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aptro

Superset MCP Integration

by aptro
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

superset_query_list

Retrieve query history from Apache Superset to monitor SQL execution status, duration, and results through paginated API requests.

Instructions

Get a list of queries from Superset

Makes a request to the /api/v1/query/ endpoint to retrieve query history. Results are paginated and include both finished and running queries.

Returns: A dictionary containing query information including status, duration, and SQL

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • main.py:1416-1429 (handler)
    The handler function for the 'superset_query_list' tool. It is decorated with @mcp.tool() for registration, @requires_auth for authentication check, and @handle_api_errors for error handling. The function makes a GET request to Superset's /api/v1/query/ endpoint via the make_api_request helper to list queries.
    @requires_auth
@handle_api_errors
async def superset_query_list(ctx: Context) -> Dict[str, Any]:
    """
    Get a list of queries from Superset

    Makes a request to the /api/v1/query/ endpoint to retrieve query history.
    Results are paginated and include both finished and running queries.

    Returns:
        A dictionary containing query information including status, duration, and SQL
    """
    return await make_api_request(ctx, "get", "/api/v1/query/")

Tool Definition Quality

A3.9/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: it 'Makes a request to the /api/v1/query/ endpoint', results are 'paginated', and includes 'both finished and running queries'. This covers the operation type, endpoint, and result characteristics, though it doesn't mention authentication needs or rate limits.

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 well-structured and concise: it starts with the core purpose, explains the request and pagination, and ends with return details. Every sentence adds value without redundancy, and it's front-loaded with the main action.

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 output schema, no annotations), the description is reasonably complete. It explains what the tool does, how it behaves (paginated, includes all query states), and what it returns. However, it could be more complete by mentioning authentication requirements or error handling.

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 tool has 0 parameters with 100% schema description coverage, so the schema fully documents the absence of inputs. The description doesn't need to add parameter details, and it appropriately focuses on behavior and output. A baseline of 4 is applied for zero parameters.

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 tool's purpose: 'Get a list of queries from Superset' with the specific verb 'Get' and resource 'queries'. It distinguishes from siblings like 'superset_query_get_by_id' (single query) and 'superset_sqllab_get_saved_queries' (saved vs. history), but doesn't explicitly mention these distinctions in the text.

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 context by mentioning it retrieves 'query history' including 'both finished and running queries', which suggests when to use it (for historical tracking). However, it doesn't provide explicit guidance on when to choose this over alternatives like 'superset_sqllab_get_saved_queries' or 'superset_activity_get_recent'.

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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