Extract Documents Inside Claude with Papersnap's MCP Server

When an AI agent tries to read a PDF on its own, it does its best to look at the page — and quietly guesses at the numbers it can't quite make out. That's fine for a summary and dangerous for an invoice. Papersnap was built to do the opposite: extract clean, structured data from a document and hand back JSON your systems can trust. Now your assistant can call it directly.

Papersnap is live as an MCP server. MCP — the Model Context Protocol — is the open standard that lets AI agents call real tools instead of approximating. Connect Papersnap once, and Claude (or any MCP client) can push a document through the real extraction pipeline and get back structured fields, not a hopeful paraphrase.

What your assistant can do

Papersnap exposes its pipeline as a handful of tools:

• Request an upload — get a secure URL to send a document into Papersnap.
• Extract a document — run an invoice, receipt, purchase order, utility bill, or report through extraction and receive clean, structured JSON.
• Get a result — fetch the finished extraction for a document by its ID, waiting a moment if it's still processing.
• List recent — see the documents you've processed lately.

Strung together, that means you can say "pull the line items and totals out of this invoice and give me JSON" and the assistant does the real work — upload, extract, fetch — instead of squinting at the page. The output is the same structured data the app produces, so it drops straight into a spreadsheet, an accounting system, or the next step of an automation.

Connecting takes about two minutes

Open your MCP client's connector settings, add a custom connector, and paste the Keelara MCP server URL — leave the OAuth fields blank, since registration is automatic. Sign in with a free Keelara account, set the Papersnap tools to Always allow, and start extracting. The exact server URL and a short FAQ are on the Papersnap MCP page, and you can try each tool live, with example inputs, in the Keelara console playground linked from there.

Extraction runs on your normal Papersnap page quota, so agent-driven work counts the same as the app — see the pricing page for how pages and plans work.

Why route it through a real pipeline

The value isn't that the model sees the document — it's that Papersnap understands it: field modeling, the right extraction path per document type, and the checks that catch the errors a naive read would miss. An MCP connection puts that reliability inside your agent's reach, so "turn this stack of receipts into structured data" becomes one instruction instead of an afternoon of manual keying. Connect Papersnap, hand your assistant a document, and get data back you can actually act on.