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Airparser

Airparser is an LLM-powered document parser that extracts structured data from emails, PDFs, images, scans, and handwritten documents. Users define an extraction schema — a structured list of fields to extract, with optional plain-language descriptions (or auto-generate the schema from a sample document) — and Airparser returns clean, structured JSON. Extracted data can be exported to Google Sheets, Excel, Airtable, or any app via Zapier, Make, n8n, native webhooks, and a REST API. Unlike templa

For agents: LLM-powered document parser turning emails, PDFs, scans and invoices into structured JSON; exports to Sheets, Airtable, Zapier and has a REST API and MCP.

document parsingstructured data extractioninvoice parsingllmrest apipdf to excel

Their llms.txt

The beginning of the file, from our validated copy saved 2026-10-21T09:41:45.331Z. Cached copy · Source on airparser.com

# Airparser

> Airparser is an LLM-powered document parser that extracts structured data from emails, PDFs, images, scans, and handwritten documents. Users define an extraction schema — a structured list of fields to extract, with optional plain-language descriptions (or auto-generate the schema from a sample document) — and Airparser returns clean, structured JSON. Extracted data can be exported to Google Sheets, Excel, Airtable, or any app via Zapier, Make, n8n, native webhooks, and a REST API. Unlike template-based parsers, Airparser handles varying and messy layouts without per-format setup. GDPR compliant. Free trial with 30 credits, no credit card required: https://app.airparser.com/signup

## Overview

- **Product type**: AI / LLM-powered email and document parsing (data extraction) SaaS
- **Extraction engine**: large language models (GPT-class) + OCR engine that recognizes typed, scanned, and handwritten text in 60+ languages
- **Input formats**: emails (body and attachments), PDF, Word, Excel, CSV, images (PNG, JPG), scanned documents, handwritten notes, HTML, XML
- **Output**: structured JSON, Excel, CSV; delivered via webhooks, REST API, Zapier, Make, n8n, Google Sheets, Airtable
- **Human-in-the-loop**: built-in review queue to validate and correct extractions before export ([details](https://airparser.com/human-in-the-loop-document-parsing/))
- **MCP server**: AI agents (Claude, ChatGPT, etc.) can parse documents through the Airparser MCP server ([details](https://airparser.com/airparser-mcp/))
- **Compliance**: GDPR compliant, DPA available ([security](https://airparser.com/security/), [GDPR](https://airparser.com/gdpr/))
- **Company**: from the makers of Parsio.io; rated 4.9/5 on Capterra; featured in Zapier's "best email parsers" guide
- **Website**: https://airparser.com — **Pricing**: https://airparser.com/pricing/

## How it works

1. **Import**: forward emails to a dedicated @airparser inbox, upload documents manually, or send them via API, Zapier, Make, n8n, or the MCP server.
2. **Extract**: define an extraction schema — a structured list of fields to extract (e.g. invoice_number, total_amount, due_date, line_items as a list), each with an optional plain-language description — or generate the schema automatically from a sample document. The LLM extracts these fields regardless of layout variations.
3. **Export**: receive structured JSON in real time via webhooks, sync to Google Sheets or Airtable, trigger automations in Zapier/Make/n8n, or download Excel/CSV.

## Key features

- **Extraction schemas** — a structured list of fields to extract, with optional plain-language descriptions; no templates, no parsing rules, no regex
- **Schema auto-generation** — upload a document and Airparser proposes the extraction schema
- **OCR engine** — typed, scanned, and handwritten text in 60+ languages
- **Email parsing** — dedicated inboxes, parses both email bodies and attachments
- **Tables and line items** — extracts repeating rows (i
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2. Publish the proof: add the line "AgentWebMap ownership: <token>" (token from step 1) to https://airparser.com/llms.txt, or use the DNS, meta-tag or well-known method the response describes.
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MCP equivalent: tools begin_ownership_claim, then verify_domain, at https://agentwebmap.com/mcp. Docs: https://agentwebmap.com/docs#verify

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