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sepfazeli

clickhouse-mcp-server

by sepfazeli

Aggregate

aggregate
Read-only

Build time-windowed aggregation queries by specifying a table, metric column, aggregation function, and optional time column with interval for grouping. No raw SQL needed.

Instructions

Build and run a time-windowed aggregation query without writing raw SQL. Specify a table, metric column, aggregation function, and optional time column with interval for grouping.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableYesTable name to aggregate from.
metricYesColumn to aggregate (e.g. 'revenue', 'count').
funcYesAggregation function.
timeColumnNoDate/DateTime column to group by time window. Omit for a single aggregate.
intervalNoTime bucketing interval. Required if timeColumn is set.
filterNoOptional WHERE clause condition (without the WHERE keyword).
groupByNoOptional additional column to group by.
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. Description adds context that it runs a query without writing SQL, which aligns with safety profile. No contradictions.

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 sentences with front-loaded core purpose and no excess. Every sentence adds meaningful information.

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?

Covers main parameters (table, metric, func, timeColumn, interval) but omits filter and groupBy in description despite schema having descriptions. No output schema, so return format is unaddressed, which is a minor gap for a moderately complex tool.

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?

Schema coverage is 100%, so baseline is 3. Description adds value by explaining the usage pattern (specify table, metric, func, optional time column) and aggregation function enum clarity, though it mostly reiterates schema.

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?

Description clearly states it builds and runs a time-windowed aggregation query without raw SQL, with a specific verb and resource. It distinguishes from sibling tools like run_query which handles raw SQL.

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?

Explicitly states when to use (in-place aggregation) and explains required parameters. Does not explicitly mention when not to use or alternatives, but context (sibling tools) implies partial guidance.

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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