io.github.humanpen/humanpen-mcp
NPM · HUMANPEN-MCP
Document-level AI humanizer for .docx/.pptx: whole file, selected passages, or flagged text.
Available components
Last scanned (10 minutes ago)
Scores higher than 72% of npm servers
Category Documents and Files
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security98
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- No install/post-install scripts declared.Pass
- 30 of 93 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency45
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (Apache-2.0).Pass
- Actively maintained (last published 71 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability70
- AI-judged instruction clarity (excellent).Pass
- Context-footprint check failed: tool/resource definitions use about 1472 tokens (~184/item across 8 items; 8 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management97
- Stability observed for 29 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 100% of tool parameters carry a description.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 8 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 8 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 23 Oct 26 0
- Stability: pass → 0.97 functional
- 17 Oct 26 0
- Stability: 0.97 → pass security
- 16 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.
- 14 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 87 to 90. That category is still filling its 30-day observation window: 26 days of observed history at the previous scan, 27 at this one. The score rises as the window fills, whether or not the server changes.
- 12 Oct 26 +16
- Malware scan: unverified → pass ▲ security
- Security disclosure: unverified → fail ▼ functional
- 11 Oct 26 −15
- Malware scan: pass → unverified ▼ security
- Security disclosure: fail → unverified ▼ functional
- 4 Oct 26 −3
- Stability: pass → 0.80 functional
- 3 Oct 26 0
- Stability: 0.97 → pass security
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 23 Oct 2026 · Analysed npm/humanpen-mcp@1.4.3
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | npm |
Background: How many MCP packages publish verified provenance →
Dependencies 93 packages
| Packages resolved | 93 |
|---|---|
| Stale | 30 |
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
check_job Check a job ~85
Look up a job by id, and download its result if it has finished. Use this after a tool returned before the job was done.
| Name | Type | Req | Description |
|---|---|---|---|
| document_path | string | – | The original document, so a downloaded result can be named after it |
| job_id | string | yes | The job id an earlier call returned |
| output_path | string | – | Where to write the result |
No output schema declared.
No examples provided.
condense_document Condense a document ~149
Shorten a .docx to a target word count, keeping meaning, structure and citations. Saves the result next to the source and returns its path. COSTS CREDITS at 100 per 1,000 words processed (10 minimum) - say so and get agreement first.
| Name | Type | Req | Description |
|---|---|---|---|
| document_path | string | yes | Absolute path to the .docx |
| instructions | string | – | Extra requirements for this job |
| max_words | integer | yes | Target word count for the whole document |
| output_path | string | – | Where to write the result; defaults to beside the source |
| wait_seconds | number | – | How long to wait before returning a job id (default 55) |
No output schema declared.
No examples provided.
fix_citations Convert citation format ~189
Rewrite a .docx's in-text citations and reference list into one target style, leaving the body text alone. Saves the result next to the source and returns its path. COSTS CREDITS at 100 per 1,000 words processed (10 minimum) - say so and get agreement first.
| Name | Type | Req | Description |
|---|---|---|---|
| document_path | string | yes | Absolute path to the .docx |
| instructions | string | – | Extra requirements for this job |
| output_path | string | – | Where to write the result; defaults to beside the source |
| style | string | yes | Target style: apa7, mla9, harvard, chicago_author_date, chicago_notes, ieee, vancouver, gbt7714, gbt7714_author_year, ama, acs, or oscola |
| wait_seconds | number | – | How long to wait before returning a job id (default 55) |
No output schema declared.
No examples provided.
free_rehumanize Re-humanize a job's still-flagged passages for free ~278
Continue a finished humanize job for FREE. Upload a fresh detection report for that job's result; only the passages it still flags are rewritten, at no credit cost. The server enforces strict limits: one free continuation per job, a per-day cap, the report must be of THAT job's own result (>=90% match) and show >=20% AI, and the result must still exist (kept ~7 days). If a limit is not met it returns a clear reason - relay it and stop; do not retry or silently fall back to a paid job. Pass the job_id a prior humanize_document (or check_job) returned.
| Name | Type | Req | Description |
|---|---|---|---|
| instructions | string | – | Extra requirements for this job |
| job_id | string | yes | The finished humanize job to continue (its job_id from humanize_document/check_job) |
| output_path | string | – | Where to write the result; defaults to beside the report |
| report_path | string | yes | Absolute path to the fresh Turnitin/iThenticate report for that job's result |
| segments | array | – | Per-passage word control for the still-flagged passages (optional), same shape and experimental caveat as humanize_document.segments |
| wait_seconds | number | – | How long to wait before returning a job id (default 55) |
No output schema declared.
