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Chinook MCP Server

Chinook MCP Server

by arslanmunawar0
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

describe_table

Read-onlyIdempotent

Show a table's columns, primary key, foreign keys, and row count to understand its structure and relationships in a SQLite database.

Instructions

Show a table's columns, primary key, foreign keys and row count.

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": {
      "table": "<table>"
    },
    "name": "describe_table"
  }
}

Input Schema

NameRequiredDescriptionDefault
tableYes

Output Schema

NameRequiredDescriptionDefault
nameYes
columnsYes
row_countYes
foreign_keysYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true and openWorldHint=false, so the safety profile is covered. The description adds what information is surfaced (keys and row count), but says nothing about cost, latency, or behavior on a missing table, so credit is limited.

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?

One sentence, front-loaded with the verb and resource, listing only substantive output fields. Every word earns its place with no redundancy.

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?

An output schema exists, so return values need not be re-explained, and the annotations cover the safety profile. For a single-parameter read tool the description is nearly sufficient, with only parameter format and error behavior left unstated.

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 single 'table' parameter is documented nowhere in the schema. The description refers only to 'a table' and provides no format guidance (qualified name, quoting, case sensitivity), so it fails to compensate for the coverage gap.

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 gives a specific verb ('Show') and resource ('a table') and enumerates the exact output it produces (columns, primary key, foreign keys, row count), which cleanly distinguishes it from siblings like list_tables and sample_rows. It stops short of explicitly naming those alternatives, so it is clear but not sibling-differentiating.

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?

There is no statement of when to use this tool versus run_query, list_tables, or sample_rows, and no prerequisites or exclusions. The purpose is implied by the content list, but no routing guidance is given.

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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