originality-mcp

originality_scan_url

Scan any published web page by URL to detect AI content, check plagiarism, verify facts, assess readability, correct grammar, and optimize SEO.

Instructions

Scan content from a URL. The API fetches the content from the provided URL and runs the same checks as a regular scan. Useful for analyzing published web pages.

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": {
      "url": "<url>",
      "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_url"
  }
}

Input Schema

Name	Required	Description
`url`	Yes	URL of the page to scan
`title`	No	Identifier/label for the scan
`check_ai`	Yes	Enable AI detection
`check_plagiarism`	Yes	Enable plagiarism detection
`check_facts`	Yes	Enable fact checking
`check_readability`	Yes	Enable readability analysis
`check_grammar`	Yes	Enable grammar checking
`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

A3.8/5.0

Behavior3/5

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

Without annotations, the description bears full behavioral burden. It discloses that the API fetches content and runs checks, but lacks details on authorization, rate limits, destructiveness, or latency. It adds some value beyond the schema but is not fully transparent.

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 two sentences, front-loaded, and no fluff. Every sentence adds value.

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

Completeness2/5

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

Despite 100% schema coverage, the description omits what the tool returns (e.g., scan ID or result object). Since the sibling 'originality_get_scan_results' exists, it implies this tool submits a scan, but no mention of output format. With 15 parameters and no output schema, more context is needed.

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 coverage is 100%, so parameters are well-documented. The description adds no additional meaning beyond the schema; it only mentions the 'URL' parameter implicitly. Baseline 3 is appropriate.

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 it scans content from a URL, fetching and analyzing it like a regular scan. It effectively distinguishes from siblings like originality_scan (direct text) and batch_scan (batch processing).

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 says it is 'useful for analyzing published web pages,' implying when to use via URL. It mentions 'same checks as a regular scan,' hinting at alternatives, but does not explicitly state when not to use or compare to other tools.

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

Deploy Server