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@takeokunn/metabase-mcp

@takeokunn/metabase-mcp

by takeokunn
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

get_root_dashboard_question_candidates

Retrieve candidate questions from the root Metabase collection for dashboard creation, enabling discovery of available questions to add.

Instructions

Get dashboard question candidates from the root collection in Metabase

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "input": "<input>"
    },
    "name": "get_root_dashboard_question_candidates"
  }
}

Input Schema

NameRequiredDescriptionDefault
inputYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.0

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavior. It only states the action and resource, omitting details such as whether the operation is read-only, has any side effects, or performance implications. The description adds no value beyond the basic action.

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 a single short sentence, which is concise and front-loaded. It wastes no words, though slightly more detail could be added without loss of conciseness.

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 is a simple getter with no output schema and one empty input, the description is minimally adequate. However, it fails to specify return format or behavior when no candidates exist, leaving gaps in context for an AI agent.

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?

The input schema has 0% coverage (parameter 'input' is an empty object with no properties). The description does not explain what this parameter is for or how to use it, leaving the agent without guidance despite the single required parameter.

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 verb 'Get', the resource 'dashboard question candidates', and the scope 'from the root collection'. It distinguishes itself from the sibling 'get_collection_dashboard_question_candidates' which operates on a specific collection, making the purpose unambiguous.

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 for retrieving candidates from the root collection, but does not explicitly state when to prefer this over 'get_collection_dashboard_question_candidates' or other alternatives. No exclusions or prerequisites are mentioned, leaving the agent to infer usage context.

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

Deploy Server

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