Copyleaks

@copyleaks check this draft blog post for grammar and readability issues before I publish it to the company site.

Copyleaks identified 3 grammar issues (subject-verb agreement in paragraph 2, comma splice in paragraph 4), 2 word-choice suggestions (replace 'utilize' with 'use', 'facilitate' with 'enable'), and flagged readability concerns in the opening sentence (Flesch score 32, consider shorter clauses). Overall structure is clear with logical paragraph flow. The feedback includes specific line references and severity ratings for each issue.

This example uses the Check Writing tool with sandbox=false, which consumes account credits. The MCP returns synchronous feedback, so large documents may time out. Requires API_KEY auth with writing-correction scope. Copyleaks does not rewrite text — it flags issues for manual revision.

@copyleaks analyze this customer support response to see if it contains any AI-generated content that we should flag internally.

Copyleaks AI Text Detector classified the 240-word response as 87% likely AI-generated, with high confidence on the middle two paragraphs (95% AI probability) and lower confidence on the opening greeting (42% human probability). The tool highlights sentence-level probability scores and notes formulaic phrasing patterns common in GPT-family models. This is a probabilistic classification, not definitive proof of authorship.

This example uses the Detect AI Text tool with sandbox=false, consuming AI detection credits from a separate wallet balance. The MCP returns synchronous results, so it works well for short texts but may struggle with multi-page documents. Check your AI Text credit balance first using the dedicated balance-check tool.

@copyleaks scan our draft privacy policy for harmful content labels before we send it to legal review, and summarize any flags by severity.

Copyleaks content moderation found no high-severity flags in the 1,800-word policy draft. Two medium-severity labels appeared: 'legal jargon density' in Section 4 (may confuse non-expert readers) and 'ambiguous consent language' in Section 7 (could be clearer about opt-out mechanisms). No profanity, hate speech, or violence detected. The tool does not assess legal compliance — it flags readability and tone issues that might harm user trust.

This example pairs the Moderate Text tool (sandbox=false, consumes credits) with AI reasoning to prioritize findings. Copyleaks moderation focuses on harmful-content labels, not legal accuracy — always route flagged sections to qualified reviewers. The MCP returns label categories and confidence scores, not rewritten text.

When Copyleaks fits a small tutoring or ed-tech team

A 3-person tutoring startup reviewing 20-30 student essays per week needs AI detection, grammar feedback, and plagiarism checks in one pass. Copyleaks wins here because all three tools run synchronously—no webhook polling, no multi-vendor juggling. The writing feedback tool returns grammar, structure, and readability scores in a single call, and the AI detection runs against the same text without re-uploading. The credit-balance tools let you gate features when wallets run low. Trade-off: if you're only doing grammar checks and already use Grammarly or LanguageTool, Copyleaks is overkill. But if you need the AI-detection layer for academic integrity, this MCP keeps the stack simple. Set sandbox=false in production or you'll get mock output forever.

Why Copyleaks moderation works for low-volume community teams

A 5-person community platform moderating 100-200 user posts per day can use the Moderate Text tool to flag harmful content before human review. The tool returns labels synchronously, so you can block or queue posts in real time without building a webhook listener. The supported-metadata endpoint tells you which harm categories Copyleaks covers, so you know the taxonomy upfront. This works if your volume stays under a few hundred calls per day—Copyleaks charges per scan, and the credit-balance tool lets you monitor burn rate. If you're moderating thousands of posts daily or need multi-language nuance, a dedicated moderation API like Perspective or Hive will scale better and cost less per call. For small teams with mixed content-integrity needs, though, Copyleaks bundles moderation with plagiarism and AI detection under one key.

When Copyleaks speeds up freelance writer vetting

A 2-person content agency hiring freelance writers can use the AI Text and Check Writing tools to vet sample submissions in one workflow. A candidate submits a 500-word article; you run AI detection to confirm it's human-written, then pull grammar and readability scores to gauge editing load. Both tools return results in seconds, so you can give feedback on a Zoom call or async in Slack. The credit-balance check keeps you from burning through your wallet on low-quality applicants. This breaks down if you're vetting 50+ writers per month—Copyleaks credits add up fast, and you'd save money with a cheaper grammar API plus spot-check AI detection. But for small agencies hiring 3-5 writers per quarter, the bundled tooling cuts the vetting loop from days to minutes.