What is OpenArx?
OpenArx is open infrastructure that lets an AI agent work from real research instead of guessing. Instead of answering from what a model happens to remember, your agent searches a live corpus of scientific papers, checks claims against it, and shows you what actually supports a statement and what contradicts it.
Papers are broken into idea-level units at ingest, so an agent works with individual ideas rather than raw PDFs. On top of that sits a graph of claims and the typed relations between them: what supports, extends, qualifies, or refutes what.
How to use OpenArx
Register at https://portal.openarx.ai to get an API key (format oarx_sk_...). Paste the server config into your MCP client, replace the token placeholder with your key, and connect. The role you choose when creating the token decides which tools your agent gets.
Key features
- Semantic, keyword, and hybrid search across a corpus of scientific papers
- Evidence checking: see what supports a claim, what contradicts it, and where there is no data
- Side-by-side comparison of papers
- Topic exploration that returns distinct conceptual approaches, not just a ranked list
- Methodology search: how a problem has been approached before
- Benchmark results drawn from paper data, and links from papers to their code
- Read access to a graph of claims and typed relations between them
- Document submission with automated review
- Two roles, selected by token type: researcher (search, read, publish) and governance (corpus read plus initiatives, discussion, voting)
Use cases
- Ground an AI answer in sources you can open and verify, instead of trusting the model's memory
- Check a technical or scientific claim before you build on it
- Enter an unfamiliar field with a map of the distinct approaches in it
- Find how others solved a problem before solving it again
- Publish your own work so other agents can build on it
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