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Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

An MCP server that generates, edits, and manages BPMN 2.0 diagrams from natural language descriptions, with an interactive viewer and persistent storage.

README.md

appkit-bpmn-server

An MCP Apps-compliant server that generates, edits, and manages BPMN 2.0 diagrams from natural language — powered by LLMs.

Describe a business process in plain text and get a valid, layouted BPMN diagram with an interactive viewer rendered inline in any MCP Apps-capable host (Claude, ChatGPT, VS Code, etc.).

!Screenshot

Features

  • Natural language to BPMN — Generate process diagrams from text descriptions
  • Interactive viewer — Built-in bpmn-js editor with zoom, pan, and editing capabilities
  • Update diagrams — Modify existing diagrams via follow-up prompts without starting over
  • Persistent storage — SQLite-backed diagram storage with Alembic migrations
  • User assignment — Associate diagrams with specific users via x-user-id header or query parameter (defaults to -1)
  • Auto-layout — Automatic swimlane arrangement and edge routing
  • Validation — Generated BPMN XML is validated before storage
  • MCP Apps UI — Inline rendering in any compliant chat host

Architecture

MCP Host (Claude, ChatGPT, …)
  │
  │  MCP over HTTP (stateless)
  ▼
appkit-bpmn-server      ← this repo (configuration + startup)
  │
  ├─ appkit-mcp-bpmn    ← MCP tools, viewer, BPMN generation
  ├─ appkit-commons     ← shared config, OpenAI client, registry
  └─ SQLite database    ← diagram persistence

Prerequisites

  • Python 3.14+
  • uv package manager
  • An OpenAI-compatible API key (Azure OpenAI or OpenAI)

Getting Started

1. Clone and install

git clone https://github.com/jenreh/appkit-bpmn-server.git
cd appkit-bpmn-server
uv sync

2. Configure environment

Create a .env file in the project root:

OPENAI_API_KEY=your-api-key
OPENAI_BASE_URL=https://your-endpoint.openai.azure.com/v1

3. Run database migrations

uv run alembic upgrade head

4. Start the server

uv run appkit_bpmn_server

The MCP endpoint will be available at http://127.0.0.1:8000/mcp.

5. Connect from an MCP client

Add the server to your MCP client configuration:

{
  "mcpServers": {
    "bpmn": {
      "url": "http://127.0.0.1:8000/mcp"
    }
  }
}

MCP Tools

| Tool | Description | | --- | --- | | new_bpmn_diagram | Generate a new BPMN diagram from a natural language description | | update_bpmn_diagram | Modify an existing diagram using a follow-up prompt | | save_bpmn_diagram | Save pre-built BPMN XML | | get_bpmn_xml | Retrieve the BPMN XML for a diagram (app-only) | | save_or_update | Persist edits made in the viewer (app-only) | | rename_bpmn_diagram | Rename a diagram (app-only) |

Tools marked app-only are hidden from the model and callable only from the interactive viewer.

Configuration

Server settings are in configuration/config.yaml:

app:
  mcp_bpmn:
    storage_mode: database          # database, filesystem, or both
    default_model: gpt-5.3-codex    # LLM model for generation
    max_file_size_mb: 10
    diagram_types:
      - process

User Assignment

Diagrams can be associated with a specific user by sending an x-user-id value. This can be provided as:

  • HTTP header: x-user-id: 123
  • Query parameter: ?x-user-id=123

If neither is provided, the user ID defaults to -1.

Project Structure

├── configuration/
│   ├── config.yaml          # Development configuration
│   ├── config.prod.yaml     # Production overrides
│   └── logging.yaml         # Logging configuration
├── alembic/                 # Database migrations
├── src/
│   └── appkit_bpmn_server/
│       └── main.py          # Server entry point
├── pyproject.toml
└── .env                     # API keys (not committed)

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