Skip to main content
Glama
jovian-zhibai

mcp-database

get_table_info

Retrieve a table's columns, data types, and row count to quickly understand its structure in any connected database.

Instructions

Get detailed information about a table: columns, types, row count.

Args: table: Table name. database: Name of the database within the connection (optional). connection_name: Name of the database connection (default: "default").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableYes
databaseNo
connection_nameNodefault

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the full burden; 'Get' makes the read-only nature reasonably clear and enumerates what information is returned. It does not mention error behavior, permissions, cost of row-count computation, or whether information is current, so behavioral transparency is only partial.

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

Conciseness4/5

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

The description is short and front-loaded with the core purpose before the Args block. The Args repetition is compact though it partly duplicates schema metadata, preventing a 5.

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

Completeness3/5

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

For a simple read tool with an output schema, the basics are present: required table, optional database, default connection. However, there is no usage context, no sibling differentiation, and no caveats, so an agent selecting among 13 siblings is under-supported.

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%, but the Args section gives each parameter a one-line meaning, so the description compensates minimally. The comments are largely tautological (table → 'Table name') and add little beyond the schema titles/defaults, but they do clarify that database is optional and connection_name has a default.

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 first sentence names a specific verb ('Get') and resource ('a table') and enumerates concrete output ('columns, types, row count'). However, it does not explicitly distinguish itself from the sibling get_schema, so an agent may need to inspect schemas to see the difference.

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?

No statement about when to prefer this tool over siblings such as get_schema, list_tables, or sample_rows, and no exclusions or alternatives. The only contextual hints are optional database/connection arguments, which are parameter-level rather than usage guidance.

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