Unstructured.io

Document parsing library and API that converts PDFs, Word docs, HTML, and emails into structured elements (Title, NarrativeText, Table) ready for LLM ingestion and RAG pipelines.

Evaluated Mar 06, 2026 (0d ago) v0.15.x
Homepage ↗ Repo ↗ Developer Tools document-parsing pdf rag etl open-source llm-pipeline html word email
⚙ Agent Friendliness
61
/ 100
Can an agent use this?
🔒 Security
81
/ 100
Is it safe for agents?
⚡ Reliability
73
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
--
Documentation
84
Error Messages
75
Auth Simplicity
90
Rate Limits
80

🔒 Security

TLS Enforcement
95
Auth Strength
80
Scope Granularity
70
Dep. Hygiene
75
Secret Handling
82

Cloud API transmits document content to Unstructured servers — review data handling policy for sensitive documents; self-hosted eliminates this concern

⚡ Reliability

Uptime/SLA
72
Version Stability
75
Breaking Changes
70
Error Recovery
76
AF Security Reliability

Best When

You need a single library that handles many document formats and produces typed, structured elements optimized for LLM and RAG pipelines.

Avoid When

You need sub-second latency for single documents or are processing purely image-based scans without embedded text.

Use Cases

  • Pre-process a corpus of PDFs into chunked, typed elements for a RAG vector database ingestion pipeline
  • Extract tables from financial reports as structured JSON for downstream agent analysis
  • Parse email threads and attachments into normalized text for a customer support automation agent
  • Convert mixed-format document archives (DOCX, PPTX, HTML) to uniform structured output for indexing
  • Extract metadata (titles, page numbers, section headers) alongside content to preserve document hierarchy for retrieval agents

Not For

  • Pure OCR of natural scene images — use EasyOCR or Tesseract for non-document images
  • Real-time single-document parsing at sub-100ms latency — cloud API adds network overhead
  • Generating or rendering documents — this is extraction only

Interface

REST API
Yes
GraphQL
No
gRPC
No
MCP Server
No
SDK
Yes
Webhooks
No

Authentication

Methods: api_key
OAuth: No Scopes: No

API key passed as header (unstructured-api-key) for cloud API; self-hosted requires no auth

Pricing

Model: freemium
Free tier: Yes
Requires CC: No

Open-source library is free and unlimited self-hosted; cloud Serverless API is freemium with usage-based paid tiers

Agent Metadata

Pagination
none
Idempotent
Full
Retry Guidance
Documented

Known Gotchas

  • hi_res strategy requires poppler and tesseract system dependencies — missing deps cause silent fallback to fast strategy without warning
  • Table extraction accuracy is highly sensitive to PDF type (native vs scanned) — agents should validate table element counts against expectations
  • Large PDF files (100+ pages) can exceed cloud API request timeout — must split documents before sending
  • Element ordering in output is not always reading-order correct for multi-column layouts — post-processing may be required
  • Self-hosted and cloud API can return different element types for the same document due to different model versions — test both paths if you switch

Alternatives

Full Evaluation Report

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Scores are editorial opinions as of 2026-03-06.

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