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IAnjaniKr

jmeter-mcp-server

by IAnjaniKr

create_test_plan_from_openapi

Turn OpenAPI YAML/JSON files into JMeter test plans. Configure users, loops, ramp time, and load profiles to generate a ready-to-run .jmx file.

Instructions

Create a JMeter test plan from an OpenAPI YAML/JSON file. Use this when the user asks for a plan based on an OpenAPI file.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoOptional JMeter test plan name
loopsNoLoop count; use -1 for forever. For deterministic profiles, omit or match the policy value.
usersNoRequired only for testProfile=custom. For deterministic profiles, omit or match the policy value.
envFileNoOptional .env file used for auth/data defaults
rampTimeNoRamp-up time in seconds. For deterministic profiles, omit or match the policy value.
outputfileYesPath where to save the .jmx file
openapiFileYesAbsolute or relative path to the OpenAPI YAML/JSON file
serverIndexNo1-based OpenAPI server index to use
testProfileNoDeterministic profile: custom, smoke, baseline, load, spike, stress, or soakcustom
endpointIndexNo1-based endpoint index from the OpenAPI paths/methods
durationSecondsNoDuration for scheduled profiles such as soak. For deterministic profiles, omit or match the policy value.
allowAggressiveLoadNoRequired for aggressive profiles or requests that exceed discovered rate limits.
addResponseCodeAssertionNoAdd a response-code assertion based on the OpenAPI success response

Schema Changelog

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

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states that a test plan is created; it does not mention output file overwrite behavior, file existence requirements, parsing failures, authentication needs, or any other side effects of generating the plan.

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 action is front-loaded, and the second sentence provides a useful invocation trigger. Every part of the text contributes value.

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

Completeness2/5

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

This is a 13-parameter tool with no annotations and no output schema, so the one-sentence description is insufficient context. It does not explain how this tool differs from create_test_plan_from_api_source, the effect of deterministic profiles, or what happens after generation. The schema covers parameters, but the workflow and behavioral context are largely 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?

The input schema has 100% description coverage, so all 13 parameters are already semantically documented. The tool description adds no parameter-level guidance beyond the schema, which is acceptable given the high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Create a JMeter test plan') and the specific source resource ('OpenAPI YAML/JSON file'), so an agent can understand what the tool does. It does not explicitly contrast itself with create_test_plan_from_api_source, but the source format provides some differentiation from generic plan creation.

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 an explicit trigger: 'Use this when the user asks for a plan based on an OpenAPI file.' This is clear context for when to invoke the tool, though it does not mention alternatives or when not to use it.

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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