MCP server for analyzing and humanizing AI-generated text to bypass AI detection.
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# humanizer-mcp [](https://pypi.org/project/humanizer-mcp/) [](https://www.npmjs.com/package/humanizer-mcp) [](https://pypi.org/project/humanizer-mcp/) [](LICENSE) [](https://github.com/aousabdo/humanizer-mcp/actions/workflows/ci.yml) An MCP (Model Context Protocol) server that measures AI-detection risk in a piece of text and tells you — line by line — what to change. Works with Claude Code, Claude Desktop, and any MCP-compatible client. > **Just want to use it?** Go to **[humanizer.analyticadss.com](https://humanizer.analyticadss.com)** — copy the URL, paste it into Claude's Connectors, done. The rest of this README is for developers and people self-hosting. Rather than running your prose through a black-box "humanizer," this server analyzes it against known detection signals (vocabulary, burstiness, contraction usage, paragraph uniformity, em dashes, first-person voice) and returns a structured report with a 0–100 risk score and a concrete rewrite plan. The actual rewriting is left to the LLM that's driving the conversation — which is the point: a planner, not a laundering service. ## Tools | Tool | What it does | |---|---| | `humanizer_humanize_text` | **Returns the rewritten text.** Applies vocabulary swaps, phrase removal, contractions, em-dash cleanup, plus before/after scores. The LLM caller polishes for context. | | `humanizer_analyze_ai_tells` | Full analysis with risk score, fix recommendations, *and* a mechanical rewrite as a starting point. | | `humanizer_quick_vocab_scan` | Fast word- and phrase-level scan with replacement suggestions. | | `humanizer_get_rewrite_instructions` | Step-by-step rewrite …
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