Metadata-Version: 2.4
Name: mseep-mcp-server-apache-airflow
Version: 0.2.2
Summary: Model Context Protocol (MCP) server for Apache Airflow
Project-URL: Homepage, https://github.com/yangkyeongmo/mcp-server-apache-airflow
Project-URL: Repository, https://github.com/yangkyeongmo/mcp-server-apache-airflow.git
Project-URL: Bug Tracker, https://github.com/yangkyeongmo/mcp-server-apache-airflow/issues
Author-email: Gyeongmo Yang <me@gmyang.dev>
License: MIT
License-File: LICENSE
Keywords: airflow,apache-airflow,mcp,model-context-protocol
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.10
Requires-Dist: apache-airflow-client>=2.7.0
Requires-Dist: click>=8.1.7
Requires-Dist: httpx>=0.24.1
Requires-Dist: mcp>=0.1.0
Provides-Extra: dev
Requires-Dist: build>=1.2.2.post1; extra == 'dev'
Requires-Dist: twine>=6.1.0; extra == 'dev'
Description-Content-Type: text/markdown

# mcp-server-apache-airflow
[![smithery badge](https://smithery.ai/badge/@yangkyeongmo/mcp-server-apache-airflow)](https://smithery.ai/server/@yangkyeongmo/mcp-server-apache-airflow)

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.

<a href="https://glama.ai/mcp/servers/e99b6vx9lw">
  <img width="380" height="200" src="https://glama.ai/mcp/servers/e99b6vx9lw/badge" alt="Server for Apache Airflow MCP server" />
</a>

## About

This project implements a [Model Context Protocol](https://modelcontextprotocol.io/introduction) 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.

## Feature Implementation Status

| Feature | API Path | Status |
|---------|----------|--------|
| **DAG Management** | | |
| List DAGs | `/api/v1/dags` | ✅ |
| Get DAG Details | `/api/v1/dags/{dag_id}` | ✅ |
| Pause DAG | `/api/v1/dags/{dag_id}` | ✅ |
| Unpause DAG | `/api/v1/dags/{dag_id}` | ✅ |
| Update DAG | `/api/v1/dags/{dag_id}` | ✅ |
| Delete DAG | `/api/v1/dags/{dag_id}` | ✅ |
| Get DAG Source | `/api/v1/dagSources/{file_token}` | ✅ |
| Patch Multiple DAGs | `/api/v1/dags` | ✅ |
| Reparse DAG File | `/api/v1/dagSources/{file_token}/reparse` | ✅ |
| **DAG Runs** | | |
| List DAG Runs | `/api/v1/dags/{dag_id}/dagRuns` | ✅ |
| Create DAG Run | `/api/v1/dags/{dag_id}/dagRuns` | ✅ |
| Get DAG Run Details | `/api/v1/dags/{dag_id}/dagRuns/{dag_run_id}` | ✅ |
| Update DAG Run | `/api/v1/dags/{dag_id}/dagRuns/{dag_run_id}` | ✅ |
| Delete DAG Run | `/api/v1/dags/{dag_id}/dagRuns/{dag_run_id}` | ✅ |
| Get DAG Runs Batch | `/api/v1/dags/~/dagRuns/list` | ✅ |
| Clear DAG Run | `/api/v1/dags/{dag_id}/dagRuns/{dag_run_id}/clear` | ✅ |
| Set DAG Run Note | `/api/v1/dags/{dag_id}/dagRuns/{dag_run_id}/setNote` | ✅ |
| Get Upstream Dataset Events | `/api/v1/dags/{dag_id}/dagRuns/{dag_run_id}/upstreamDatasetEvents` | ✅ |
| **Tasks** | | |
| List DAG Tasks | `/api/v1/dags/{dag_id}/tasks` | ✅ |
| Get Task Details | `/api/v1/dags/{dag_id}/tasks/{task_id}` | ✅ |
| Get Task Instance | `/api/v1/dags/{dag_id}/dagRuns/{dag_run_id}/taskInstances/{task_id}` | ✅ |
| List Task Instances | `/api/v1/dags/{dag_id}/dagRuns/{dag_run_id}/taskInstances` | ✅ |
| Update Task Instance | `/api/v1/dags/{dag_id}/dagRuns/{dag_run_id}/taskInstances/{task_id}` | ✅ |
| Clear Task Instances | `/api/v1/dags/{dag_id}/clearTaskInstances` | ✅ |
| Set Task Instances State | `/api/v1/dags/{dag_id}/updateTaskInstancesState` | ✅ |
| **Variables** | | |
| List Variables | `/api/v1/variables` | ✅ |
| Create Variable | `/api/v1/variables` | ✅ |
| Get Variable | `/api/v1/variables/{variable_key}` | ✅ |
| Update Variable | `/api/v1/variables/{variable_key}` | ✅ |
| Delete Variable | `/api/v1/variables/{variable_key}` | ✅ |
| **Connections** | | |
| List Connections | `/api/v1/connections` | ✅ |
| Create Connection | `/api/v1/connections` | ✅ |
| Get Connection | `/api/v1/connections/{connection_id}` | ✅ |
| Update Connection | `/api/v1/connections/{connection_id}` | ✅ |
| Delete Connection | `/api/v1/connections/{connection_id}` | ✅ |
| Test Connection | `/api/v1/connections/test` | ✅ |
| **Pools** | | |
| List Pools | `/api/v1/pools` | ✅ |
| Create Pool | `/api/v1/pools` | ✅ |
| Get Pool | `/api/v1/pools/{pool_name}` | ✅ |
| Update Pool | `/api/v1/pools/{pool_name}` | ✅ |
| Delete Pool | `/api/v1/pools/{pool_name}` | ✅ |
| **XComs** | | |
| List XComs | `/api/v1/dags/{dag_id}/dagRuns/{dag_run_id}/taskInstances/{task_id}/xcomEntries` | ✅ |
| Get XCom Entry | `/api/v1/dags/{dag_id}/dagRuns/{dag_run_id}/taskInstances/{task_id}/xcomEntries/{xcom_key}` | ✅ |
| **Datasets** | | |
| List Datasets | `/api/v1/datasets` | ✅ |
| Get Dataset | `/api/v1/datasets/{uri}` | ✅ |
| Get Dataset Events | `/api/v1/datasetEvents` | ✅ |
| Create Dataset Event | `/api/v1/datasetEvents` | ✅ |
| Get DAG Dataset Queued Event | `/api/v1/dags/{dag_id}/dagRuns/queued/datasetEvents/{uri}` | ✅ |
| Get DAG Dataset Queued Events | `/api/v1/dags/{dag_id}/dagRuns/queued/datasetEvents` | ✅ |
| Delete DAG Dataset Queued Event | `/api/v1/dags/{dag_id}/dagRuns/queued/datasetEvents/{uri}` | ✅ |
| Delete DAG Dataset Queued Events | `/api/v1/dags/{dag_id}/dagRuns/queued/datasetEvents` | ✅ |
| Get Dataset Queued Events | `/api/v1/datasets/{uri}/dagRuns/queued/datasetEvents` | ✅ |
| Delete Dataset Queued Events | `/api/v1/datasets/{uri}/dagRuns/queued/datasetEvents` | ✅ |
| **Monitoring** | | |
| Get Health | `/api/v1/health` | ✅ |
| **DAG Stats** | | |
| Get DAG Stats | `/api/v1/dags/statistics` | ✅ |
| **Config** | | |
| Get Config | `/api/v1/config` | ✅ |
| **Plugins** | | |
| Get Plugins | `/api/v1/plugins` | ✅ |
| **Providers** | | |
| List Providers | `/api/v1/providers` | ✅ |
| **Event Logs** | | |
| List Event Logs | `/api/v1/eventLogs` | ✅ |
| Get Event Log | `/api/v1/eventLogs/{event_log_id}` | ✅ |
| **System** | | |
| Get Import Errors | `/api/v1/importErrors` | ✅ |
| Get Import Error Details | `/api/v1/importErrors/{import_error_id}` | ✅ |
| Get Health Status | `/api/v1/health` | ✅ |
| Get Version | `/api/v1/version` | ✅ |

