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get_config_section

Retrieve all configuration options from a specific section in Apache Airflow, enabling users to inspect and manage cluster settings without API complexity.

Instructions

[Tool Role]: Gets all options within a specific configuration section.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
section_nameYes

Implementation Reference

  • The core handler function for the 'get_config_section' tool. It retrieves a specific section from Airflow's configuration by making an API request to /config and extracting the requested section.
    @mcp.tool()
    async def get_config_section(section_name: str) -> Dict[str, Any]:
        """[Tool Role]: Gets all options within a specific configuration section."""
        try:
            resp = await airflow_request("GET", "/config")
            resp.raise_for_status()
            config_data = resp.json()
            
            section_data = config_data.get("sections", {}).get(section_name)
            if not section_data:
                return {"error": f"Section '{section_name}' not found"}
            
            return {
                "section_name": section_name,
                "options": section_data.get("options", {}),
                "options_count": len(section_data.get("options", {}))
            }
        except Exception as e:
            return {
                "error": f"Configuration access denied: {str(e)}",
                "note": "This requires 'expose_config = True' in airflow.cfg [webserver] section"
            }
  • Registration entry point for v1 API tools. Sets the v1-specific airflow_request function and calls register_common_tools(mcp), which registers the get_config_section tool among others.
    def register_tools(mcp):
        """Register v1 tools by importing common tools with v1 request function."""
        
        logger.info("Initializing MCP server for Airflow API v1")
        logger.info("Loading Airflow API v1 tools (Airflow 2.x)")
        
        # Set the global request function to v1
        common_tools.airflow_request = airflow_request_v1
        
        # Register all 56 common tools (includes management tools)
        common_tools.register_common_tools(mcp)
        
        # V1 has no exclusive tools - all tools are shared with v2
        
        logger.info("Registered all Airflow API v1 tools (56 tools: 43 core + 13 management tools)")
  • Registration entry point for v2 API tools. Sets the v2-specific airflow_request function and calls register_common_tools(mcp), which registers the get_config_section tool among others.
    def register_tools(mcp):
        """Register v2 tools: common tools + v2-exclusive asset tools."""
        
        logger.info("Initializing MCP server for Airflow API v2")
        logger.info("Loading Airflow API v2 tools (Airflow 3.0+)")
        
        # Set the global request function to v2
        common_tools.airflow_request = airflow_request_v2
        
        # Register all 43 common tools
        common_tools.register_common_tools(mcp)
        
        # Add V2-exclusive tools (2 tools)
        @mcp.tool()
        async def list_assets(limit: int = 20, offset: int = 0,
                             uri_pattern: Optional[str] = None) -> Dict[str, Any]:
            """
            [V2 New] List all assets in the system for data-aware scheduling.
            
            Assets are a key feature in Airflow 3.0 for data-aware scheduling.
            They enable workflows to be triggered by data changes rather than time schedules.
            
            Args:
                limit: Maximum number of assets to return (default: 20)
                offset: Number of assets to skip for pagination (default: 0)
                uri_pattern: Filter assets by URI pattern (optional)
                
            Returns:
                Dict containing assets list, pagination info, and metadata
            """
            params = {'limit': limit, 'offset': offset}
            if uri_pattern:
                params['uri_pattern'] = uri_pattern
                
            query_string = "&".join([f"{k}={v}" for k, v in params.items()])
            
            resp = await airflow_request_v2("GET", f"/assets?{query_string}")
            resp.raise_for_status()
            data = resp.json()
            
            return {
                "assets": data.get("assets", []),
                "total_entries": data.get("total_entries", 0),
                "limit": limit,
                "offset": offset,
                "api_version": "v2",
                "feature": "assets"
            }
    
        @mcp.tool()
        async def list_asset_events(limit: int = 20, offset: int = 0,
                                   asset_uri: Optional[str] = None,
                                   source_dag_id: Optional[str] = None) -> Dict[str, Any]:
            """
            [V2 New] List asset events for data lineage tracking.
            
            Asset events track when assets are created or updated by DAGs.
            This enables data lineage tracking and data-aware scheduling in Airflow 3.0.
            
            Args:
                limit: Maximum number of events to return (default: 20)
                offset: Number of events to skip for pagination (default: 0)
                asset_uri: Filter events by specific asset URI (optional)
                source_dag_id: Filter events by source DAG that produced the event (optional)
                
            Returns:
                Dict containing asset events list, pagination info, and metadata
            """
            params = {'limit': limit, 'offset': offset}
            if asset_uri:
                params['asset_uri'] = asset_uri
            if source_dag_id:
                params['source_dag_id'] = source_dag_id
                
            query_string = "&".join([f"{k}={v}" for k, v in params.items()])
            
            resp = await airflow_request_v2("GET", f"/assets/events?{query_string}")
            resp.raise_for_status()
            data = resp.json()
            
            return {
                "asset_events": data.get("asset_events", []),
                "total_entries": data.get("total_entries", 0),
                "limit": limit,
                "offset": offset,
                "api_version": "v2",
                "feature": "asset_events"
            }
    
        logger.info("Registered all Airflow API v2 tools (43 common + 2 assets + 4 management = 49 tools)")

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