Document-level AI humanizer for .docx/.pptx: whole file, selected passages, or flagged text.
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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
* or 0%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.
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.
| 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 |
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".
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.
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.
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.
Apache-2.0
Source-derived launch command. Check the maintainer’s required arguments and credentials before running:
npx -y humanpen-mcpMerge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.
{
"mcpServers": {
"io-github-humanpen-humanpen-mcp": {
"command": "npx",
"args": [
"-y",
"humanpen-mcp"
]
}
}
}Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the client’s tool list, then try a read-only example from its documentation.
Claude Desktop setup referencehumanpen-mcpnpmio.github.humanpen/humanpen-mcp works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.
~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.~/.cursor/mcp.jsonRestart Cursor for changes to take effect..vscode/mcp.jsonReload VS Code window for changes to take effect.~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect..mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.