jdbc-mcp-server

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columnHistogram

columnHistogram

Read-onlyIdempotent

Measure percentile distribution for a numeric, date, timestamp, or text column, including min/max, percentiles (P25-P99), and null counts to understand data spread.

Instructions

Measure percentile distribution for one orderable numeric, date, timestamp or text column: min/max, P25/P50/P75/P90/P95/P99 and null counts. Use columnDistribution for top frequent values instead.

Input Schema

TableJSON Schema

Name	Required	Description
`table`	Yes
`column`	Yes
`schema`	No
`connection`	Yes	Database to run against. Call listConnections for valid names; do not guess.

Output Schema

TableJSON Schema

Name	Required	Description
`max`	No	Maximum observed non-null column value.
`min`	No	Minimum observed non-null column value.
`p25`	No	25th percentile value for the column.
`p50`	No	Median, or 50th percentile, value for the column.
`p75`	No	75th percentile value for the column.
`p90`	No	90th percentile value for the column.
`p95`	No	95th percentile value for the column.
`p99`	No	99th percentile value for the column.
`table`	No
`column`	No	Column whose percentile distribution was measured.
`schema`	No
`nullRows`	Yes	Number of rows where the column value is NULL.
`nullRatio`	Yes	Share of rows where the column value is NULL, from 0.0 to 1.0.
`totalRows`	Yes	Total number of rows considered for this statistic.
`columnType`	No	Database type of the column used to choose percentile behavior.
`nonNullRows`	Yes	Number of rows where the column value is not NULL.
`percentileFunction`	No	Database percentile function used, such as continuous or discrete percentile.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 15, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the safety profile is covered. The description adds meaningful behavioral context beyond annotations: the accepted column types (numeric, date, timestamp, text), the requirement that the column be orderable, and the precise set of statistics returned including null counts.

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 two sentences with no filler: the first front-loads the purpose and exact output statistics, and the second gives a clear alternative. Every word contributes to selecting or invoking the tool correctly.

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?

Given the presence of a full output schema, the description does not need to explain return values. Combined with annotations for read-only behavior and the explicit sibling routing, it covers the essential information an agent needs. A minor gap is the lack of guidance on how to specify tables/schemas, but the schema's standard parameter names make this largely self-evident.

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 only 25%; the connection parameter is well-documented in the schema itself. The description partially compensates for the undocumented column parameter by specifying that it must be an orderable numeric, date, timestamp, or text column. However, the table and schema parameters receive no added meaning, and the description does not clarify how to qualify the table or handle the optional schema parameter.

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 states a specific verb ('Measure') and resource ('percentile distribution for one orderable numeric, date, timestamp or text column') and enumerates exact outputs (min/max, P25/P50/P75/P90/P95/P99, null counts). It also distinguishes itself from columnDistribution by explicitly naming that sibling as the alternative for top frequent values.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context for when to use this tool: when percentile distribution for a single orderable column is needed. It explicitly instructs to use columnDistribution for top frequent values instead, providing a direct exclusion and routing the agent to a sibling tool.

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