Iceberg MCP Server (via Impala)

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get_schema

Lists tables in the current Impala database with their columns and types, so you can call it first and write queries using the exact column names returned.

Instructions

List the tables in the current Impala database with their columns (name and type). Call this first, and use the exact column names it returns.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_schema"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 11, 2026

TDQS

A3.9/5.0

Behavior3/5

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

No annotations are supplied, so the description carries the burden; it implies a read-only metadata lookup via "List" but never states permissions, cost, or whether the result is cached/scoped. The output schema exists, so the brief mention of returned column name/type is adequate but not additive beyond that schema.

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 short sentences with no filler; the purpose comes first and the call-ordering instruction is front-loaded in the second sentence. Every clause carries actionable information.

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?

For a zero-parameter introspection tool with an output schema, the description covers what it returns and how to use the result, which is what an agent needs to call it correctly. It could add a note on scope (all schemas vs. current only) or result size, but the essentials are present.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. The scoping phrase "current Impala database" usefully clarifies that no database argument is needed or accepted.

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 ("List") and resource ("tables in the current Impala database") and clarifies that column names and types are included. It doesn't explicitly contrast itself with the execute_query sibling, but the metadata-listing scope is unambiguous.

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?

"Call this first" gives a clear ordering rule that implicitly positions this tool ahead of execute_query, and "use the exact column names it returns" tells the agent how to consume the result. No explicit when-not condition is stated, which keeps it below a 5.

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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