humanpen-mcp

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Keywords: ai humanizer, mcp server, model context protocol, turnitin ai detection, reduce ai score, humanize ai text, bypass ai detection, docx ai humanizer, ai content rewriter, ai writing tool, claude mcp, cursor mcp, ithenticate ai report

Humanize what's flagged. Preserve the rest. An MCP server for HumanPen — a document-level AI humanizer that can humanize an entire document, rewrite user-selected passages, or automatically target flagged text from a Turnitin / iThenticate AI-detection report, editing .docx / .pptx files in place while preserving formatting, tables, images, citations, and formulas. Also converts citations between 12 styles, condenses to a word budget, and translates between 12 languages.

claude mcp add humanpen -s user -e HUMANPEN_API_KEY=hp_your_key -- npx -y humanpen-mcp

Features

• Selective rewriting by detection report — import a Turnitin / iThenticate AI Writing Report to pinpoint flagged passages; unflagged content is never touched
• Format in, format out — a DOCX comes back as a DOCX, a PPTX as a PPTX; formatting, tables, images, and formulas survive intact and the result is still editable
• Academic structure preserved — in-text citations, reference lists, footnotes, TOC fields, cross-references, figure numbering, equations, and special formatting are treated as protected objects
• No error injection — restructures meaning and syntax to change expression; never adds grammar mistakes, spelling errors, or awkward sentences as a detection strategy
• Full-length documents — no per-input word limit; a single file can be up to 100 MB, no splitting into text boxes
• Free to keep going — still flagged? Re-humanize for free with a fresh report until the AI rate falls to * or 0%
• Word-count control (experimental) — set a min/max word range to keep the output within a target length
• Pay per rewrite — billed on words actually changed, not the whole document; failed and cancelled jobs cost nothing; credits never expire

Get a key

Sign up at https://humanpen.net and create a key at https://humanpen.net/settings/api-keys. New accounts start with free credits, enough to put a document through and see what comes back.

The key goes in an environment variable, never in a URL. URLs end up in server logs, proxy logs, shell history and screenshots.

Install

claude mcp add humanpen -s user -e HUMANPEN_API_KEY=hp_your_key -- npx -y humanpen-mcp

-s user puts it in every project. The default scope is local, which loads the server only in the directory you ran the command from — and looks like a broken install the first time you open Claude Code somewhere else.

If your version rejects -e (reported upstream), use the JSON form:

claude mcp add-json humanpen -s user '{"command":"npx","args":["-y","humanpen-mcp"],"env":{"HUMANPEN_API_KEY":"hp_your_key"}}'

In ~/.codex/config.toml:

[mcp_servers.humanpen]
command = "npx"
args = ["-y", "humanpen-mcp"]
env = { HUMANPEN_API_KEY = "hp_your_key" }

codebuddy mcp add --scope user humanpen -- npx -y humanpen-mcp

It also reads ${VAR} in its config, so the key can stay in your environment instead of the file:

{ "mcpServers": { "humanpen": {
  "command": "npx", "args": ["-y", "humanpen-mcp"],
  "env": { "HUMANPEN_API_KEY": "${HUMANPEN_API_KEY}" }
} } }

~/.codebuddy/.mcp.json for every project, <project>/.mcp.json for one.

It has gemini mcp add, but the argument order differs between versions — run gemini mcp add --help and follow the usage line it prints. Pass the key with -e HUMANPEN_API_KEY=... and the scope with -s user; the default is project, which is only the directory you ran it in.

In claude_desktop_config.json. Use the absolute path to npx — run which npx and paste the result: a desktop app is launched by the OS with a minimal PATH, so the bare name that works in your terminal often is not found here, and the only symptom is that the tools never appear.

