OkraPDF Public Documentsv1.0.0

A researcher queries pre-parsed arxiv papers to get answers about recent AI advancements, compare results across multiple papers, and extract structured benchmark data without manual reading.

A financial analyst browses pre-extracted SEC 10-K and 10-Q filings for major companies, asks questions about revenue segments, risk factors, and compares R&D spending across competitors to inform investment decisions.

An analyst uses the SEC filing channel to compare AI strategies, gross margins, or debt obligations across up to 10 tickers in a single query, enabling rapid competitive benchmarking.

A data scientist extracts tabular benchmark results from arxiv papers by providing a JSON schema, getting structured numbers for models, datasets, and scores without manual copy-pasting.

Arxiv papers channel requires a free API key for access, while SEC filings remain completely open. This model attracts users with zero-auth SEC features and upsells them to the authenticated arxiv service.

OkraPDF provides pre-extracted, structured document corpora (research papers and financial filings) accessible via API. Users pay indirectly through API key usage or future subscription plans for high-volume access.

By integrating as MCP servers, OkraPDF becomes a core utility within AI agent ecosystems (Claude Code, Cursor). This creates stickiness and positions the platform as an essential tool for agentic document querying.