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CW-Codewalnut

Metabase MCP Server

get_metabase_current_user

Retrieve details of the currently authenticated Metabase user, including ID, email, and group memberships, for identity verification and access control.

Instructions

Get current logged-in user info from Metabase.

Returns: Dict[str, Any]: User details like id, email, groups, etc.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function for 'get_metabase_current_user' tool. This async function retrieves the current logged-in user info from Metabase by making a GET request to the '/api/user/current' endpoint. It takes no parameters and returns a Dict containing user details like id, email, groups, etc. The @mcp.tool() decorator registers it as an MCP tool.
    @mcp.tool()
    async def get_metabase_current_user() -> Dict[str, Any]:
        """
        Get current logged-in user info from Metabase.
    
        Returns:
            Dict[str, Any]: User details like id, email, groups, etc.
        """
        logger.info("Getting current user info")
        return await make_metabase_request(RequestMethod.GET, "/api/user/current")
  • The 'make_metabase_request' helper function that supports the tool handler. This async function makes HTTP requests to the Metabase API using aiohttp. It handles request construction, error handling, response parsing, and ensures responses are properly formatted as dictionaries for FastMCP compatibility. Used by the handler to make the actual GET request to '/api/user/current'.
    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 FastMCP instance initialization that enables tool registration. The 'mcp' object is created with the name 'metabase' and a lifespan manager, and is used to register tools via the @mcp.tool() decorator.
    mcp = FastMCP("metabase", lifespan=app_lifespan)
Behavior3/5

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

With no annotations provided, the description carries the full burden. It states the tool returns user details, which is helpful, but doesn't disclose behavioral traits like authentication requirements, rate limits, or error handling. It adds basic context about the return type but misses key operational details.

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

Conciseness5/5

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

The description is front-loaded with the core purpose in the first sentence, followed by a concise note on the return type. Both sentences add value without redundancy, making it efficiently structured and appropriately sized for the tool's simplicity.

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

Completeness4/5

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

Given the tool's low complexity (0 parameters, no annotations, but with an output schema), the description is reasonably complete. It explains what the tool does and the return format, though it could benefit from more behavioral context. The output schema reduces the need to detail return values, so gaps are minor.

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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the return value. This meets expectations for a parameterless tool, earning a high score.

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

Purpose4/5

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

The description clearly states the verb ('Get') and resource ('current logged-in user info from Metabase'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_metabase_users', which retrieves multiple users rather than the current one. This omission prevents a perfect score.

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

Usage Guidelines3/5

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

The description implies usage by mentioning 'current logged-in user', suggesting it's for retrieving the authenticated user's details. However, it lacks explicit guidance on when to use this versus alternatives like 'get_metabase_users' or prerequisites such as authentication context. This leaves room for ambiguity.

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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