originality-mcp

originality_scan

Identify AI-written content, plagiarism, factual inaccuracies, readability issues, grammar errors, and SEO weaknesses in one scan.

Instructions

Run a comprehensive content scan for AI detection, plagiarism, fact checking, readability, grammar/spelling, and SEO optimization. Requires plain text content. Each enabled check consumes 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": {
      "title": "<title>",
      "content": "<content>",
      "check_ai": "<check_ai>",
      "check_plagiarism": "<check_plagiarism>",
      "check_facts": "<check_facts>",
      "check_readability": "<check_readability>",
      "check_grammar": "<check_grammar>",
      "check_contentOptimizer": "<check_contentOptimizer>",
      "aiModelVersion": "<aiModelVersion>"
    },
    "name": "originality_scan"
  }
}

Input Schema

Name	Required	Description
`title`	Yes	Identifier/label for the scan
`content`	Yes	Plain text content to analyze
`check_ai`	Yes	Enable AI detection
`check_plagiarism`	Yes	Enable plagiarism detection
`check_facts`	Yes	Enable factual accuracy verification
`check_readability`	Yes	Enable readability scoring
`check_grammar`	Yes	Enable grammar/spelling checks
`check_contentOptimizer`	Yes	Enable SEO optimization analysis
`aiModelVersion`	Yes	AI detection model to use
`optimizerQuery`	No	Target keyword/phrase for SEO analysis
`optimizerCountry`	No	Country for SEO analysis (e.g. "United States")
`optimizerDevice`	No	Device type for SEO analysis
`optimizerPublishingDomain`	No	Website URL for contextual SEO analysis
`storeScan`	No	Whether to persist results for later retrieval
`excludedUrls`	No	URLs to exclude from plagiarism checks

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0May 28, 2026

TDQS

A3.6/5.0

Behavior3/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It reveals that enabled checks consume credits and that content must be plain text, but it does not disclose rate limits, whether results are returned synchronously, what happens if credits are insufficient, or how stored results are structured. The storeScan parameter suggests persistence but is not explained.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

The description is concise with two sentences. The first sentence front-loads the comprehensive capabilities, and the second adds key constraints. While efficient, it could benefit from a slightly more structured breakdown of the scan types.

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

Completeness3/5

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

Given the tool has 15 parameters (9 required), no output schema, and no annotations, the description covers the core purpose and credit consumption but lacks details on return format, processing model (sync/async), and how to use stored results. It is sufficient for basic understanding but not fully complete for an agent to predict behavior without additional context.

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 the baseline is 3. The description adds minimal value beyond the schema: it notes that plain text is required and that credits are consumed per check. No deeper semantics are provided for individual parameters.

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 performs a comprehensive content scan and lists all specific checks (AI detection, plagiarism, fact checking, readability, grammar/spelling, SEO). It distinguishes from siblings like originality_scan_url and originality_batch_scan by focusing on plain text content for a single scan.

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 description mentions the requirement for plain text content and that each enabled check consumes credits, which provides some usage context. However, it does not explicitly guide when to use this tool versus alternatives like originality_scan_url or originality_batch_scan, nor does it specify exclusions or alternatives.

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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