sqldb-mcp-server

describeTable

Retrieve complete schema details for a table—columns, types, nullability, keys, indexes, foreign keys, constraints—along with size and row-count statistics.

Instructions

Describe a table: returns columns (name, type, nullability, primary key, identity), indexes, foreign keys, check constraints, and table-level size/row-count statistics.

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": "describeTable"
  }
}

Input Schema

Name	Required	Description	Default
`table`	Yes	Table name to describe. Optionally prefix with schema: 'schema.table'
`database`	No	Database containing the table; omit to use the default

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.3.0Sep 26, 2026

addedInput schema / properties / database

Added value: +{
+  "description": "Database containing the table; omit to use the default",
+  "minLength": 1,
+  "type": "string"
+}

First observedv0.1.1Jul 13, 2026

TDQS

A3.8/5.0

Behavior3/5

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

With no annotations, the description carries the behavioral disclosure burden. It states exactly what is returned and 'Describe' strongly implies a read-only metadata operation, but it does not explicitly confirm that no data is modified, nor does it mention permission, error, or performance behavior. This is adequate but leaves the safety profile implicit.

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 well-structured sentence with a front-loaded purpose and a concise list of return categories. It contains no redundant wording and each listed item earns its place.

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?

The tool has no output schema skill, so the description compensates by listing the major returned components: columns, indexes, foreign keys, check constraints, and table-level statistics. It is sufficient for an agent to invoke the tool, though it could add a brief note about behavior on missing tables or privilege requirements.

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?

Schema description coverage is 100%, and both parameters are already documented in the input schema, including the optional schema.table prefix. The tool description adds no additional parameter-level meaning, so the 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 opens with a specific verb and resource, 'Describe a table', and enumerates the returned metadata: columns, indexes, foreign keys, check constraints, and statistics. This clearly distinguishes the tool from sibling listTables, which would only list table names.

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 described output implies when to use the tool—when schema details such as columns, keys, and constraints are needed—but it does not explicitly state when not to use it or name alternatives like listTables for a simple table inventory. The usage context is inferable rather than specified.

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

Deploy Server