Skip to main content
Glama
Sign In
mcp-data-agent

mcp-data-agent

by prudhvikollads-source
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Local

describe_table

Retrieve a database table's schema—column names, data types, nullability, and primary key—to understand its structure before querying.

Instructions

Describe one table: column names, types, nullability, primary key.

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
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose the output fields, which is the key behavioral fact. However, it says nothing about error behavior for a nonexistent table, permission requirements, or whether the table name must be schema-qualified.

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?

A single front-loaded sentence with zero filler; every clause adds information about what is returned.

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 needn't be restated, and the description is adequate for a simple one-parameter metadata read. The remaining gap is argument format and failure behavior for unknown tables.

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 0% for the single 'table' parameter, so the description must compensate. It only implies the argument is one table identifier and gives no format guidance (e.g., schema-qualified vs bare name, quoting).

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?

States a specific verb ('Describe') and resource ('one table'), and enumerates the returned metadata (column names, types, nullability, primary key). The 'one table' scope implicitly separates it from list_tables, but no sibling is named explicitly.

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?

No explicit when-to-use or when-not-to-use guidance, and no mention of alternatives like list_tables or run_query. Usage is only implied by the nature of a schema-inspection tool.

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

Deploy Server

Other Tools