Mathpix

Specialized OCR and document processing API for mathematical content. Mathpix converts images, PDFs, and handwritten math into LaTeX, MathML, Markdown, and structured formats with best-in-class accuracy for equations, tables, chemistry diagrams, and scientific notation. Also offers Snip (iOS/Windows app) for converting photos of math to LaTeX. Critical for RAG applications over scientific papers where math equation fidelity is required.

Evaluated Mar 06, 2026 (0d ago) vcurrent
Homepage ↗ AI & Machine Learning pdf ocr latex math science document-parsing api
⚙ Agent Friendliness
63
/ 100
Can an agent use this?
🔒 Security
82
/ 100
Is it safe for agents?
⚡ Reliability
80
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
--
Documentation
85
Error Messages
80
Auth Simplicity
90
Rate Limits
82

🔒 Security

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

HTTPS enforced. API key pair (app_id + app_key) for authentication. Uploaded documents processed on Mathpix servers — review data retention policy for confidential scientific documents. US-hosted — consider for GDPR compliance.

⚡ Reliability

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

Best When

You're processing scientific papers, textbooks, or handwritten math where equation accuracy is critical — standard PDF parsers produce garbled LaTeX.

Avoid When

You're processing business documents, invoices, or non-scientific PDFs — cheaper general OCR tools will perform as well at lower cost.

Use Cases

  • Convert scientific PDFs with complex mathematical equations to LaTeX or Markdown for RAG and LLM ingestion
  • Extract structured data from academic papers, textbooks, and technical documents with accurate math/chemistry notation
  • Convert handwritten math from images to LaTeX for STEM education applications and agent pipelines
  • Process large volumes of scientific literature (arXiv papers, textbooks) for training data preparation with accurate equation representation
  • Build RAG systems over technical documentation where equation accuracy matters — standard PDF parsers corrupt math symbols

Not For

  • General OCR for non-scientific documents — AWS Textract, Google Document AI, or Azure Form Recognizer are more cost-effective for business documents
  • Tables in non-scientific contexts — specialized table extraction tools handle business tables better
  • Very high-volume, cost-sensitive pipelines — Mathpix pricing per page can add up at scale

Interface

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

Authentication

Methods: api_key
OAuth: No Scopes: No

app_id and app_key pair in HTTP headers. Keys generated in Mathpix dashboard. No scope granularity — single key pair grants access to all API methods.

Pricing

Model: usage_based
Free tier: Yes
Requires CC: No

Usage-based per API call. Free tier limited to 1000 requests/month — sufficient for development. Production pipelines over scientific literature can incur significant costs at $0.004/page.

Agent Metadata

Pagination
none
Idempotent
Full
Retry Guidance
Not documented

Known Gotchas

  • Large PDFs require async batch processing (pdf endpoint) rather than page-by-page conversion — use the right endpoint for your use case
  • LaTeX output may use custom macro definitions — downstream LaTeX rendering must support standard LaTeX
  • Mathpix MMD (Mathpix Markdown) format is different from standard Markdown — check output format compatibility with your downstream pipeline
  • Chemistry structures (SMILES notation) require enabling chemistry features in API request options
  • Very complex multi-column PDFs may have column order issues in text extraction — verify output for two-column scientific papers
  • Processing cost scales with PDF page count — for books or large technical documents, plan budget carefully
  • API calls include base64-encoded image/PDF data — large documents require chunking or file URL upload for efficiency

Alternatives

Full Evaluation Report

Detailed scoring breakdown, competitive positioning, security analysis, and improvement recommendations for Mathpix.

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

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