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CW-Codewalnut

Metabase MCP Server

delete_metabase_database

Remove a database connection from Metabase by specifying its ID to manage BI platform data sources.

Instructions

Delete a database connection from Metabase.

Args: database_id (int): ID of the database to delete.

Returns: Dict[str, Any]: Deletion confirmation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
database_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The delete_metabase_database tool handler that executes the deletion logic. It takes a database_id parameter and makes a DELETE request to the Metabase API endpoint /api/database/{database_id}.
    @mcp.tool()
    async def delete_metabase_database(database_id: int) -> Dict[str, Any]:
        """
        Delete a database connection from Metabase.
    
        Args:
            database_id (int): ID of the database to delete.
    
        Returns:
            Dict[str, Any]: Deletion confirmation.
        """
        logger.info(f"Deleting database {database_id}")
        return await make_metabase_request(RequestMethod.DELETE, f"/api/database/{database_id}")
  • The @mcp.tool() decorator registers the delete_metabase_database function as an MCP tool, making it available for invocation through the Model Context Protocol.
    @mcp.tool()
  • The make_metabase_request helper function that handles all HTTP requests to the Metabase API. It manages sessions, error handling, and response parsing for the delete_metabase_database tool and other tools.
    async def make_metabase_request(
        method: RequestMethod,
        endpoint: str,
        data: Optional[Dict[str, Any] | bytes] = None,
        params: Optional[Dict[str, Any]] = None,
        json: Any = None,
        headers: Optional[Dict[str, str]] = None,
    ) -> Dict[str, Any]:
        """
        Make a request to the Metabase API.
        
        Args:
            method: HTTP method to use (GET, POST, PUT, DELETE)
            endpoint: API endpoint path
            data: Request data (for form data)
            params: URL parameters
            json: JSON request body
            headers: Additional headers
            
        Returns:
            Dict[str, Any]: Response data
            
        Raises:
            MetabaseConnectionError: When the Metabase server is unreachable
            MetabaseResponseError: When Metabase returns a non-2xx status code
            RuntimeError: For other errors
        """
        
        if not METABASE_URL or not METABASE_API_KEY:
            raise RuntimeError("METABASE_URL or METABASE_API_KEY environment variable is not set. Metabase API requests will fail.")
    
        if session is None:
            raise RuntimeError("HTTP session is not initialized. Ensure app_lifespan was called.")
    
        try:
            request_headers = headers or {}
            
            logger.debug(f"Making {method.name} request to {METABASE_URL}{endpoint}")
            
            # Log request payload for debugging (omit sensitive info)
            if json and logger.level <= logging.DEBUG:
                sanitized_json = {**json}
                if 'password' in sanitized_json:
                    sanitized_json['password'] = '********'
                logger.debug(f"Request payload: {sanitized_json}")
                
            response = await session.request(
                method=method.name,
                url=endpoint,
                timeout=aiohttp.ClientTimeout(total=30),
                headers=request_headers,
                data=data,
                params=params,
                json=json,
            )
    
            try:
                # Handle 500 errors with more detailed info
                if response.status >= 500:
                    error_text = await response.text()
                    logger.error(f"Server error {response.status}: {error_text[:200]}")
                    raise MetabaseResponseError(response.status, f"Server Error: {error_text[:200]}", endpoint)
                
                response.raise_for_status()
                response_data = await response.json()
                
                # Ensure the response is a dictionary for FastMCP compatibility
                return ensure_dict_response(response_data)
                
            except aiohttp.ContentTypeError:
                # Handle empty responses or non-JSON responses
                content = await response.text()
                if not content:
                    return {"data": {}}
                logger.warning(f"Received non-JSON response: {content}")
                return {"data": content}
    
        except aiohttp.ClientConnectionError as e:
            logger.error(f"Connection error: {str(e)}")
            raise MetabaseConnectionError("Metabase is unreachable. Is the Metabase server running?") from e
        except aiohttp.ClientResponseError as e:
            logger.error(f"Response error: {e.status}, {e.message}, {e.request_info.url}")
            raise MetabaseResponseError(e.status, e.message, str(e.request_info.url)) from e
        except Exception as e:
            logger.error(f"Request error: {str(e)}")
            raise RuntimeError(f"Request error: {str(e)}") from e
  • The RequestMethod enum defines HTTP methods (GET, POST, PUT, DELETE) used by the make_metabase_request helper function. The delete_metabase_database tool uses RequestMethod.DELETE.
    class RequestMethod(Enum):
        GET = auto()
        POST = auto()
        PUT = auto()
        DELETE = auto()
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool deletes a database connection and returns a confirmation, but lacks critical details: whether deletion is permanent/reversible, required permissions, side effects (e.g., impact on dependent dashboards/cards), or error handling. For a destructive operation with zero annotation coverage, this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and appropriately sized, with a clear purpose statement followed by Args and Returns sections. Every sentence adds value: the first defines the action, and the others document parameters and return type. It could be slightly more concise by integrating the Args/Returns into a single sentence, but it's efficient overall.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (destructive operation), lack of annotations, and presence of an output schema (which covers return values), the description is partially complete. It covers the basic purpose and parameters but misses behavioral context like safety warnings or dependencies. For a delete tool, more detail on consequences would improve completeness, but the output schema helps mitigate gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds meaningful context beyond the input schema. The schema only indicates 'database_id' is an integer, but the description clarifies it's 'ID of the database to delete', specifying its purpose. With 0% schema description coverage and only 1 parameter, this adequately compensates, though it could note format constraints (e.g., where to find the ID).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Delete') and resource ('a database connection from Metabase'), distinguishing it from sibling tools like 'delete_metabase_card' or 'delete_metabase_dashboard' which target different resources. It precisely identifies what the tool does without being vague or tautological.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing database), exclusions (e.g., not for read-only operations), or comparisons to siblings like 'get_metabase_databases' for listing databases. Usage is implied by the name but not explicitly stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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