A Model Context Protocol (MCP) server implementation for Apache Airflow, enabling seamless integration with MCP clients. This project provides a
A Model Context Protocol (MCP) server implementation for Apache Airflow, enabling seamless integration with MCP clients. This project provides a standardized way to interact with Apache Airflow through the Model Context Protocol. The apache airflow mcp server wraps that behind the Model Context Protocol, so an assistant can use it through 9 defined tools rather than through you.
This project implements a Model Context Protocol server that wraps Apache Airflow's REST API, allowing MCP clients to interact with Airflow in a standardized way. It uses the official Apache Airflow client library to ensure compatibility and maintainability.
@smithery/cli on npm is all you need. Most clients run it directly, so configuration is a few lines and a restart.
Everything the assistant can do here goes through one of these:
config — connectionsdag — dagrundagstats — dataseteventlog — importerrormonitoring — pluginpool — providertaskinstance — variableDependencies — This project depends on the official Apache Airflow client library (apache-airflow-client). It will be automatically installed when you install thisAuthentication — To obtain a JWT token, you can use Airflow's authentication endpoint:You will need 6 environment variables: AIRFLOW_HOST, AIRFLOW_USERNAME, AIRFLOW_PASSWORD, AIRFLOW_JWT_TOKEN, READ_ONLY, ENDPOINT_URL. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
This sits in the monitoring and observability group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Apache Airflow's toolset — config, dag, dagstats and 6 more — is a fair guide to whether it matches your workflow. It is maintained by yangkyeongmo; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
| Tool | What it does |
|---|---|
| config | connections |
| dag | dagrun |
| dagstats | dataset |
| eventlog | importerror |
| monitoring | plugin |
| pool | provider |
| taskinstance | variable |
| Dependencies | This project depends on the official Apache Airflow client library (apache-airflow-client). It will be automatically installed when you install this package. |
| Authentication | To obtain a JWT token, you can use Airflow's authentication endpoint: |
**JWT Token Authentication:**
```json
{
"mcpServers": {
"mcp-server-apache-airflow": {
"command": "uvx",
"args": ["mcp-server-apache-airflow"],
"env": {
"AIRFLOW_HOST": "https://your-airflow-host",
"AIRFLOW_JWT_TOKEN": "your-jwt-token"
}
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| AIRFLOW_HOST | Endpoint or connection string the server talks to. | Optional |
| AIRFLOW_USERNAME | Configuration value read at startup. | Optional |
| AIRFLOW_PASSWORD | Configuration value read at startup. | Optional |
| AIRFLOW_JWT_TOKEN | Credential the server authenticates with. | Yes |
| READ_ONLY | Configuration value read at startup. | Optional |
| ENDPOINT_URL | Endpoint or connection string the server talks to. | Yes |
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