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juliodelimas

jmeter-mcp-server

by juliodelimas

add_json_assertion

Add a JSON Assertion to an HTTP sampler to validate JSONPath expressions in responses. Configure expected values, regex, negation, and null checks for precise API testing.

Instructions

Add a JSON Assertion under an HTTP sampler, to validate a JSONPath expression exists (and optionally matches a value) in the response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoJSON Assertion
invertNoNegate the assertion
planIdYes
isRegexNoTreat expectedValue as a regular expression
jsonPathYesJSONPath expression, e.g. $.value
parentIdYes
expectNullNo
expectedValueNoValue to compare against, only checked if jsonValidation is true
jsonValidationNoWhether to check expectedValue at all

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.4.5

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the behavioral burden. It explains what the assertion validates but does not disclose that this mutates the test plan, any permission/side-effect implications, or behavior around failing validations/defaults. The optional-match behavior is mentioned but is closer to parameter semantics than to tool behavior.

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 a single front-loaded sentence with no filler. It states the action, the target element, the placement condition, and the core validation behavior without wasted words.

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?

For a mutation tool with nine parameters, no annotations, and no output schema, this description is too thin. It does not explain the required planId/parentId semantics, the meaning of expectNull, or what happens after a successful/failed addition; the agent would need to rely on incomplete schema text for several parameters.

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 56%, and the description adds a high-level hint that matching a value is optional, which aligns with jsonValidation/expectedValue. However, it does not clarify parameters like expectNull, planId, or parentId, and much of the parameter meaning still depends on the schema's own descriptions.

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 uses a specific verb and resource ('Add a JSON Assertion') and states the tool's function: validating that a JSONPath expression exists and optionally matches a value. It is clear and points to the JSON assertion element, but it does not explicitly contrast it with sibling tools such as add_response_assertion or add_json_extractor, so sibling differentiation is only implicit.

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

Usage Guidelines3/5

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

The phrase 'under an HTTP sampler' gives a placement constraint and the validation purpose implies when the tool should be used. However, there is no explicit guidance about when not to use it or how it differs from alternative assertion/extractor tools, leaving the agent to infer the choice.

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