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@takeokunn/metabase-mcp

@takeokunn/metabase-mcp

by takeokunn
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

extract_tables_from_sql

Extract table references from SQL queries using AI to automatically identify which database tables are referenced.

Instructions

[Requires Metabase Pro] Extract table references from a SQL query using AI

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": "extract_tables_from_sql"
  }
}

Input Schema

NameRequiredDescriptionDefault
inputYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description must bear full burden. It mentions AI usage but does not disclose reliability, performance, or potential side effects of the extraction. The description lacks detail on what 'extract table references' entails behaviorally.

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 a single sentence that conveys the core purpose concisely. It front-loads the requirement and uses no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has nested parameters and no output schema, yet the description does not explain the output format, how template_tags work, or how the AI extraction behaves. More detail is needed for a complex tool.

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?

The input schema properties have descriptions (100% coverage), so the schema already explains the parameters. The main description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.

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 tool extracts table references from a SQL query using AI, with a specific verb and resource. It also notes the requirement for Metabase Pro. This distinguishes it from sibling tools like execute_query or generate_sql.

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 mentions 'Requires Metabase Pro' as a condition but does not provide guidance on when to use this tool versus alternatives, nor does it explain when not to use it.

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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