superset-mcp

list_datasets

Retrieve datasets from Apache Superset to explore available data tables for analysis and visualization.

Instructions

List datasets (virtual or physical tables).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_datasets"
  }
}

Input Schema

Name	Required	Description	Default
`page`	No
`page_size`	No
`search`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Apr 14, 2026

TDQS

C2.6/5.0

Behavior2/5

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

With no annotations provided, the description carries full burden but only states the action without behavioral details. It doesn't disclose if this is read-only, paginated, requires authentication, has rate limits, or what the output entails, leaving significant gaps in understanding tool behavior.

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 very concise with a single sentence that is front-loaded and to the point. However, it could be more structured by including key details like pagination or search functionality, though it avoids unnecessary verbosity.

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 has an output schema, the description doesn't need to explain return values, but it lacks context for a list operation with parameters. With no annotations and low schema coverage, it's minimally adequate but incomplete for guiding effective use, especially compared to siblings.

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

Parameters2/5

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

Schema description coverage is 0%, and the description adds no parameter information beyond what the schema provides. It doesn't explain the meaning of 'page', 'page_size', or 'search' parameters, failing to compensate for the low coverage and leaving parameters undocumented.

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

Purpose3/5

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

The description states the action ('List') and resource ('datasets'), specifying they can be 'virtual or physical tables', which clarifies scope. However, it doesn't differentiate from siblings like 'list_tables' or 'get_dataset', making the purpose somewhat vague in context.

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?

No guidance is provided on when to use this tool versus alternatives such as 'list_tables' or 'get_dataset'. The description lacks context about use cases, prerequisites, or exclusions, offering only basic functional information.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.