A
licenseNot graded
qualityD
maintenanceProvides integration with Apache Airflow's REST API, allowing AI assistants to programmatically interact with Airflow workflows, monitor DAG runs, and manage tasks.
MIT
airflow-mcp-server
by ssasuoirafen
Related Servers
Alternatives to airflow-mcp-server
No user-submitted related servers found.
Related Servers
- AlicenseAqualityAmaintenanceEnables inspection and management of Apache Airflow DAGs, runs, and logs across multiple instances. It provides tools for monitoring workflows and performing gated write operations like triggering DAGs or clearing task instances.162Apache 2.0
- AlicenseAqualityBmaintenanceMCP server exposing Apache Airflow REST API operations as tools — list DAGs, inspect runs and task instances, trigger DAG runs, and check failed DAGs and scheduler health72MIT
- AlicenseNot gradedqualityDmaintenanceEnables natural language interaction with Apache Airflow for querying DAGs, monitoring execution, and troubleshooting failures.1MIT
- AlicenseCqualityCmaintenanceProvides a standardized way for MCP clients to interact with Apache Airflow's REST API, supporting operations like DAG management and monitoring Airflow system health.68177MIT
astro-airflow-mcpofficial
AlicenseAqualityFmaintenanceAn MCP server that enables AI assistants to interact with Apache Airflow's REST API for DAG management, task monitoring, and system diagnostics. It provides comprehensive tools for triggering workflows, retrieving logs, and inspecting system health across Airflow 2.x and 3.x versions.3113Apache 2.0
TDQS
A3.9/5.0
Scored across 14 tools
Disambiguation5/5
Each tool has a clearly distinct purpose. For example, 'get_dag' retrieves a single DAG, while 'list_dags' lists multiple; 'clear_task_instances' resets tasks, distinct from 'trigger_dag_run'. No overlapping functionality.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., 'get_dag', 'list_pools', 'set_dag_paused'). Verbs like 'get' for single entities, 'list' for collections, 'clear', 'set', and 'trigger' are used uniformly.
Tool Count5/5
14 tools is well-scoped for an Airflow MCP server. Core operations for DAGs, runs, task instances, pools, health, and version are covered without bloat or excessive specialization.
Completeness4/5
The toolset covers the main lifecycle for DAGs (list, get, pause, trigger), runs, and task instances (list, get, clear, logs). However, it lacks management operations for pools (only list), DAG run deletion, and advanced task retry options, leaving minor gaps for some workflows.
Maintenance
ActivityMaintained
ResponsivenessNo issues