In-depth architectural comparison of the MCP Airflow and MCP Databricks Server MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.
At a Glance & Executive Verdict
MCP Airflow
Data Platforms · Local stdio
Quality: 53/100 (Good) | Auth: other
MCP Databricks Server
Data Platforms · Local stdio
Quality: 35/100 (Fair) | Auth: API Key required
Verdict Summary: Choose MCP Airflow if you need specialized Data Platforms tools running via a local process. Choose MCP Databricks Server if your workspace requires Data Platforms integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.
Which MCP Server Should You Choose?
Choose MCP Airflow when:
You need dedicated capabilities in the Data Platforms domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: other (Free / Open Source).
You have access to required keys: AIRFLOW_BASE_URL, AIRFLOW_USERNAME, AIRFLOW_PASSWORD.
Manage Apache Airflow through its REST API — list DAGs, inspect DAG runs and task instances, trigger runs, and check failed-DAG and scheduler/metadatabase health. 7 tools, built with FastMCP. Install: uvx mcp-airflow.
Connect to Databricks API, allowing LLMs to run SQL queries, list jobs, and get job status.
Category & Scope
Tools & Capabilities Breakdown
MCP Airflow Tools (7)
list_dags
List all DAGs with paused/active status
get_dag_runs_today
Get all DAG runs from today with status
get_dag_run_status
Get the latest run status for a specific DAG
trigger_dag_run
Trigger a manual DAG run
get_task_instances
Get task instances for a specific DAG run
check_failed_dags
Check for failed DAGs in the last 24 hours
Ready-to-Paste Client Configurations
Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).
MCP Airflow is categorized under Data Platforms and uses a local stdio subprocess. In contrast, MCP Databricks Server belongs to Data Platforms using local stdio subprocess. Select MCP Airflow when you need capabilities focused on data platforms and MCP Databricks Server when you require tools for data platforms.