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igorolv

jdbc-mcp-server

listKnownKinds

listKnownKinds
Read-onlyIdempotent

Discover valid source-kind values and their query counts for use in listQueries filters across JDBC databases.

Instructions

Discover valid usage-catalog source-kind values and their query counts for reuse in listQueries filters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
connectionYesDatabase to run against. Call listConnections for valid names; do not guess.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindsNoKnown source-kind values and their usage counts.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds useful context by mentioning query counts and the usage-catalog source, but it does not disclose potential caveats like cache freshness or open-world value variability, which would have added more value.

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, front-loaded sentence with no filler. Every phrase earns its place: what is discovered, what is included, and why the result matters.

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

Completeness5/5

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

For a one-parameter, read-only tool with a rich output schema and strong annotations, the description is complete. The agent knows when to call it, what it returns, and how the result should be used.

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 100% and the single connection parameter is well documented, including guidance to call listConnections for valid names. The description itself does not add new parameter-level meaning, but the schema already carries the full burden.

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 uses a specific verb ('Discover') with a specific resource ('valid usage-catalog source-kind values and their query counts') and states the intended downstream use ('for reuse in listQueries filters'). This clearly differentiates it from sibling tools like listKnownDomains, listKnownTags, and listQueries.

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 clearly indicates when to use this tool: when valid source-kind values are needed for listQueries filters. It provides clear context but does not explicitly name alternatives or state when not to use it, so it stops short of the strongest guidance.

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