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tibero-mcp

tibero-mcp

by jdk1021
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

describe_table

Read-only

Inspect a table’s columns, types, nullability, defaults, comments, keys, foreign keys, and indexes to understand its structure before querying or modifying data.

Instructions

Show a table's columns (type, nullability, default, comment), keys, foreign keys and indexes.

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
tableYesTable or view name, optionally qualified as SCHEMA.TABLE.
schemaNoSchema (owner). Defaults to the connected user.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds the scope of metadata retrieved, but says nothing about error behavior for a missing table or whether output is truncated for very wide tables.

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 sentence with zero filler, and the payload contents are front-loaded so the agent learns the return scope immediately.

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 need no further explanation, and both parameters are fully documented. The only shortfall is absent guidance on when this tool is preferable to siblings such as search_columns.

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 coverage is 100%, and the schema already explains both 'table' (with SCHEMA.TABLE qualification) and 'schema' (defaults to connected user). The description adds no meaning beyond that, so the baseline of 3 applies.

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 description uses a specific verb ('Show') with a concrete resource ('a table's') and enumerates exactly what it exposes: columns with type/nullability/default/comment, keys, foreign keys, and indexes. An agent knows precisely what this returns, though it does not explicitly contrast with siblings like search_columns or list_tables.

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?

There is no when-to-use guidance, no prerequisite (e.g. table must exist, view support), and no named alternative such as search_columns for locating a column across tables. Usage must be inferred entirely from the tool name and the sibling list.

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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