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Superset MCP Integration

by aptro

superset_sqllab_get_saved_queries

Retrieve saved SQL queries from Superset SQL Lab to access and manage previously created database queries for analysis.

Instructions

Get a list of saved queries from SQL Lab

Makes a request to the /api/v1/saved_query/ endpoint to retrieve all saved queries the current user has access to. Results are paginated.

Returns: A dictionary containing saved query information including id, label, and database

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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 of behavioral disclosure. It adds useful context: it specifies the API endpoint ('/api/v1/saved_query/'), mentions pagination, and notes access is limited to 'the current user has access to'. However, it doesn't cover critical aspects like authentication requirements, rate limits, error handling, or what 'access' entails (e.g., permissions). This is a moderate but incomplete effort.

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 well-structured and concise, with three sentences that each add value: stating the purpose, detailing the request and pagination, and describing the return format. There's no wasted text, and it's front-loaded with the core function. A minor deduction for slightly verbose phrasing like 'Makes a request to...' instead of a more direct statement.

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 complexity (a read operation with no parameters) and no annotations or output schema, the description is adequate but has gaps. It explains what the tool does, the endpoint, pagination, and return content, but lacks details on authentication, error cases, or pagination mechanics (e.g., how to navigate pages). This makes it minimally viable but not fully comprehensive.

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, and schema description coverage is 100% (though the schema is empty). The description doesn't need to explain parameters, so it appropriately focuses on behavior. It doesn't add param info beyond the schema, but with no parameters, this is acceptable, warranting a baseline score above 3.

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 saved queries from SQL Lab.' It specifies the verb ('Get'), resource ('saved queries'), and scope ('from SQL Lab'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'superset_query_list' or 'superset_saved_query_get_by_id', which 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 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 mentions that results are paginated and the current user's access, but doesn't specify prerequisites, exclusions, or compare it to similar tools like 'superset_saved_query_get_by_id' or 'superset_query_list'. This leaves the agent without clear usage context.

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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