      "args": ["-m", "rapidchart_mcp"],
      "env": {
        "RAPIDCHART_API_TOKEN": "rc_your_token_here",
        "RAPIDCHART_API_URL": "https://fastuml-0bb6938ba599.herokuapp.com",
        "RAPIDCHART_DEFAULT_TYPE": "general",
        "RAPIDCHART_FEW_PROMPTS": "false",
        "RAPIDCHART_GUIDELINES": "true"
      }
    }
  }
}

Usage

In Cursor

Once configured, you can use natural language:

User: "Generate a class diagram from src/models.py"
→ Cursor reads the file and calls RapidChart MCP
→ Returns diagram URL

User: "List my available AI models"
→ Shows models with your credit status

User: "Update diagram abc123 with new code from src/models.py"
→ Updates the diagram with context awareness

Available Tools

  • list_models - Show available AI models and your credits
  • list_workspaces - List your workspaces
  • list_folders - List folders in a workspace
  • list_diagrams - Browse your diagrams
  • create_diagram - Generate diagram from code
  • get_diagram - Get specific diagram details
  • update_diagram - Update diagram with new code
  • delete_diagram - Delete a diagram
  • move_diagram - Move diagram to different folder/workspace

Environment Variables

Variable Required Default Description
RAPIDCHART_API_TOKEN āœ… Yes - Your RapidChart API token
RAPIDCHART_API_URL No Production URL API base URL
RAPIDCHART_DEFAULT_TYPE No general Default diagram type
RAPIDCHART_DEFAULT_MODEL No Auto Default AI model ID
RAPIDCHART_FEW_PROMPTS No false Enable multi-step thinking
RAPIDCHART_GUIDELINES No true Include diagram guidelines
RAPIDCHART_TIMEOUT No 300 Request timeout (seconds)

Development

# Clone the repo
git clone https://github.com/rapidchart/rapidchart-mcp.git
cd rapidchart-mcp

# Install in development mode
pip install -e .

# Run tests
pytest

# Run the server directly
python -m rapidchart_mcp

Known Issues

503 Timeout on Diagram Creation

Symptom: You get a 503 Service Unavailable error, but the diagram is created successfully.

Cause: Heroku has a 30-second router timeout. Complex diagrams can take 30-60+ seconds to generate.

Solution:

  1. The diagram IS being created despite the error
  2. Run list_diagrams to see your newly created diagram
  3. This is a Heroku limitation, not a bug in RapidChart

Workaround: Use simpler code or smaller diagrams for faster generation.


License

MIT

Support

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