IRIS MCP Blueprint

describe_table

Retrieve column names and data types for a specified table in an InterSystems IRIS database.

Instructions

Show columns and types for a table. Args: ctx: The context of the tool call. table_name: The name of the table to describe. table_schema: The schema of the table to describe.

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_name": "<table_name>"
    },
    "name": "describe_table"
  }
}

Input Schema

Name	Required	Description	Default
`table_name`	Yes
`table_schema`	No		SQLUser

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.4Jun 12, 2026

TDQS

C2.9/5.0

Behavior2/5

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

Without annotations, the description carries full burden for behavioral disclosure. It does not mention whether the operation is read-only (though implied), nor does it discuss error handling, permissions, or performance implications. The description only states what the tool does, not its side effects or constraints.

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 concise and front-loaded with the primary purpose. The 'Args' section is slightly redundant but adds clarity for parameter semantics. Every sentence contributes meaning without excess.

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?

Given the presence of an output schema, the description does not need to detail return values. However, it lacks contextual details such as behavior for non-existent tables, schema resolution, or interaction with permissions. For a simple read tool, this is adequate but not complete.

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?

The description provides parameter explanations ('The name of the table...', 'The schema of the table...'), which add meaning beyond the bare schema (which has 0% coverage). However, it does not explain the default value of 'table_schema' or any constraints on the parameters, leaving some gaps.

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 states 'Show columns and types for a table', which is a clear verb-resource combination. It effectively distinguishes from siblings like 'get_tables' (which lists tables) and 'fetch_data' (which retrieves rows). However, it could be slightly more explicit about the output being metadata.

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 guidance is provided on when to use this tool versus alternatives, such as 'fetch_data' for actual data retrieval or 'get_tables' for table listing. There is no mention of prerequisites (e.g., table existence) or exclusion scenarios.

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