Uses Google Gemini AI to generate PlantUML code for creating UML Class and Sequence diagrams from domain descriptions or free text input
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@UMLmcpcreate a sequence diagram for user login flow"
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.
UMLmcp
This project is a Python service that uses Google Gemini to generate PlantUML code for UML Class and Sequence diagrams. It exposes a gRPC interface and an MCP tool for generating UML diagrams.
Setup
Create a virtual environment:
python -m venv .venv source .venv/bin/activateInstall the dependencies:
pip install -r requirements.txtCreate a
key.txtfile in the root of the project and paste your Gemini API key in the first line.
Generating gRPC stubs
To generate the gRPC stubs, run the following command:
python -m grpc_tools.protoc -I proto --python_out=grpc_server/generated --grpc_python_out=grpc_server/generated proto/uml_service.protoRunning the servers
gRPC server
To run the gRPC server, run the following command:
python -m grpc_server.serverMCP server
The MCP (Model-Context-Protocol) server exposes the generate_uml tool, allowing other processes to generate UML diagrams. To run the MCP server, use the following command:
python -m mcp_server.serverCLI usage
To use the CLI, run the following command:
python -m cli.main --mode [domain_json|free_text] --input <file or "-"> --class --sequence --outdir ./outTesting
To run the tests, run the following command:
pytest -q