postgres-mcp-server

get_object_details

Retrieve detailed information about a database table, view, or sequence including columns, data types, constraints, indexes, size, and row count. Use this to understand table structure before writing queries.

Instructions

Get detailed info about a table/view/sequence: columns, data types, constraints, indexes, size, row count. Use this to understand table structure before writing queries. Optionally use server/database/targetSchema params for one-time execution on a different server.

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": {
      "schema": "<schema>",
      "objectName": "<objectName>"
    },
    "name": "get_object_details"
  }
}

Input Schema

Name	Required	Description
`schema`	Yes	Schema name containing the object
`objectName`	Yes	Name of the table, view, or sequence
`objectType`	No	Object type (auto-detected if not specified)
`server`	No	One-time server override. Execute on this server without changing main connection.
`database`	No	One-time database override. Uses this database for execution.
`targetSchema`	No	One-time schema override. Sets search_path for this execution only.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv3.0.3May 30, 2026

TDQS

A4.2/5.0

Behavior3/5

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

No annotations were provided, so the description carries full burden. It describes the operation as retrieving info but does not explicitly state it is read-only, non-destructive, or free of side effects. It lacks details on authorization or rate limits.

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?

Two concise sentences: first states purpose and outputs, second adds optional usage. No redundancy, efficiently front-loaded.

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?

Given no output schema, the description lists key return categories (columns, data types, constraints, indexes, size, row count) but does not specify the exact structure. This is largely sufficient for an agent to understand the tool's value.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description adds value by explaining the one-time override parameters ('Optionally use server/database/targetSchema params for one-time execution on a different server'), reinforcing the schema descriptions.

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 action ('Get detailed info') and the resources ('table/view/sequence'), listing specific outputs (columns, data types, constraints, etc.). It distinguishes from siblings like 'describe_table' by implying a more comprehensive analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly advises 'Use this to understand table structure before writing queries,' providing clear context for when to use. It also mentions optional overrides for one-time execution but does not explicitly exclude alternatives like 'describe_table'.

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