Do I need a wallet or crypto?

No — card checkout gets you an API key. Wallets are optional, and only for the x402 pay-per-call path used by autonomous agents.

Agent OracleRealtid-nettforsknings-API bygget for AI-agenter, som returnerer kildesittet, strukturert data.

4.6 (5)

Anmeldt av Daniel Nikulshyn·Oppdatert mai 2026

API Developer Tools AI Agents Web Research RAG Real-Time Data Structured Data

Oversikt

Agent Oracle er et forskningslag som er spesielt designet for AI‑agenter og automatiserte arbeidsflyter. Det utfører live nett‑søk og returnerer resultatene som strukturerte, maskinlesbare data sammen med kildehenvisninger, slik at agenter kan forankre sin resonnering i oppdatert informasjon i stedet for utdaterte treningsdata. I stedet for å skrape eller tolke rå HTML, kan utviklere kalle Agent Oracle for å hente friske svar med vedlagt provenance. Dette gjør det egnet for brukstilfeller som markedsovervåking, faktasjekkpipelines, retrieval-augmented generation, og autonome agenter som trenger å verifisere påstander før de handler.

Nøkkelfunksjoner

Realtid-nettforsknings-API
Kildesitater med hver respons
Strukturert, maskinlesbar utdata
Designet for AI-agent arbeidsflyter
Støtter retrieval-augmented generation
Live-data utover modellens kunnskapsgrense

Priser

Modell: $0.02
Kategori: Oversikt
Vurdering: 4.6 / 5 (5)

Brukstilfeller

Forankre AI-agenter i live-nettdata

Gi autonome agenter fersk, kildesittet informasjon utover modellens treningsgrense slik at de kan resonnere og handle på aktuelle fakta i stedet for utdaterte kunnskaper.

Retrieval-augmented generation-pipelines

Koble Agent Oracle til RAG-arbeidsflyter for å hente strukturert, kildesittet kontekst som LLMs kan bruke til å generere nøyaktige, verifiserbare svar.

Automatiserte faktasjekkingsflyter

Verifiser påstander programmatisk ved å hente live-nettresultater med kildeattribusjon, noe som muliggjør pipeliner som flagger eller bekrefter uttalelser før videre bruk.

Marked- og konkurrentovervåkning

Kjør planlagte agentspørringer for å spore markedsendringer, konkurrentoppdateringer eller bransjenyheter, og returnere strukturert data klar for dashbord eller varsler.

Fordeler og ulemper

Fordeler

Returnerer kildesittede resultater for verifiserbarhet
Strukturert utdata er enkel for agenter å parse
Gir oppdatert informasjon utover modellens treningsgrense
Spesielt designet for programmatisk agentbruk

Ulemper

Krever utviklerintegrasjon for bruk
Kvaliteten avhenger av tilgjengelige nettkilder
Ikke rettet mot ikke-tekniske sluttbrukere

Anmeldelser

4.6

Gjennomsnitt fra 5 vurderinger.

Logg inn for å legge igjen en anmeldelse.

Daniel Schmidt

May 10, 2026

Use it every day

Honestly didn't expect to like it this much. Structured, machine-readable output is exactly what I needed, and provides up-to-date information beyond model training cutoffs. but I reach for it almost every day now and it just clicks.

Carlos Mendoza

Apr 20, 2026

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on supports retrieval-augmented generation, and structured output is easy for agents to parse caught me off guard. Quality depends on available web sources is why this isn't a perfect score, still, I'd recommend giving it a real trial.

Liam O’Connor

Apr 5, 2026

Does the job

Pretty happy overall. Real-time web research API just works and purpose-built for programmatic agent use. Quality depends on available web sources can be annoying, but no dealbreakers — I'd recommend it to a friend without hesitating.

Ethan Brooks

Aug 28, 2025

Compared a few options

Evaluated this against two competitors. Where it wins: source citations with each response and structured output is easy for agents to parse. Where it lags: quality depends on available web sources. On balance the feature set — especially live data beyond model knowledge cutoffs — justifies the 4 stars for our use case.

Grace Okafor

Jul 6, 2025

Compared a few options

Evaluated this against two competitors. Where it wins: supports retrieval-augmented generation and provides up-to-date information beyond model training cutoffs. Where it lags: quality depends on available web sources. On balance the feature set — especially structured, machine-readable output — justifies the 4 stars for our use case.

Spørsmål

Can my agent pay per call without an account?

Yes — that's the x402 path: the agent pays per verification in USDC (gasless via SKALE) and gets the receipt in the response. Built for agent-to-agent commerce.

Asked by Idris Suleiman · Jun 21, 2026

What happens when a claim fails the check?

You get the same signed receipt with verdict "do_not_act" and the contradicting sources sealed in. The "no" is evidence too — often the more valuable kind.

Asked by Ivo Novotný · Jun 14, 2026

Does this help with the EU AI Act?

Article 12 requires records of high-risk AI operation, applicable December 2027. Receipts are records that verify independently — the property plain logs can't offer an examiner. We publish a free Article 12 mapping in the whitepaper.

Asked by Fumiko Sato · Jun 1, 2026

How do I verify a receipt without trusting you?

Install the MIT-licensed verifier (or write your own from the IETF draft — a team already has, byte-identically). Verification runs offline against our published public keys. You never need our permission, our API, or our continued existence.

Asked by Yara Mansour · May 31, 2026

What exactly does a receipt prove?

That a specific claim was checked at a specific time, against named sources, under a published rule table, producing a specific verdict — and that none of it has been altered since. It proves what was checked and what the answer was. It doesn't prove things it can't: our whitepaper publishes the limits next to the strengths.

Asked by Mohammed Al-Amin · Mar 27, 2026