## Setup

### Dependencies

This project depends on the official Apache Airflow client library (`apache-airflow-client`). It will be automatically installed when you install this package.

### Environment Variables

Set the following environment variables:
```
AIRFLOW_HOST=<your-airflow-host>
AIRFLOW_USERNAME=<your-airflow-username>
AIRFLOW_PASSWORD=<your-airflow-password>
```

### Usage with Claude Desktop

Add to your `claude_desktop_config.json`:

```json
{
  "mcpServers": {
    "mcp-server-apache-airflow": {
      "command": "uvx",
      "args": ["mcp-server-apache-airflow"],
      "env": {
        "AIRFLOW_HOST": "https://your-airflow-host",
        "AIRFLOW_USERNAME": "your-username",
        "AIRFLOW_PASSWORD": "your-password"
      }
    }
  }
}
```

Alternative configuration using `uv`:

```json
{
  "mcpServers": {
    "mcp-server-apache-airflow": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/mcp-server-apache-airflow",
        "run",
        "mcp-server-apache-airflow"
      ],
      "env": {
        "AIRFLOW_HOST": "https://your-airflow-host",
        "AIRFLOW_USERNAME": "your-username",
        "AIRFLOW_PASSWORD": "your-password"
      }
    }
  }
}
```

Replace `/path/to/mcp-server-apache-airflow` with the actual path where you've cloned the repository.

### Selecting the API groups

You can select the API groups you want to use by setting the `--apis` flag.

```bash
uv run mcp-server-apache-airflow --apis "dag,dagrun"
```

The default is to use all APIs.

Allowed values are:

- config
- connections
- dag
- dagrun
- dagstats
- dataset
- eventlog
- importerror
- monitoring
- plugin
- pool
- provider
- taskinstance
- variable
- xcom

### Manual Execution

You can also run the server manually:
```bash
make run
```

`make run` accepts following options:

Options:
- `--port`: Port to listen on for SSE (default: 8000)
- `--transport`: Transport type (stdio/sse, default: stdio)

Or, you could run the sse server directly, which accepts same parameters:
```bash
make run-sse
```

### Installing via Smithery

To install Apache Airflow MCP Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@yangkyeongmo/mcp-server-apache-airflow):

```bash
npx -y @smithery/cli install @yangkyeongmo/mcp-server-apache-airflow --client claude
```

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## License

[MIT License](LICENSE)
