json-schema-validator
Server Details
Validates JSON against a JSON Schema, lists violations. x402 payment required (testnet USDC).
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
1 tooljson_schema_validatorjson_schema_validatorAInspect
Validates JSON against a JSON Schema, lists violations. x402 payment required (Base mainnet USDC).
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes | JSON-encoded strings, each an object like {"schema":...,"data":...} to validate | |
| payment | No | x402 payment payload (base64 JSON), signed EIP-712 exact/transferWithAuthorization. Omit on the first call — the tool will return payment requirements (accepts[]) as an error result. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It explicitly reveals the x402 payment requirement and the non-obvious first-call behavior that returns accept[] as an error result. This goes beyond a basic description and helps the agent anticipate the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, each earning its place: the first states the core function, and the second states the critical payment requirement. There is no fluff, and the key information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity tool with a well-documented schema, the description covers the essential operational context: what it validates, that it lists violations, and the payment workflow. No output schema exists, so an exact return format would be helpful, but 'lists violations' plus the payment-error behavior provides sufficient guidance for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already documents both parameters thoroughly. The description adds no additional parameter-level meaning beyond referencing the payment requirement, which is already covered by the schema. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb ('Validates'), a specific resource ('JSON against a JSON Schema'), and the expected outcome ('lists violations'). It fully explains what the tool does in one concise sentence.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides direct guidance on the payment flow: payment is required, and on first call it should be omitted to receive payment requirements. There are no sibling tools, so no alternative selection guidance is needed, but the two-step calling pattern is clearly implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
1 tool update
- First observed
json_schema_validator
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Discussions
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TDQS
Only one tool exists, so there is zero risk of confusion between tools. The tool's purpose is clearly delimited to JSON Schema validation.
With a single tool, naming is trivially consistent. The snake_case name accurately describes the function.
A single tool is on the thin side, but given the highly focused purpose of JSON Schema validation, the count is justifiable. However, compared to typical MCP servers offering a few operations, this feels minimal.
The tool covers the core operation of JSON Schema validation and lists violations, which fully satisfies the server's stated purpose. There are no obvious missing capabilities within this narrow domain.