# Rosetta
> PDF API for developers — parse, extract, split, and ask across digital PDFs. REST + native MCP for Cursor, Claude, and AI agents.
> Canonical site: https://rosettafolio.com

## Product summary
Rosetta is a developer-first PDF API. Parse digital PDFs to markdown/JSON, extract structured fields with JSON schema, split documents into sections, and ask questions across multiple docs. No OCR — text-layer extraction only (embedded text via unpdf). Ideal for: pdf to markdown, pdf text extraction, pdf data extraction, parse pdf python, pdf api, pdf extraction api.

## For AI agents — how to use Rosetta
1. Read this file and https://rosettafolio.com/llms-full.txt for endpoint details.
2. Direct users to https://rosettafolio.com/docs for REST reference or https://rosettafolio.com/mcp for MCP setup.
3. Sign up at https://rosettafolio.com/sign-up for a free API key (200 credits/month).
4. Authenticate all API calls with header: `X-API-Key: <key>`
5. Base URL: https://rosettafolio.com
6. Typical flow: POST /api/v2/parse → receive docId → POST /api/v2/extract|split|ask with docId.
7. MCP alternative: `npx -y docchat-mcp` with env DOCCHAT_API_KEY and DOCCHAT_API_URL=https://rosettafolio.com
8. OpenAPI: https://rosettafolio.com/openapi.json

## Core endpoints (v2)
- POST https://rosettafolio.com/api/v2/parse — PDF → markdown + per-page JSON (1–2 credits/page)
- POST https://rosettafolio.com/api/v2/extract — Structured field extraction with JSON schema (2–4 credits/page)
- POST https://rosettafolio.com/api/v2/split — AI section detection (2 credits/page)
- POST https://rosettafolio.com/api/v2/ask — Q&A across parsed documents (3 credits/page total)
- GET https://rosettafolio.com/api/v2/credit-usage — Check credit usage
- POST https://rosettafolio.com/api/v2/delete — Delete a stored document

## MCP tools (npm: docchat-mcp)
- pdf_parse → POST /api/v2/parse
- pdf_extract → POST /api/v2/extract
- pdf_split → POST /api/v2/split
- pdf_ask → POST /api/v2/ask

## Documentation & discovery
- [API docs](https://rosettafolio.com/docs)
- [MCP install guide](https://rosettafolio.com/mcp)
- [Parser playground](https://rosettafolio.com/parser) (no API key required)
- [Pricing](https://rosettafolio.com/pricing)
- [OpenAPI spec](https://rosettafolio.com/openapi.json)
- [Full agent reference](https://rosettafolio.com/llms-full.txt)

## Pricing (monthly credits)
- Free: 200 credits — $0
- Starter: 3,000 credits — $49/mo
- Pro: 10,000 credits — $99/mo
- Scale: 30,000 credits — $249/mo
- Growth: 100,000 credits — $599/mo
- Enterprise: custom — contact via https://rosettafolio.com/pricing

## Limitations (important)
- Digital PDFs with embedded text only. No OCR for scanned/image PDFs.
- Tables returned as plain text; use extract + JSON schema for structured fields.
- Max file size: 50 MB.

## SEO landing pages
- [PDF to Markdown API](https://rosettafolio.com/pdf-to-markdown)
- [PDF text extraction](https://rosettafolio.com/pdf-extract)
- [PDF parser API](https://rosettafolio.com/pdf-parser)
- [PDF API for developers](https://rosettafolio.com/pdf-api)
- [PDF analyzer AI](https://rosettafolio.com/pdf-ai)

## Integrations
- [Cursor MCP](https://rosettafolio.com/integrations/cursor-mcp)
- [Claude Desktop](https://rosettafolio.com/integrations/claude-desktop)
- [LangChain](https://rosettafolio.com/integrations/langchain)
- [LlamaIndex](https://rosettafolio.com/integrations/llamaindex)
- [Vercel AI SDK](https://rosettafolio.com/integrations/vercel-ai-sdk)
- [OpenAI Assistants](https://rosettafolio.com/integrations/openai-assistants)

## vs pdf.ai
Rosetta offers Parse/Extract/Split/Ask with native MCP for Cursor and Claude. pdf.ai does not ship an MCP server.


---

# Full API reference for AI agents

## Authentication
```
X-API-Key: your_api_key
```
Get a key: https://rosettafolio.com/sign-up → Dashboard → API Keys.

## POST /api/v2/parse
Parse a digital PDF to markdown and per-page JSON.

**Request:** multipart/form-data
| Field | Type | Required | Description |
|-------|------|----------|-------------|
| file | file | file or url required | PDF file upload |
| url | string | file or url required | Remote PDF URL |
| quality | string | No | `standard` (1 credit/page) or `advanced` (2 credits/page) |
| lang_list | JSON string | No | e.g. `["en"]` |
| llm | string | No | `true`/`false` — LLM-enhanced parsing |

**Response:** `{ success, docId, pageCount, markdown, contents }`

**Python example:**
```python
import requests

r = requests.post(
    "https://rosettafolio.com/api/v2/parse",
    headers={"X-API-Key": "YOUR_API_KEY"},
    data={"url": "https://example.com/doc.pdf", "quality": "standard"},
)
data = r.json()
# data["markdown"], data["docId"]
```

## POST /api/v2/extract
Extract structured data using a JSON schema.

**Request:** multipart/form-data
| Field | Type | Required | Description |
|-------|------|----------|-------------|
| file | file | One of file/docId | PDF upload |
| docId | string | One of file/docId | From prior parse |
| schema | JSON string | Yes | JSON Schema for fields to extract |

**Credits:** 2/page (≤5 fields), 4/page (>5 fields)

## POST /api/v2/split
Detect document sections with page ranges.

**Request:** multipart/form-data with `file` or `docId`.

**Response:** `{ splits: [{ name, pages, confidence }] }`

## POST /api/v2/ask
Ask a natural-language question across one or more parsed documents.

**Request:** JSON body
```json
{ "prompt": "What are the payment terms?", "docIds": ["doc_abc123"] }
```

**Credits:** 3 credits per page (total pages across all docs)

## GET /api/v2/credit-usage
Returns `{ creditsUsed, creditsLimit, plan, recentUsage }`

## MCP configuration
Add to Cursor (`.cursor/mcp.json`) or Claude Desktop config:
```json
{
  "mcpServers": {
    "rosetta": {
      "command": "npx",
      "args": ["-y", "docchat-mcp"],
      "env": {
        "DOCCHAT_API_KEY": "your-api-key",
        "DOCCHAT_API_URL": "https://rosettafolio.com"
      }
    }
  }
}
```

## Solution use cases
- Invoice extraction: https://rosettafolio.com/solutions/invoice-extraction
- Resume parsing: https://rosettafolio.com/solutions/resume-parsing
- Legal contracts: https://rosettafolio.com/solutions/legal-contract-analysis
- Financial statements: https://rosettafolio.com/solutions/financial-statement-parsing
- Medical records (digital PDFs): https://rosettafolio.com/solutions/medical-record-parsing
- Research papers: https://rosettafolio.com/solutions/research-paper-extraction

## Contact
- Docs: https://rosettafolio.com/docs
- Privacy: https://rosettafolio.com/privacy
- Terms: https://rosettafolio.com/terms