Your private document brain.
PDFs in, RAG out. Self-hosted. Plug everywhere.
Quickstart · What you get · Plug everywhere · Docs · OpenAPI · Changelog
v1.1.0: cloud integrations end-to-end. Connect Dropbox / Google Drive / OneDrive from the UI (paste your own OAuth client_id+secret if the operator hasn't), browse and import any file from the cloud, send any OCR result back as
md,docx,xlsx,obsidian, orzip, and configure watched folders (cloud or local) that auto-submit new files for OCR. See the changelog.v1.0.0: side-by-side multi-model comparison with server-computed word-level diff, model recommendations from your own OCR history, PII auto-redaction with audit trail, form-field extraction, LaTeX equation extraction, and an E2E encryption scaffold (RSA SPKI public-key registration + AES-256-GCM envelope).
Most document-to-AI tools are SaaS. They cost per page, they see your documents, they lock you into one provider. Extracto is the opposite: one Docker container, your machine, any vision model (local or hosted), output goes wherever you want it. Browser, code, agent, vector store. You pick.
A complete pipeline from raw document to retrievable knowledge, in one container:
- Ingest any PDF, image, watched local folder, or watched Dropbox / Google Drive / OneDrive folder.
- Extract with the vision model of your choice (Ollama, Mistral OCR, OpenRouter, any OpenAI-compatible endpoint).
- Post-process with a second LLM pass (clean to markdown or strict JSON, with your own instruction).
- Chunk + embed + store into Chroma, Qdrant, Weaviate, Milvus, OpenSearch, Pinecone, or Typesense.
- Retrieve through a stable v1 REST API, an OpenAI-Chat-Completions adapter, an MCP server, a typed CLI, or the browser UI.
- Push any result back to Dropbox / Google Drive / OneDrive, S3/MinIO, or download as
md,json,docx,rtf,csv,xlsx,obsidian, or per-pagezip.
Everything else (per-user accounts, scoped API keys, rate limits, signed webhooks, S3/MinIO offload, Prometheus metrics, multi-language UI, per-user OAuth credentials when the operator hasn't preconfigured them) is documented at extracto.help.
You need Docker. That's it.
curl -fsSL https://extracto.help/install.sh | bashPulls the prebuilt multi-arch image, runs a single container with an auto-generated AUTH_SECRET and a persistent SQLite volume, waits for the healthcheck, and prints the URL. Open http://localhost:3000, sign up, follow the tour.
For the full install (compose stack, Docker + Ollama provisioning, extracto CLI on PATH, Windows path), see extracto.help/install.
Same backend, five surfaces. Pick what fits.
| Surface | Use it when | Read |
|---|---|---|
| Browser UI | You're a human with a stack of PDFs | How it works |
REST API (/api/v1/*) |
You're building a document-intake pipeline | API reference |
| MCP server | Your agent speaks MCP (Claude Desktop, Cursor, Codex, OpenClaw, Hermes) | Agents |
CLI + SKILL.md |
Your agent only has a shell tool | Skill file |
| OpenAI-Chat adapter | You already have OpenAI-SDK code; point it at Extracto | OpenAI compat |
OpenAPI 3.1 spec at openapi.yaml. Live Scalar reference at /api/v1/docs on every running instance.
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