UML-MCP
@antoinebou12
UML-MCP Server is a UML diagram generation tool based on MCP (Model Context Protocol), which can help users generate various types of UML diagrams through natural language description or directly writing PlantUML and Mermaid and Kroki
Overview
What is UML-MCP?
UML-MCP is a diagram generation server that implements the Model Context Protocol (MCP), enabling AI assistants and other applications to create UML diagrams, Mermaid, D2, Graphviz, ERD, and more. It connects to rendering services like PlantUML and Kroki, making diagram creation seamless from supported clients.
How to use UML-MCP?
Install Python 3.10+, clone the repository, and run python mcp_server.py. Configure the server in Claude Desktop or Cursor via mcpServers JSON pointing to the script. Use the provided tools (e.g., generate_uml, generate_class_diagram) with parameters like diagram_type, code, and output_dir. Environment variables such as MCP_OUTPUT_DIR, KROKI_SERVER, and PLANTUML_SERVER control rendering services.
Key features of UML-MCP
- Supports UML, Mermaid, D2, Graphviz, ERD, and more diagram types
- Seamless MCP integration with AI assistants
- Direct playground links for online editing
- Multiple output formats: SVG, PNG, PDF, and others
- Simple configuration with local or remote rendering servers
Use cases of UML-MCP
- Generate UML class, sequence, or activity diagrams from AI chat prompts
- Create ERDs and BPMN diagrams for database or process documentation
- Automate diagram production for software documentation and reports
- Integrate diagram generation into IDEs like Cursor or Claude Desktop
FAQ from UML-MCP
What diagram types does UML-MCP support?
UML-MCP supports UML (Class, Sequence, Activity, Use Case, State, Component, Deployment, Object), Mermaid, D2, Graphviz, ERD, BlockDiag, BPMN, and C4 with PlantUML.
What are the runtime requirements?
Python 3.10 or higher and pip. Optionally, Docker for local PlantUML or Kroki servers.
How can I use local rendering servers?
Set USE_LOCAL_PLANTUML=true and PLANTUML_SERVER=http://localhost:8080 (or USE_LOCAL_KROKI=true and KROKI_SERVER=http://localhost:8000), then start the corresponding Docker containers.
What output formats are available?
SVG, PNG, PDF, and other formats depending on the diagram type and rendering engine.
How do I integrate UML-MCP with Cursor?
Run python mcp/install_to_cursor.py or manually add the server configuration in Cursor settings under mcpServers with the command and arguments pointing to mcp_server.py.
