Skip to main content
Glama
aptro

Superset MCP Integration

by aptro

superset_database_get_catalogs

Retrieve all available catalogs from a specified database in Apache Superset to organize and access data structures for analysis.

Instructions

Get all catalogs from a database

Makes a request to the /api/v1/database/{id}/catalogs/ endpoint to retrieve all catalogs available in the database.

Args: database_id: ID of the database

Returns: A dictionary with list of catalog names for databases that support catalogs

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
database_idYes

Implementation Reference

  • main.py:948-969 (handler)
    The handler function decorated with @mcp.tool() that implements the superset_database_get_catalogs tool. It retrieves catalogs from a Superset database by calling the API endpoint /api/v1/database/{database_id}/catalogs/ using the make_api_request helper.
    @mcp.tool()
    @requires_auth
    @handle_api_errors
    async def superset_database_get_catalogs(
        ctx: Context, database_id: int
    ) -> Dict[str, Any]:
        """
        Get all catalogs from a database
    
        Makes a request to the /api/v1/database/{id}/catalogs/ endpoint to retrieve
        all catalogs available in the database.
    
        Args:
            database_id: ID of the database
    
        Returns:
            A dictionary with list of catalog names for databases that support catalogs
        """
        return await make_api_request(
            ctx, "get", f"/api/v1/database/{database_id}/catalogs/"
        )
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions the API endpoint but lacks critical behavioral details: it doesn't specify if this is a read-only operation, whether it requires authentication, potential rate limits, error conditions, or pagination. The description is minimal beyond the basic action, leaving gaps in understanding how the tool behaves.

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 three sentences: purpose, endpoint, and parameter/return details. It's front-loaded with the core action. However, the 'Args' and 'Returns' sections could be integrated more smoothly, and some sentences are slightly verbose (e.g., 'for databases that support catalogs'), keeping it from a perfect 5.

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 low complexity (1 parameter, no output schema, no annotations), the description is somewhat complete but has gaps. It covers the basic action and parameter but lacks behavioral context (e.g., safety, errors) and doesn't fully explain the return value beyond 'dictionary with list of catalog names'. For a simple read tool, this is adequate but minimal.

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

Parameters3/5

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

Schema description coverage is 0%, so the schema provides no parameter details. The description adds minimal value by stating 'database_id: ID of the database', which clarifies the parameter's purpose but doesn't explain format, constraints, or where to obtain it. This partial compensation justifies a baseline 3, as it addresses the parameter's role without full semantics.

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 'all catalogs from a database', making the purpose unambiguous. It distinguishes from siblings like 'superset_database_get_tables' by focusing on catalogs rather than tables or schemas. However, it doesn't explicitly differentiate from all database-related siblings, keeping it at 4 rather than 5.

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), nor does it compare with siblings like 'superset_database_schemas' or 'superset_database_get_tables' for related data retrieval. Usage is implied 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.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/aptro/superset-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server