Skip to main content
Glama
Sign In
AutoRank MCP

AutoRank MCP

by RyanKramer
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

validate_json_ld

Validate JSON-LD blocks by parsing and checking required Schema.org fields to flag issues that cause rich-result warnings.

Instructions

Validate a JSON-LD block: parse it, check required Schema.org fields, and flag the things that commonly cause a rich-result warning.

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": {
      "content": "<content>"
    },
    "name": "validate_json_ld"
  }
}

Input Schema

NameRequiredDescriptionDefault
contentYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

No annotations are provided, so the description carries the transparency burden. It discloses that the tool parses, checks required Schema.org fields, and flags common warning triggers, implying a read-only validation behavior. It does not explicitly state side effects, but 'validate' suggests no modifications, and the output schema will cover return values.

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 one concise sentence, structured with a colon and a list, front-loading the action verb and resource. No unnecessary words are present.

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

Completeness5/5

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

For a single-parameter validation tool with an output schema and no annotations, the description covers selection and invocation context adequately. It is complete for the agent to understand when and how to use it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has no parameter descriptions, but the description explicitly identifies the 'content' parameter as a JSON-LD block to validate, providing meaning beyond the schema. With only one parameter, this is sufficient.

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

Purpose5/5

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

The description clearly states the tool's function: validating a JSON-LD block via parsing, checking required Schema.org fields, and flagging common rich-result warning causes. This distinguishes it from sibling tools that generate schema or check other SEO elements.

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 implies use when you have an existing JSON-LD block to validate, and it is not for generating schemas. However, it does not explicitly state alternatives or when-not-to-use conditions, so it earns a 4 rather than a 5.

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

Deploy Server

Other Tools