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CW-Codewalnut

Metabase MCP Server

delete_metabase_dashboard

Remove a dashboard from Metabase to manage BI assets and maintain organized analytics workspaces by specifying the dashboard ID.

Instructions

Delete a dashboard from Metabase.

Args: dashboard_id (int): ID of the dashboard to delete.

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dashboard_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The delete_metabase_dashboard tool handler function. Decorated with @mcp.tool() to register it as an MCP tool. Takes a dashboard_id parameter and makes a DELETE request to the Metabase API endpoint /api/dashboard/{dashboard_id}. Returns a Dict[str, Any] with the deletion confirmation.
    @mcp.tool()
    async def delete_metabase_dashboard(dashboard_id: int) -> Dict[str, Any]:
        """
        Delete a dashboard from Metabase.
    
        Args:
            dashboard_id (int): ID of the dashboard to delete.
    
        Returns:
            Dict[str, Any]: Deletion confirmation.
        """
        logger.info(f"Deleting dashboard {dashboard_id}")
        return await make_metabase_request(RequestMethod.DELETE, f"/api/dashboard/{dashboard_id}")
  • Helper function that makes HTTP requests to the Metabase API. Used by delete_metabase_dashboard (and other tools) to communicate with Metabase. Handles request construction, error handling, connection errors, and response parsing. Returns Dict[str, Any] for FastMCP compatibility.
    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
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. While it mentions 'Delete' (implying a destructive operation) and 'Deletion confirmation' (hinting at a response), it lacks critical behavioral details such as whether deletion is permanent/irreversible, if it requires admin permissions, or if it affects dependent resources (e.g., cards on the dashboard).

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 appropriately sized and front-loaded with the core purpose in the first sentence. The Args/Returns sections are structured but slightly verbose for a single parameter; however, every sentence adds value without redundancy.

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 destructive nature, no annotations, and an output schema (which covers return values), the description is minimally adequate. It explains the action and parameter but lacks context on safety, permissions, or side effects, which is a significant gap for a deletion tool.

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?

With only 1 parameter and 0% schema description coverage, the description compensates well by clearly explaining 'dashboard_id (int): ID of the dashboard to delete.' This adds essential meaning beyond the schema's basic type information, though it doesn't specify format constraints (e.g., valid ID ranges).

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 dashboard from Metabase'), making the purpose immediately apparent. It distinguishes itself from sibling tools like 'get_dashboard_by_id' (read) and 'update_metabase_dashboard' (modify) by focusing on permanent removal.

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 the dashboard ID from a previous operation), exclusions (e.g., not for cards or collections), or related tools like 'delete_metabase_card' for similar operations on different resources.

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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