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Superset MCP Integration

by aptro

superset_database_get_function_names

Retrieve all SQL function names supported by a specific database in Apache Superset to understand available query capabilities and ensure compatible SQL operations.

Instructions

Get function names supported by a database

Makes a request to the /api/v1/database/{id}/function_names/ endpoint to retrieve all SQL functions supported by the database.

Args: database_id: ID of the database

Returns: A dictionary with list of supported function names

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
database_idYes

Implementation Reference

  • Handler function decorated with @mcp.tool() that implements the tool by making an authenticated GET request to Superset API endpoint /api/v1/database/{database_id}/function_names/ using the shared make_api_request helper.
    @mcp.tool()
    @requires_auth
    @handle_api_errors
    async def superset_database_get_function_names(
        ctx: Context, database_id: int
    ) -> Dict[str, Any]:
        """
        Get function names supported by a database
    
        Makes a request to the /api/v1/database/{id}/function_names/ endpoint to retrieve
        all SQL functions supported by the database.
    
        Args:
            database_id: ID of the database
    
        Returns:
            A dictionary with list of supported function names
        """
        return await make_api_request(
            ctx, "get", f"/api/v1/database/{database_id}/function_names/"
        )
  • main.py:994-994 (registration)
    The @mcp.tool() decorator registers this function as an MCP tool.
    @mcp.tool()
  • Shared helper function used by the tool to make authenticated API requests to Superset, handling token refresh, CSRF, and error handling.
    async def make_api_request(
        ctx: Context,
        method: str,
        endpoint: str,
        data: Dict[str, Any] = None,
        params: Dict[str, Any] = None,
        auto_refresh: bool = True,
    ) -> Dict[str, Any]:
        """
        Helper function to make API requests to Superset
    
        Args:
            ctx: MCP context
            method: HTTP method (get, post, put, delete)
            endpoint: API endpoint (without base URL)
            data: Optional JSON payload for POST/PUT requests
            params: Optional query parameters
            auto_refresh: Whether to auto-refresh token on 401
        """
        superset_ctx: SupersetContext = ctx.request_context.lifespan_context
        client = superset_ctx.client
    
        # For non-GET requests, make sure we have a CSRF token
        if method.lower() != "get" and not superset_ctx.csrf_token:
            await get_csrf_token(ctx)
    
        async def make_request() -> httpx.Response:
            headers = {}
    
            # Add CSRF token for non-GET requests
            if method.lower() != "get" and superset_ctx.csrf_token:
                headers["X-CSRFToken"] = superset_ctx.csrf_token
    
            if method.lower() == "get":
                return await client.get(endpoint, params=params)
            elif method.lower() == "post":
                return await client.post(
                    endpoint, json=data, params=params, headers=headers
                )
            elif method.lower() == "put":
                return await client.put(endpoint, json=data, headers=headers)
            elif method.lower() == "delete":
                return await client.delete(endpoint, headers=headers)
            else:
                raise ValueError(f"Unsupported HTTP method: {method}")
    
        # Use auto_refresh if requested
        response = (
            await with_auto_refresh(ctx, make_request)
            if auto_refresh
            else await make_request()
        )
    
        if response.status_code not in [200, 201]:
            return {
                "error": f"API request failed: {response.status_code} - {response.text}"
            }
    
        return response.json()
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions making an API request but doesn't describe authentication requirements, rate limits, error conditions, or what happens if the database ID is invalid. For a read operation with zero annotation coverage, this leaves significant behavioral gaps.

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 with four sentences that are front-loaded (purpose first, then implementation details, then parameter and return value documentation). The Args/Returns structure is clear, though slightly redundant with the opening sentence.

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 moderate complexity (single parameter, read-only operation), no annotations, and no output schema, the description is minimally adequate. It covers the basic purpose and parameter but lacks behavioral context and usage guidance that would make it complete for effective agent use.

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 for the single parameter 'database_id' by explaining it's 'ID of the database' and that the tool retrieves functions 'supported by the database.' With 0% schema description coverage, this compensates well for the schema's lack of parameter documentation, though it doesn't specify format constraints (e.g., integer type).

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 tool's purpose with a specific verb ('Get') and resource ('function names supported by a database'), and distinguishes it from siblings like superset_database_get_tables or superset_database_get_catalogs by focusing specifically on SQL functions rather than other database metadata.

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 a valid database ID), typical use cases, or how it differs from related database metadata tools in the sibling list.

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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