{
  "mcpServers": {
    "humanpen": {
      "command": "npx",
      "args": ["-y", "humanpen-mcp"],
      "env": { "HUMANPEN_API_KEY": "hp_your_key" }
    }
  }
}

All three read the same shape — Cursor in .cursor/mcp.json, Windsurf in ~/.codeium/windsurf/mcp_config.json, Cline in its MCP settings panel:

{
  "mcpServers": {
    "humanpen": {
      "command": "npx",
      "args": ["-y", "humanpen-mcp"],
      "env": { "HUMANPEN_API_KEY": "hp_your_key" }
    }
  }
}

In opencode.json — the key names differ slightly from everyone else's:

{
  "mcp": {
    "humanpen": {
      "type": "local",
      "command": ["npx", "-y", "humanpen-mcp"],
      "environment": { "HUMANPEN_API_KEY": "hp_your_key" }
    }
  }
}

{
  "mcp": {
    "inputs": [
      { "type": "promptString", "id": "humanpenKey", "description": "HumanPen API key", "password": true }
    ],
    "servers": {
      "humanpen": {
        "command": "npx",
        "args": ["-y", "humanpen-mcp"],
        "env": { "HUMANPEN_API_KEY": "${input:humanpenKey}" }
      }
    }
  }
}

VS Code prompts once and stores the key in its secret store, so it never lands in a file you might commit.

git clone https://github.com/humanpen/humanpen-mcp
cd humanpen-mcp && npm install && npm run build

Then point your client at node /path/to/humanpen-mcp/dist/index.js instead of npx -y humanpen-mcp.

Any MCP client works: this is a plain stdio server started by npx -y humanpen-mcp with HUMANPEN_API_KEY in its environment.

Tools

Tool	What it does	Credits
humanize_document	Rewrite a .docx/.pptx to read as human-written and score lower on AI detectors. Optionally take a detection report to rewrite only its flagged passages. Length can be held to a whole-document word range, or to per-passage ranges (experimental — limiting words weakens AI-rate reduction).	yes
free_rehumanize	Continue a finished humanize_document job for free: upload a fresh detection report for its result and only the still-flagged passages are rewritten. Once per job, with a daily cap; the report must match that result.	free
fix_citations	Convert in-text citations and the reference list to APA 7, MLA 9, Harvard, Chicago, IEEE, Vancouver, GB/T 7714, AMA, ACS or OSCOLA. Body text untouched.	yes
condense_document	Shorten a .docx to a target word count, keeping structure and citations.	yes
translate_document	Translate .docx/.pdf/.pptx/.xlsx/.epub/.html/.txt between 12 languages, keeping layout.	yes
read_detection_report	Read a Turnitin or iThenticate AI Writing report: overall AI percentage and the flagged passages.	free
check_job	Look up a job and download its result.	free
get_credit_balance	Credits remaining.	free

Two things worth knowing

Jobs take minutes; tool calls do not. Each operation waits about 55 seconds — enough for most documents — then returns a job_id with a note to call check_job. The work continues on the server either way; nothing is lost by the tool returning early.

ai_percent can be null, and that is usually good news. Turnitin prints * instead of a number whenever AI writing comes in under 20% — it will not quantify that band, because too much of it is false positives. So null means "under 20%, and Turnitin will say no more", never "0%" and never "no result".

Questions people ask

Will this bring a Turnitin AI score down? Usually under 20% in one pass with balanced — the threshold below which Turnitin prints * instead of a number. If it misses, hand the result back with the new report; only the passages still flagged get rewritten.

Does it work with iThenticate too? Yes — pass either report. The format is read from the file.

Is my document sent to the model? No. It uploads the file and answers with a path. A 40-page paper costs no tokens.

Privacy Policy

Documents you pass to a tool are uploaded over HTTPS to HumanPen's API (api.humanpen.net) for processing; results are written back to your disk, and processed files are kept server-side for about 7 days so check_job and the free re-humanize pass can find them. Document contents never enter the model's context. The full policy — what is collected, retention, and how to reach us — is at https://humanpen.net/legal/privacy.

Development

npm install
npm run build
HUMANPEN_API_KEY=hp_... node selftest.mjs sample.docx report.pdf

selftest.mjs spawns the built server and talks JSON-RPC to it over stdio the way a real client does — proving the protocol, the tool registrations, stdout hygiene and one end-to-end job, not merely that the functions return. It needs a live key and spends credits, so it is a pre-release check rather than a CI step.

Links

• API documentation · OpenAPI schema
• humanpen-skill — the same operations as an Agent Skill, if you would rather not run a server
• humanpen.net

Apache-2.0