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peakacom

peaka-mcp-server

Official
by peakacom

peaka_get_query

Read-only

Retrieve a saved query by its ID to view its full definition, including the SQL, query type, display name, and auto-refresh schedule for materialized queries.

Instructions

Read a single saved query by its ID. Returns the full query object including displayName, inputQuery (SQL), queryType, and the auto-refresh schedule for materialized queries.

If you do not already know the projectId for the current task, call peaka_list_projects first and ask the user which project to use. Remember the chosen projectId for subsequent calls in this conversation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryIdYesThe query ID to read. Available from peaka_list_queries.
projectIdYesThe Peaka project ID to run against.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.11.0

TDQS

A4.3/5.0
Behavior4/5

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

The readOnlyHint and destructiveHint annotations already signal a safe read operation, and the description adds useful behavioral detail by naming the exact returned object fields and the special auto-refresh schedule for materialized queries. It does not cover error or not-found behavior, but this is less critical for a read tool with strong annotation coverage.

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?

The description is concise and front-loaded: the first sentence states the operation and return value, and the second gives a short, necessary workflow hint. Every sentence contributes useful information with no filler or repetition.

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 simple read-by-ID operation, the description fully covers what the tool returns, identifies both required parameters, and resolves the likely projectId prerequisite by directing the agent to peaka_list_projects. No crucial invocation information is missing.

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%, so both parameters are already documented. The description adds workflow context around projectId but does not add much semantic meaning beyond the schema. A baseline of 3 is appropriate because the schema carries the parameter documentation 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-resource pair ('Read a single saved query by its ID') and explicitly lists the returned fields, including SQL, query type, and refresh schedule. This clearly differentiates it from listing, executing, or status-oriented sibling tools.

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 gives concrete pre-usage guidance: call peaka_list_projects first if the projectId is unknown, ask the user which project to use, and retain that projectId for later calls. It does not explicitly mention when-not-to-use this tool versus alternatives, but the read-only purpose and schema-referenced peaka_list_queries provide clear context.

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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