IA-QA — 152 QA & Dev Tools for AI Agents

validate_mcp_response

Read-onlyIdempotent

Validate that an MCP tool response conforms to expected format, schema, and content rules. Use this to QA-test any MCP server tool. Supply the tool's actual JSON result and a set of checks to perform.

Input Schema

Name	Required	Description
`response`	Yes	The MCP tool result as a JSON string to validate
`min_items`	No	If response is an array, minimum number of items expected
`expected_type`	No	Expected top-level type: "object", "array", "string", "number"
`required_keys`	No	Comma-separated list of keys that MUST exist in the response (dot-notation for nested: "data.id, data.name")
`actual_latency`	No	Actual measured latency in ms (from the call)
`forbidden_keys`	No	Comma-separated list of keys that MUST NOT exist (e.g. "password, secret, token")
`max_size_bytes`	No	Maximum acceptable response size in bytes
`max_response_ms`	No	Maximum acceptable latency in ms (will be compared if provided)

Output Schema

Name	Required	Description	Default
`total`	No
`checks`	No
`failed`	No
`passed`	No
`verdict`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 31, 2026

addedInput schema / examples

Added value: +[
+  {
+    "forbidden_keys": "password",
+    "response": "{\"user\":{\"name\":\"x\"}}"
+  }
+]

Changed1 schema field changedJun 21, 2026

addedOutput schema / properties

Added value: +{
+  "checks": {},
+  "failed": {
+    "type": "number"
+  },
+  "passed": {
+    "type": "number"
+  },
+  "total": {
+    "type": "number"
+  },
+  "verdict": {
+    "type": "string"
+  }
+}

Changed1 schema field changedJun 10, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "type": "object"
+}

First observedMay 26, 2026

TDQS

A3.8/5.0

Behavior3/5

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

The annotations already establish that this is a safe, read-only, idempotent, non-destructive, closed-world operation. The description adds that it checks format, schema, and content rules, but it does not explain validation failure behavior, output shape, or other runtime details beyond the structured fields.

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 three efficient sentences, front-loaded with the core action and followed by usage and input expectations. Every sentence contributes without repetition or filler.

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 complete schema coverage, annotations, and presence of an output schema, the description is sufficient for an agent to understand and invoke the tool. It could be stronger by naming nearby alternatives or validation-specific edge cases, but no critical invocation information is 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?

Schema description coverage is 100%, so all eight parameters are already documented in the input schema. The description only broadly mentions supplying the JSON result and a set of checks, and does not add syntax or semantics beyond what the schema provides. Baseline 3 is appropriate.

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 states a specific verb and resource: validate an MCP tool response against format, schema, and content rules. It clearly distinguishes this as a QA-testing validator for MCP server tool outputs, though it does not explicitly contrast itself with close siblings such as mcp_schema_lint or function_call_validate.

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?

It gives clear usage context: use this to QA-test any MCP server tool, supplying the actual JSON result and checks. It does not state exclusions or name alternative tools, so it falls short of the top score, but the intended context is clear.

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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