APIVerve

JSON Schema Validator

JSONSchemaValidator

Read-only

JSON Schema Validator: JSON Schema Validator is a JSON validator API that tests any JSON object against a JSON Schema you provide, so you can check JSON against its schema before trusting it. It reports pass-fail status and total error count, while paid plans add specific error messages. (Cost: 2 credits)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "schema": "<schema>",
      "json": "<json>"
    },
    "name": "JSONSchemaValidator"
  }
}

Input Schema

Name	Required	Description	Default
`json`	Yes	The JSON data to validate. An empty object is a valid document and is accepted.
`schema`	Yes	The JSON Schema to validate against

Output Schema

Name	Required	Description
`data`	No
`error`	No	Error message, null on success
`status`	No	"ok" on success

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 7, 2026

TDQS

A3.6/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds genuinely useful context beyond that: it returns pass-fail plus a total error count, detailed error messages require a paid plan, and the call costs 2 credits. That tier/cost disclosure is exactly the sort of behavior an agent cannot get from 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.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded and reasonably short, but the name is restated twice ("JSON Schema Validator: JSON Schema Validator is..."), which is wasted space in the first and most-read sentence. The remaining sentences earn their place by covering output and cost.

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?

An output schema exists, yet the description still summarizes the return shape (pass-fail, error count, gated error messages), which is helpful. Combined with the credit cost and two well-documented params, an agent has enough to call this correctly; only explicit sibling routing 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% (both parameters documented with examples, and the empty-object edge case noted), so the schema carries the load. The description only says a schema "you provide" is required and adds no format or sizing guidance beyond that, so baseline 3 applies.

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?

States a specific verb and resource: it tests a JSON object against a user-provided JSON Schema. That cleanly distinguishes it from the adjacent JSONSchemaGenerator sibling, though the description never names that sibling explicitly, so it stops short of a 5.

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?

Offers an implied use case ("check JSON against its schema before trusting it") but gives no explicit when-to-use/when-not guidance and no pointer to alternatives such as JSONSchemaGenerator for the inverse operation. Usage must be inferred.

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

All APIVerve tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.