MWAA MCP Server
Related Servers
Alternatives to MWAA 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.1633 PyPI2Apache 2.0
- AlicenseAqualityBmaintenanceMCP server for Amazon MWAA that enables managing Airflow environments, DAGs, runs, task instances, and configurations through natural language, using secure AWS-native API access and read-only by default.21Apache 2.0
- FlicenseNot gradedqualityDmaintenanceEnables DAG management, monitoring, debugging, and connection testing for Apache Airflow through the MCP protocol.-
- AlicenseNot gradedqualityNot gradedmaintenanceAn MCP server that wraps the Apache Airflow REST API, enabling clients to manage DAGs, monitor task instances, and handle workflows through a standardized interface. It provides comprehensive access to Airflow features including DAG runs, variables, connections, and XComs.MIT
- AlicenseCqualityFmaintenanceEnables AI assistants to manage Amazon SageMaker AI resources including endpoints, jobs, pipelines, MLflow tracking servers, domains, models, model cards, and apps.574Apache 2.0
- AlicenseNot gradedqualityDmaintenanceEnables interaction with Apache Airflow through the Model Context Protocol, allowing users to manage DAGs, task instances, variables, connections, pools, XComs, and datasets.MIT
TDQS
Scored across 21 tools
Most tools have distinct purposes targeting specific MWAA/Airflow resources (environments, DAGs, tasks, connections, variables), but there is some overlap between airflow_best_practices and dag_design_guidance as both provide guidance rather than operational actions. The descriptions help differentiate them, but an agent might initially confuse these two guidance tools.
Tool names follow a consistent verb_noun pattern throughout (e.g., create_environment, list_dags, get_dag_run, update_environment). All tools use snake_case with clear action-object naming, making the set predictable and easy to navigate.
With 21 tools, the count is slightly high but reasonable for the comprehensive MWAA management scope, covering environment lifecycle, DAG operations, task monitoring, and system components. It might feel heavy, but each tool serves a specific function in this domain.
The toolset provides complete coverage for MWAA management, including environment CRUD (create, get, update, delete), DAG operations (list, get, trigger, source), task monitoring (instances, logs), and auxiliary functions (connections, variables, tokens, guidance). No obvious gaps exist for core workflows.