uc-mcp-gen 0.1.1

Generate Databricks App MCP servers from OpenAPI specs

uc-mcp-gen

A CLI that compiles an OpenAPI spec directly into a self-contained Databricks App bundle — a runnable MCP server with one concrete Python function per API operation. Auth and routing are handled by a Databricks Unity Catalog connection.

How It Works

1. Point uc-mcp-gen generate at an OpenAPI spec (local file or URL, YAML or JSON)
2. Provide a UC connection name
3. Get a self-contained Databricks App bundle back — ready to deploy with databricks bundle deploy

The generated main.py has zero dependency on uc_mcp_gen. It's a plain FastMCP server where every API operation becomes a typed async def tool function, with all HTTP calls proxied through your UC connection.

Install

# Run without installing (recommended)
uvx uc-mcp-gen generate ...

# Or install locally for development
uv sync

Usage

uc-mcp-gen generate <spec> --connection <conn-name> [--name <service-name>] [-o <output-dir>]

Arguments:

Argument	Description
spec	Path or URL to OpenAPI spec (.yaml, .yml, .json, or remote URL)
--connection	UC connection name in your Databricks workspace
--name	Service name (kebab-case). Derived from spec title if omitted.
-o / --output	Output directory. Defaults to generated_mcp_servers/<name>-app.

Examples:

# From a local YAML spec
uc-mcp-gen generate openapi.yaml --connection my-slack-conn -o ./slack-app

# From a local JSON spec
uc-mcp-gen generate openapi.json --connection my-api-conn

# From a remote spec
uc-mcp-gen generate https://api.example.com/openapi.yaml --connection my-conn -o ./example-app

Generated Bundle

<output>/
├── databricks.yml           Databricks Asset Bundle manifest
├── app.yaml                 App startup config — sets UC_CONNECTION_NAME
├── pyproject.toml           App dependencies (mcp, databricks-sdk, starlette, uvicorn)
└── src/app/
    ├── __init__.py
    └── main.py              Self-contained FastMCP server

Deploy with:

cd <output>
databricks bundle deploy
databricks bundle run

Auth

The generated main.py handles three auth scenarios automatically:

Scenario	Mechanism
Databricks Apps (user-facing)	X-Forwarded-Access-Token header → per-user WorkspaceClient
Databricks Model Serving	Model Serving credentials context
Service principal / local dev	Default WorkspaceClient() from environment

All tool calls are routed through client.serving_endpoints.http_request(conn=CONNECTION_NAME, ...) — your UC connection handles the downstream API auth.

Running Tests

uv run pytest -v