Kopioitavat ohjeet. Valmiit API-esimerkit.

Read this llms.txt (AI-optimized API docs):
https://api.paperoffice.ai/latest/docs/llms.txt

Build me an invoice extractor that:
1. Uploads a PDF via POST /job/add/workflow (multipart, field file_1)
2. Uses idp_collection=invoice, processing_lane=instant (sync)
3. Reads every field from result.pages_idp[0].suggested_fields
   (keys like _supplier_name, _total_amount, _invoice_date)
   and the boxes from result.pages_aiocr.pages
4. Renders a verification view highlighting each value
   at its bounding box position

Auth: Authorization: Bearer po_ut_YOUR_API_KEY

Read this llms.txt (AI-optimized API docs):
https://api.paperoffice.ai/latest/docs/llms.txt

Write a minimal script that:
1. Sends an image or PDF to POST /job/add/paperoffice_aiocr___generate
   (multipart, field file_1)
2. Uses ocr_mode=complete and processing_lane=instant (sync)
3. Prints the extracted text from result ?? job_result (pages)

Modes: complete (+tables), grid (+bounding boxes), text (plain).
Auth: Authorization: Bearer po_ut_YOUR_API_KEY

Read this llms.txt (AI-optimized API docs):
https://api.paperoffice.ai/latest/docs/llms.txt

Build a splitter for large batch PDFs (up to 3000 pages):
1. POST /job/add/workflow with template=pdf_ai_split (multipart, field file)
2. naming_instruction=Dokumenttyp_Datum_Absender,
   locale=de_DE, processing_lane=instant
3. List every created document from the result
   (suggested filename + page range)

The AI detects document boundaries automatically.
Auth: Authorization: Bearer po_ut_YOUR_API_KEY

Read this llms.txt (AI-optimized API docs):
https://api.paperoffice.ai/latest/docs/llms.txt
Also use llms-full.txt for anonymize parameters (scenario, apply).

Build a GDPR anonymizer (preview → apply):
1. POST /job/add/workflow template=document_anonymize_preview (field file)
2. Set scenario=gdpr_auskunft (or externe_weitergabe / finanzdaten),
   redact_categories=all, optional whitelist / custom_redact
3. client_wait=false then poll GET /job/get/{job_id}
4. Show detected_pii.redact_box_ids + simplified_boxes
5. Apply: POST /job/add/paperoffice_dataripper___redact_image
   with files + bounding_boxes + redact_boxes from the preview
   (or MCP: po_anonymization_pii_detect → po_anonymization_redaction_apply
   with preview_job_id)
Optional one-shot: REST template=document_anonymize OR MCP po_anonymization_anonymize
  (no HITL; pass scenario/whitelist).
Redact Agent: POST /documents/redact-agent-run or MCP po_documents_redact_agent_run.

Auth: Authorization: Bearer po_ut_YOUR_API_KEY

Read this llms.txt (AI-optimized API docs):
https://api.paperoffice.ai/latest/docs/llms.txt

Build a text-to-speech generator:
1. POST /job/add/paperoffice_voice___tts with text=..., voice=Nadja,
   output_format=mp3
2. output=url and processing_lane=instant for a synchronous audio link
3. Play or download the audio URL from result ?? job_result

Voices: Nadja, Thomas, Anna, Hans (DE) + 100+ more.
Auth: Authorization: Bearer po_ut_YOUR_API_KEY

Read this llms.txt (AI-optimized API docs):
https://api.paperoffice.ai/latest/docs/llms.txt

Build a contract extractor that:
1. Uploads a PDF via POST /job/add/workflow (multipart, field file_1)
2. Uses idp_collection=contract, processing_lane=instant (sync)
3. Reads parties, dates and notice period from
   result.pages_idp[0].suggested_fields (value + bounding box)
4. Renders a verification view with bounding boxes

Auth: Authorization: Bearer po_ut_YOUR_API_KEY

Read this llms.txt (AI-optimized API docs):
https://api.paperoffice.ai/latest/docs/llms.txt

