https://github.com/yangkyeongmo/mcp-server-apache-airflow

Last synced: 7 months ago
JSON representation

Host: GitHub
URL: https://github.com/yangkyeongmo/mcp-server-apache-airflow
Owner: yangkyeongmo
License: mit
Created: 2025-02-13T04:09:06.000Z (8 months ago)
Default Branch: main
Last Pushed: 2025-03-20T13:35:07.000Z (7 months ago)
Last Synced: 2025-03-20T14:25:33.547Z (7 months ago)
Language: Python
Homepage: https://pypi.org/project/mcp-server-apache-airflow/
Size: 222 KB
Stars: 3
Watchers: 1
Forks: 3
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE
- Codeowners: .github/CODEOWNERS

Awesome Lists containing this project

awesome-mcp-list - @yangkyeongmo/mcp-server-apache-airflow - server-apache-airflow?style=social)](https://github.com/yangkyeongmo/mcp-server-apache-airflow): Connects to Apache Airflow using the official client. (Uncategorized / Uncategorized)
awesome-mcp-servers - **mcp-server-apache-airflow** - Python-based (actively maintained) `python` `http` `ai` `git` `github` `pip install git+https://github.com/yangkyeongmo/mcp-server-apache-airflow` (AI/ML)
awesome-mcp-servers - **mcp-server-apache-airflow** - Python-based (actively maintained) `python` `http` `ai` `git` `github` `pip install git+https://github.com/yangkyeongmo/mcp-server-apache-airflow` (AI/ML)
best-of-mcp-servers - GitHub - 40% open · ⏱️ 13.09.2025) (Developer Tools)
awesome-mcp-servers - @yangkyeongmo@/mcp-server-apache-airflow - MCP server that connects to [Apache Airflow](https://airflow.apache.org/) using official client. (Legend / 💻 <a name="developer-tools"></a>Developer Tools)
Awesome-MCP-Servers-directory - Airflow - A MCP Server that connects to Apache Airflow using official python client (Workflow Automation)
awesome-mcp-servers - Airflow MCP Server - Provides a Model Context Protocol (MCP) server for standardized Apache Airflow interaction (Table of Contents / System Automation)
awesome-mcp-servers - Airflow MCP Server - Provides a Model Context Protocol (MCP) server for standardized Apache Airflow interaction (Table of Contents / System Automation)
mcp-index - Apache Airflow MCP Server - Integrates Apache Airflow's REST API with the Model Context Protocol, enabling MCP clients to interact with Airflow tasks and workflows effectively. Facilitates standardized communication between AI models and Apache Airflow for job orchestration. (Business Tools)
awesome-mcp-servers - @yangkyeongmo@/mcp-server-apache-airflow - MCP server that connects to [Apache Airflow](https://airflow.apache.org/) using official client. (Legend / 💻 <a name="developer-tools"></a>Developer Tools)
awesome-mcp - @yangkyeongmo@/mcp-server-apache-airflow - MCP server that connects to [Apache Airflow](https://airflow.apache.org/) using official client. (MCP Servers / 💻 Developer Tools)

README

          # 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.



  



## 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=

AIRFLOW_USERNAME=

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)

ecosyste.ms

Data

Tools

Indexes

Applications

Experiments

Awesome

https://github.com/yangkyeongmo/mcp-server-apache-airflow

Awesome Lists containing this project

README