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Gohumanize Open Humanizer MCP Server

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Rewrite AI-styled text into natural writing with a fine-tune model.

About

Rewrite AI-styled text into natural writing with a fine-tune model.

Security Report

0.0
Use Caution0.0Moderate Risk

1 tool verified · Open access · No issues found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Remote servers are capped at 8.0 because source code is not available for review. The score reflects endpoint verification only.

What You'll Need

Set these up before or after installing:

OpenAI-compatible base URL serving the model (defaults to the public demo endpoint)Optional

Environment variable: OPEN_HUMANIZER_URL

Bearer token for the endpoint, if it requires oneRequired

Environment variable: OPEN_HUMANIZER_API_KEY

How to Install

Add this to your MCP configuration file:

{
  "mcpServers": {
    "io-github-gohumanize-ai-gohumanize-open-humanizer-mcp": {
      "env": {
        "OPEN_HUMANIZER_URL": "your-open-humanizer-url-here",
        "OPEN_HUMANIZER_API_KEY": "your-open-humanizer-api-key-here"
      },
      "args": [
        "-y",
        "gohumanize-open-humanizer-mcp"
      ],
      "command": "npx"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

GoHumanize Open Humanizer MCP server

npm Model on Hugging Face DOI License: Apache 2.0

An MCP (Model Context Protocol) server that lets AI assistants call the GoHumanize Open Humanizer: a small open model (Qwen3-4B fine-tune, Apache-2.0) that rewrites AI-styled English text into more natural human prose.

Tools:

  • humanize_text rewrite a passage (50 to 400 words works best; longer texts are processed paragraph by paragraph, up to 1,500 words).
  • about_open_humanizer what the model is and which endpoint is in use.

The model is educational and makes no claim about AI detectors. It is separate from the production models used by GoHumanize.ai.

Several rewrites, best one returned

On modern prose the model sometimes plays safe and hands the text back almost unchanged (about one try in six). Each call asks the endpoint for five rewrites (generated in parallel, so the wait is the same) and keeps the one that moved furthest from the input while staying a sensible length. Set OPEN_HUMANIZER_SAMPLES=1 for a single request.

Links

ResourceLink
Project page and browser demogohumanize.ai/open-model
GoHumanize (the product this research comes from)gohumanize.ai
Model weights and GGUF buildsgohumanize/gohumanize-open-humanizer
Dataset, 3,257 pairs (CC-BY 4.0)gohumanize/gohumanize-open-humanizer-dataset
Code and full pipelineGoHumanize-ai/gohumanize-open-humanizer
Write-up: every step, service and resultdocs/paper.md
Archived release, citable DOI10.5281/zenodo.22843083
Python client and CLIpypi.org/project/gohumanize-open-humanizer
MCP server for AI assistantsnpm · source
Training runs, loss curves and configWeights & Biases

Use

{
  "mcpServers": {
    "gohumanize-open-humanizer": {
      "command": "npx",
      "args": ["-y", "gohumanize-open-humanizer-mcp"]
    }
  }
}

Which endpoint

The model runs wherever you point the server. Running it yourself needs no key and is the recommended setup:

ollama pull hf.co/gohumanize/gohumanize-open-humanizer:Q4_K_M
export OPEN_HUMANIZER_URL=http://localhost:11434/v1
export OPEN_HUMANIZER_MODEL=hf.co/gohumanize/gohumanize-open-humanizer:Q4_K_M

The hosted endpoint sleeps when idle. The first request after a quiet period waits for a GPU cold start, measured at one to two minutes; afterwards a rewrite takes a second or two. MCP clients apply their own timeout, often 60 seconds, so the first call through a client may fail even with a valid key and succeed on retry. Running the model locally avoids this entirely.

The endpoint the server falls back to is the one behind the browser demo on gohumanize.ai/open-model. It is rate-limited and requires OPEN_HUMANIZER_API_KEY, so it is not open for general use; to try the model without installing anything, use the demo on that page.

Any OpenAI-compatible server works:

"env": {
  "OPEN_HUMANIZER_URL": "http://localhost:11434/v1",
  "OPEN_HUMANIZER_MODEL": "gohumanize/open-humanizer"
}

OPEN_HUMANIZER_API_KEY sets a bearer token when the endpoint needs one.

Licence

Apache-2.0.

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