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sql-query-mcp

sql-query-mcp

by andyWang1688
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

describe_table

Get a detailed description of a table's columns, keys, and indexes to understand its structure.

Instructions

Describe columns, keys, and indexes for a table.

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": {
      "connection_id": "<connection_id>",
      "table_name": "<table_name>"
    },
    "name": "describe_table"
  }
}

Input Schema

NameRequiredDescriptionDefault
schemaNo
databaseNo
table_nameYes
connection_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.3.0
  2. Removedv0.1.2
  3. First observedv0.1.3

TDQS

B3.1/5.0
Behavior3/5

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

No annotations are present, so the description carries full burden. It implies a read-only metadata retrieval but does not explicitly state safety, permissions, or rate limits. While 'describe' suggests non-destructive, the lack of explicit transparency justifies a moderate score.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single 7-word sentence, which is concise but under-specified. It front-loads the purpose but omits necessary context for parameters and usage. It could be expanded without losing conciseness.

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?

With 4 parameters (2 required), no output schema, and no annotations, the description is too brief to be complete. It does not explain return values, parameter roles, or usage context, leaving significant gaps for an agent to properly invoke the tool.

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% (no parameter descriptions). The description does not explain the meaning or usage of parameters like 'connection_id', 'table_name', 'schema', or 'database'. It fails to compensate for the schema gap, offering no parameter semantics.

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's purpose: describing columns, keys, and indexes for a table. It uses a specific verb 'describe' and resource 'table', which distinctively sets it apart from siblings like 'list_tables' (list tables) and 'get_table_sample' (fetch data).

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 does not mention prerequisites (e.g., connection_id, table_name) or scenarios where it is inappropriate. No comparison with siblings like 'list_tables' or 'get_table_sample'.

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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