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airflow-dev-mcp

by BrianLondon

airflow-dev-mcp

An MCP server that lets an AI coding assistant (Claude Code, Cursor, and other MCP clients) drive a development or local Airflow cluster through Airflow's REST API. It can trigger DAG runs, watch their status, read task logs, and diagnose parse errors.

It talks to Airflow over HTTP only. There's no dependency on your Airflow source tree, no filesystem or database access, and no local config files. All configuration is set through environment variables. It support both Airflow 3 (via /api/v2, the default) and Airflow 2 (/api/v1).

Airflow-dev-mcp is designed for the write-a-DAG / run-it / read-the-logs loop against a development and/or local environment. Pointing it at a production cluster is not recommended.

Install & run

The package ships a single console command, airflow-dev-mcp, which starts the MCP server on stdio. Installation requires uv.

_Note: most users will skip this and just add it to their coding environment (See: below)

To download and validate the package, run:

uvx airflow-dev-mcp --check      # fetch + run a one-shot connectivity check

It can be installed as a persistent tool but typical installation is to just have your coding agent call it through uvx (See: Configure your MCP client below). If you do want to install it system wide, use one of the two following commands

uv tool install airflow-dev-mcp
# or
pipx install airflow-dev-mcp

Related MCP server: astro-airflow-mcp

Configure your MCP client

Claude Code

The easiest way is the claude mcp add CLI, which writes the config to the correct place for you. From your project directory:

claude mcp add airflow-dev \
  -e AIRFLOW_URL=http://localhost:8080 \
  -e AIRFLOW_USERNAME=admin \
  -e AIRFLOW_PASSWORD=admin \
  -- uvx airflow-dev-mcp

Add --scope user to make it available in every project, or --scope project to write a checked-in .mcp.json you can commit for your team (the default scope is local to you in the current project).

To configure it by hand instead, create a .mcp.json file in the project root — this is the file Claude Code reads for project-scoped MCP servers.

{
  "mcpServers": {
    "airflow-dev": {
      "command": "uvx",
      "args": ["airflow-dev-mcp"],
      "env": {
        "AIRFLOW_URL": "http://localhost:8080",
        "AIRFLOW_USERNAME": "admin",
        "AIRFLOW_PASSWORD": "admin"
      }
    }
  }
}

For a user-global setup, put the same mcpServers block in ~/.claude.json instead.

Other MCP clients

Any client that launches stdio MCP servers works the same way: run the command airflow-dev-mcp (or uvx airflow-dev-mcp) with the environment variables below.

Configuration

All configuration is via environment variables:

Variable

Default

Description

AIRFLOW_URL

http://localhost:8080

Base URL of the cluster, no path.

AIRFLOW_API_PREFIX

/api/v2

API path prefix. Use /api/v1 for Airflow 2.x.

AIRFLOW_USERNAME

Username. Used together with AIRFLOW_PASSWORD.

AIRFLOW_PASSWORD

Password.

AIRFLOW_TOKEN

Explicit bearer token; skips username/password entirely.

AIRFLOW_AUTH_MODE

auto

auto, jwt, or basic (see below).

AIRFLOW_TOKEN_ENDPOINT

/auth/token

Path used to exchange credentials for a JWT.

AIRFLOW_TIMEOUT

30

HTTP timeout, in seconds.

AIRFLOW_VERIFY_SSL

true

Set false to skip TLS verification (self-signed dev certs).

Authentication

  • Airflow 3.x (the default local/MWAA-style image): leave AIRFLOW_AUTH_MODE=auto. The server posts your username/password to /auth/token, caches the returned JWT, and sends it as a bearer token on every request.

  • Airflow 2.x: set AIRFLOW_API_PREFIX=/api/v1 and AIRFLOW_AUTH_MODE=basic (2.x uses HTTP basic auth against the REST API).

  • Pre-issued token: set AIRFLOW_TOKEN and omit the username/password.

Tools

Tool

What it does

trigger_dag

Start a manual DAG run, optionally with a conf payload. Returns the dag_run_id.

get_run_status

State of a run plus per-task states (task, state, try number, operator, timing).

get_task_logs

Logs for one task attempt, tailed to the last N lines by default.

list_dag_runs

Recent runs of a DAG — find a run when you don't already have its id.

clear_task_instances

Clear tasks so they re-run. Defaults to a dry-run preview.

list_dags

Registered DAGs with their paused / import-error / active flags.

get_import_errors

Parse failures with filename and traceback — why a new DAG isn't showing up.

set_dag_paused

Pause or unpause a DAG (new local DAGs start paused).

list_variables

Read Airflow Variables (read-only).

list_connections

Read Airflow Connections, minus passwords (read-only).

The four list_* tools, get_run_status, get_task_logs, and get_import_errors are strictly read-only. trigger_dag, set_dag_paused, and clear_task_instances change cluster state. There are deliberately no tools that create or modify Variables or Connections.

License

MIT — see LICENSE.

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maintenance

Maintenance

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Release cycle
1Releases (12mo)
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