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juliodelimas

jmeter-mcp-server

by juliodelimas

add_jdbc_request

Add a JDBC Request sampler under a specified parent in a JMeter test plan, using a named dataSource to run SQL queries.

Instructions

Add a JDBC Request sampler under the given parent (usually a Thread Group). dataSource must match a JDBC Connection Configuration's dataSource name added elsewhere in the same plan.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoJDBC Request
queryYes
planIdYes
parentIdYes
queryTypeNoSelect Statement
dataSourceYes
variableNamesNoComma-separated variable names to store each result column under
resultVariableNoVariable name to store the whole result set under

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.4.5

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description carries the full transparency burden. It discloses a key dependency (dataSource must match an existing configuration) and clarifies that the element is added to a parent. However, it does not cover failure behavior, return value, or what happens if the parent or dataSource is invalid.

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 primary action is front-loaded, and the critical prerequisite is stated in the second sentence without unnecessary detail.

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?

For an 8-parameter mutation tool with no annotations and no output schema, the description covers placement and the main prerequisite but omits guidance on queryType semantics, required plan/parent state, and return behavior. It is adequate for selecting the tool but leaves several call-time details to inference.

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%, so the description must compensate. It adds real meaning to dataSource (must match a JDBC Connection Configuration's name) and parentId (usually a Thread Group), but leaves query, queryType, and the variable storage parameters to their names and enum values. Compensation is partial but helpful.

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 names the exact element to create ('JDBC Request sampler'), the operation ('Add'), and the placement ('under the given parent'). It also distinguishes the tool from the sibling add_jdbc_connection_configuration by focusing on the sampler rather than the configuration.

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?

Provides clear prerequisite context: the sampler requires a JDBC Connection Configuration with a matching dataSource name in the same plan. It does not explicitly list alternatives or when-not-to-use conditions, but the parent placement and dependency are enough for an agent to select it appropriately among sampler siblings.

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