Build an e-signature request flow:
1. Ensure the document has a pofid in PaperOffice
2. POST /signatures/create with document_pofid (or pofid)
   and a signers array (name + email per signer)
3. Return the signature request id and status
4. Optionally POST /signatures/remind for pending signers

Auth: Authorization: Bearer po_ut_YOUR_API_KEY

Read this llms.txt (AI-optimized API docs):
https://api.paperoffice.ai/latest/docs/llms.txt

Build a secure document delivery (digital registered mail):
1. POST /document_delivery/create_and_send with:
   pofids: ["POFID_HERE"],
   recipient_email, optional recipient_name,
   subject, optional message
2. security_mode=link → PDF password in the same email
   security_mode=secure_sms → link by email, password by SMS
   (requires recipient_phone in E.164, e.g. +49170…)
3. Show delivery_id and that access events are logged
   (Versandhistorie / delivery log)

Auth: Authorization: Bearer po_ut_YOUR_API_KEY

Read this llms.txt (AI-optimized API docs):
https://api.paperoffice.ai/latest/docs/llms.txt

Create a Python script that:
1. Takes a folder of invoice PDFs
2. Extracts all fields using POST /job/add/workflow with idp_collection=invoice
3. Returns bounding boxes for verification (result.pages_aiocr)
4. Exports to CSV

Important: Use file_1 for uploads; fields live in result.pages_idp[0].suggested_fields.
Handle sync (HTTP 200 with result) and async (HTTP 202 → poll GET /job/get/{job_id}).
Auth: Authorization: Bearer po_ut_YOUR_API_KEY

Read this llms.txt (AI-optimized API docs):
https://api.paperoffice.ai/latest/docs/llms.txt

Help me set up the MCP Server for PaperOffice in Cursor.
I want to use Document AI directly in my IDE.

Show me:
1. How to configure the MCP connection (URL https://mcp.paperoffice.ai/cursor)
2. Available tools via tools/list
3. How to process documents from my workspace

Auth: Authorization: Bearer po_ut_YOUR_API_KEY

Read this llms.txt (AI-optimized API docs):
https://api.paperoffice.ai/latest/docs/llms.txt

Create a voice agent that:
1. Takes audio input (Speech-to-Text)
2. Processes the text
3. Generates audio response (Text-to-Speech)

Use these pipelines:
- STT: POST /job/add/paperoffice_voice___stt (audio_file)
- TTS: POST /job/add/paperoffice_voice___tts (text, voice=Nadja,
  output_format=mp3, output=url)
- Use processing_lane=instant for a synchronous response.
Auth: Authorization: Bearer po_ut_YOUR_API_KEY

Read this llms.txt (AI-optimized API docs):
https://api.paperoffice.ai/latest/docs/llms.txt

Build a fraud detection system that:
1. Checks device fingerprints
2. Validates IP geolocation
3. Detects suspicious patterns

Use the Security & Data AI endpoints.
These are instant APIs (no polling needed).
Auth: Authorization: Bearer po_ut_YOUR_API_KEY

Read this llms.txt (AI-optimized API docs):
https://api.paperoffice.ai/latest/docs/llms.txt

Create a batch processor that:
1. Takes a folder of large PDFs (up to 3000 pages each)
2. Uses POST /job/add/workflow with template=pdf_ai_split
3. Uses naming_instruction for smart filenames
4. Handles async jobs (HTTP 202) by polling GET /job/get/{job_id}

Use locale=de_DE for German document types.
Auth: Authorization: Bearer po_ut_YOUR_API_KEY

Read this llms.txt (AI-optimized API docs):
https://api.paperoffice.ai/latest/docs/llms.txt

Build a document classifier that:
1. Watches a folder for new PDFs
2. Uses OCR (POST /job/add/paperoffice_aiocr___generate, ocr_mode=complete)
   to extract text
3. Classifies into: invoice, contract, receipt, correspondence
4. Moves files to category subfolders
5. Logs results to classification_log.csv

Authenticate with: Authorization: Bearer po_ut_YOUR_API_KEY.
processing_lane=instant for a synchronous response.