Drawing Anonymizer

Drawing Anonymizer MCP Server

Anonymize technical drawings before you share them — mask company names, logos, people, addresses and contact data on drawing PDFs from any MCP-enabled assistant.

This Model Context Protocol server exposes the engine behind drawing-anonymizer.imnoo.com, the free drawing anonymizer by Imnoo. Sending a drawing to a supplier, a subcontractor or a second source for a quote? Hand the PDF to your assistant and get an anonymized copy in about a minute: Imnoo's drawing analysis finds the sensitive data in the title block, the notes and anywhere else on the sheet — company names, logos, person names, addresses, phone numbers, emails, websites and other identifying text — and the server whites it out (or replaces it with your own company name and logo), masks any extra term or area you name, and writes a tamper-proof, single-layer PDF with the document metadata removed. Article numbers, drawing numbers, dates, dimensions and tolerances stay readable, so the drawing can still be quoted and manufactured. Need to send it right away? Ask for an expiring share link (1 minute to 24 hours) that only ever serves the masked copy. NDA-safe drawing sharing and GDPR-safe drawing exchange, on vector and scanned PDFs alike. Built by Imnoo, the planning, scheduling and quoting platform for CNC manufacturers — where the same automatic drawing masking protects every drawing that leaves a quote.

"Anonymize bracket.pdf for our subcontractor, put our name in, and give me a 1-hour link"

│ ▼ (your assistant calls the tools) analyze_drawing ──► review_masking ──► mask_drawing │ │ ▼ ▼ 14 masked · 4 visible ART-88213_masked.pdf (flattened, metadata removed) still visible: "BRACKET LEFT" https://drawing-anonymizer.imnoo.com/api/share/… (expires in 1 h)

Tools

Plus an anonymize-drawing prompt that walks the assistant through analyze → review → mask.

Where the analysis runs. Uploading the drawing is the only step that leaves your machine: analyze_drawing (or mask_drawing with a new pdf_path) sends the PDF to Imnoo's drawing analysis exactly like the web app does — 1 free analysis per day per IP address (need more? signed-in Imnoo users get a higher daily limit in the web app); uploaded files are deleted automatically within 24 hours and nothing else is stored. Masking, flattening and metadata removal run locally and are unlimited: review and re-mask as often as you like. A share link uploads the masked copy only — never the original.

Installation

Requires Node.js ≥ 22.13.

Claude Code

claude mcp add drawing-anonymizer -- npx -y drawing-anonymizer-mcp

Claude Desktop

Add to claude_desktop_config.json (Settings → Developer → Edit Config):

{

"mcpServers": { "drawing-anonymizer": { "command": "npx", "args": ["-y", "drawing-anonymizer-mcp"] } } }

Cursor

Add to Cursor — or add to ~/.cursor/mcp.json:

{

"mcpServers": { "drawing-anonymizer": { "command": "npx", "args": ["-y", "drawing-anonymizer-mcp"] } } }

VS Code (GitHub Copilot)

code --add-mcp '{"name":"drawing-anonymizer","command":"npx","args":["-y","drawing-anonymizer-mcp"]}'

Windsurf / other stdio clients

Any client that launches stdio servers works with:

npx -y drawing-anonymizer-mcp

Configuration (optional)

Example session

You: Anonymize C:\drawings\bracket.pdf before it goes to our subcontractor. Put "Supplier AG" where the customer's name was and give me a link that works for an hour.

Assistant: *calls analyze_drawing* — 18 detections on 1 page (A3): 3 company names, 4 person names, a logo, an address, a phone number, an email, a website, 2 other identifying items (a purchase-order number and a project name), plus the article number ART-88213, the drawing number DRW-10457-B and 2 dates, which stay visible. *calls review_masking with mode: "replace" and company_name: "Supplier AG"* — 14 items masked, anonymity score 100; still visible on the sheet: the part title "BRACKET LEFT". *adds it with terms: ["BRACKET LEFT"], reviews again, then calls mask_drawing with the same masking and share_link: "1h"* — wrote ART-88213_masked.pdf (flattened, metadata removed) and created a link that expires at 15:42. Two "Other" detections were found with low confidence — their boxes are worth a glance.

Those numbers are the web app's bundled sample drawing the smoke test runs against; real drawings vary.

Masking options (the masking argument)

One object, accepted by review_masking and mask_drawing — pass the same one to both so the PDF matches the reviewed masks. Everything is optional; the defaults reproduce the web app.

When masking is omitted on a drawing that was masked before in the same session — including the identical PDF under another path — the previous masking is reused, and the identical PDF is not uploaded again.

How the masked PDF is made

• Detections come with their box, value and confidence; the categories you choose (and the detection scope) decide which are masked, and your explicit mask / unmask choices win.
• Boxes are drawn onto a copy of the original pages. With secure on (the default), every page is then rasterized at 288 dpi and the PDF is rebuilt from those images — the covered text no longer exists in the file, so it cannot be copied, searched or recovered by removing the boxes. With secure off, the result is a layered PDF whose original content stays recoverable under the masks; the tools warn about it.
• Document metadata (author, title, subject, keywords, creator, XMP) is removed by default.
• The anonymity score combines the share of identifying detections masked, secure output, metadata removal and full opacity — the same score the web app shows.

Limitations

• The drawing analysis is automated: it can miss text (unusual layouts, free-text notes, hand-written additions) — read visible_text_after_masking in review_masking and add terms or rectangles for anything still identifying, and look at the masked PDF before sharing it.
• Custom terms need the PDF's text layer; on scans, cover areas with rectangles. Inside a longer line the term's position is estimated from the character count, so leave a little margin with a rectangle when a term sits between other text.
• Free tier: 1 analysis per day per IP address; PDFs up to 30 MB and 4 pages. Saved analyses (save_analysis_to → load_analysis) and re-masking are unlimited and offline.
• Dragging boxes, the before/after slider, batch processing of up to 15 drawings and the hand-off from the Imnoo calculator are features of the web app.

Development

The server lives in src/; engine/ holds the masking engine it shares with the web app (mask builder, title-block scope, text search, coverage report and the secure-PDF builder), synced from the Drawing Anonymizer monorepo at Imnoo on every release — so the web app and this server detect, mask and flatten a drawing the same way by construction. Every release is gated on end-to-end checks that drive all four tools over stdio against the sample drawing in test/fixtures and read the output's text layer and pixels:

npm ci

npm test # build + end-to-end stdio checks SMOKE_LIVE=1 npm test # + a real upload and share link (one daily analysis of your IP)

Issues and feature requests are welcome in this repository.

About Imnoo

Imnoo — The System for Manufacturers | AI Planning, Scheduling & Quoting · Complete Assemblies · DFM · Tool & Material Libraries · Quoted-Parts Database · Toolpath & G-Code · Machine Connection · Webshop · ERP · Shop Analytics & Optimization · Drawing Masking & IP Security

*Plan It. Schedule It. Quote It. Win It.* — trusted by over 3,000 manufacturers.

Imnoo is the AI-powered planning, scheduling, and quoting platform for CNC manufacturers — your automatic production platform. One system that covers it all: automatic manufacturing planning with raw-material, catalog and purchase-part, and subcontracting sourcing; scheduling with smart reminders and AI-