No examples provided.
get_credit_balance Check the credit balance ~49
How many credits the account has. 1,000 words costs 100 credits, charged on the words actually processed, with a 10-credit minimum per job. Worth checking before a large document.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
humanize_document Humanize a document ~414
Rewrite a .docx or .pptx so it reads as human-written and scores lower on AI detectors, keeping meaning, citations, tables and layout. Optionally pass a Turnitin/iThenticate AI report to rewrite only the passages it flagged. If a fresh report still flags the result, run this tool again on the rewritten file with that new report - only the still-flagged passages are touched, and balanced remains the right strategy for the second pass. Saves the result next to the source and returns its path. COSTS CREDITS at 100 per 1,000 words processed (10 minimum) - say so and get agreement first.
| Name | Type | Req | Description |
|---|---|---|---|
| document_path | string | yes | Absolute path to the .docx or .pptx to rewrite |
| instructions | string | – | Extra requirements for this job |
| max_words | integer | – | Upper word bound for the rewritten document (optional; omit for no limit). Same experimental caveat and exclusivity as min_words. |
| min_words | integer | – | Lower word bound for the rewritten document (optional; omit for no limit). Experimental - a word limit noticeably weakens AI-rate reduction, so omit unless the user requires a length. Cannot combine… |
| output_path | string | – | Where to write the result; defaults to beside the source |
| report_path | string | – | Path to a Turnitin/iThenticate AI report PDF; only its flagged passages are rewritten |
| segments | array | – | Per-passage word control (optional): each item is a flagged passage plus its own min_words/max_words. Get the passage texts from read_detection_report and pass report_path alongside so the report def… |
| strategy | string | – | Rewriting intensity; balanced is the usual first choice, aggressive rewrites more heavily |
| wait_seconds | number | – | How long to wait before returning a job id (default 55) |
No output schema declared.
No examples provided.
read_detection_report Read an AI-detection report ~111
Read a Turnitin or iThenticate AI Writing report PDF: returns the overall AI percentage and the flagged passages. Free - reads the file without starting a job. Pass the same report to humanize_document to rewrite only what was flagged.
| Name | Type | Req | Description |
|---|---|---|---|
| include_segments | boolean | – | Include the flagged passage texts, which can be long (default false) |
| report_path | string | yes | Absolute path to the report PDF |
| type | string | – | Which product exported it; omit to identify it from the file |
No output schema declared.
No examples provided.
translate_document Translate a document ~197
Translate a document into another language while keeping its layout, tables, images and formulas. Takes .docx, .pdf, .pptx, .xlsx, .epub, .html and .txt. Saves the result next to the source and returns its path. COSTS CREDITS at 100 per 1,000 words processed (10 minimum) - say so and get agreement first.
| Name | Type | Req | Description |
|---|---|---|---|
| document_path | string | yes | Absolute path to the document |
| output_path | string | – | Where to write the result; defaults to beside the source |
| source_lang | string | – | Source language, or auto to detect it (the default) |
| target_lang | string | yes | Target language: zh, en, zh-tw, ja, ko, es, fr, pt, ru, de, pl or it |
| wait_seconds | number | – | How long to wait before returning a job id (default 55) |
No output schema declared.
No examples provided.
How do I install the io.github.humanpen/humanpen-mcp server?
io.github.humanpen/humanpen-mcp runs locally as an npm package, launched with npx -y humanpen-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
npm · humanpen-mcp
claude mcp add humanpen-humanpen-mcp -- npx -y humanpen-mcp
What is the io.github.humanpen/humanpen-mcp server?
io.github.humanpen/humanpen-mcp is listed in the public MCP registry as io.github.humanpen/humanpen-mcp. Document-level AI humanizer for .docx/.pptx: whole file, selected passages, or flagged text. This page covers its npm package (humanpen-mcp).
Is the io.github.humanpen/humanpen-mcp server safe to use?
io.github.humanpen/humanpen-mcp scores 83 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 23 October 2026. It declares no install or post-install scripts. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the io.github.humanpen/humanpen-mcp server expose?
io.github.humanpen/humanpen-mcp exposes 8 tools: humanize_document, free_rehumanize, fix_citations, condense_document, translate_document, and 3 more. Their descriptions and schemas cost roughly 1,472 tokens of context every time the server is loaded.
Is the io.github.humanpen/humanpen-mcp server still maintained?
io.github.humanpen/humanpen-mcp is still listed as active in the MCP registry. We last reached this channel on 23 October 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.
What licence is the io.github.humanpen/humanpen-mcp server under?
io.github.humanpen/humanpen-mcp declares the Apache-2.0 licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.