PDF.co API

PDF processing API for converting, merging, splitting, extracting text/data from PDFs, adding annotations, and running OCR on documents via a simple REST interface.

Evaluated Mar 07, 2026 (0d ago) vcurrent
Homepage ↗ Other pdf document-processing conversion ocr extraction rest-api sdk
⚙ Agent Friendliness
60
/ 100
Can an agent use this?
🔒 Security
81
/ 100
Is it safe for agents?
⚡ Reliability
80
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
--
Documentation
80
Error Messages
72
Auth Simplicity
85
Rate Limits
78

🔒 Security

TLS Enforcement
100
Auth Strength
78
Scope Granularity
70
Dep. Hygiene
80
Secret Handling
78

PDF processing API. API key auth. PDFs may contain sensitive data — check data retention policies. Files uploaded to their servers temporarily.

⚡ Reliability

Uptime/SLA
82
Version Stability
80
Breaking Changes
78
Error Recovery
78
AF Security Reliability

Best When

You need versatile PDF manipulation and extraction capabilities in agent workflows without managing PDF processing infrastructure.

Avoid When

You need legally binding signatures, very high-volume processing, or real-time document generation.

Use Cases

  • Extracting text and structured data from PDFs for agent workflows
  • Converting PDFs to Word, Excel, HTML, or images
  • Merging and splitting PDF documents programmatically
  • Filling PDF forms and adding digital signatures
  • OCR processing of scanned documents and images

Not For

  • Legally binding eSignatures (use DocuSign)
  • Real-time document rendering with sub-second requirements
  • Very high-volume processing (costs can add up)

Interface

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

Authentication

Methods: api_key
OAuth: No Scopes: No

Single API key per account. Passed as x-api-key header or query parameter.

Pricing

Model: usage-based
Free tier: Yes
Requires CC: No

Credit-based pricing where different operations cost different credits. Can be affordable for moderate use but scales with volume.

Agent Metadata

Pagination
none
Idempotent
No
Retry Guidance
Not documented

Known Gotchas

  • Large file processing is asynchronous - agents must poll job status or wait for completion URL
  • Files can be provided as URLs or base64-encoded - URL method is much more efficient for large files
  • Processing time varies significantly with file size and complexity - plan for timeouts
  • Credits are consumed even if processing fails partway through
  • OCR quality depends heavily on input scan quality - agents should validate output

Alternatives

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Scores are editorial opinions as of 2026-03-07.

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