AgentOracle
Real-time research API for autonomous AI agents — two tiers, no API keys, pay-per-query via x402
🛡️ AgentReady threat assessment
MAESTRO 7-layer threat model + OWASP AIVSS risk score for AgentOracle, derived from its capabilities.
These scores are auto-generated from public information (the agent's own listing, docs, and repository) using the canonical OWASP AIVSS formula and the MAESTRO framework — an estimate for guidance, not a penetration test, audit, or certification. See the scoring methodology — every score is re-derived by the same automated method as an agent's public evidence changes.
Overview
AgentOracle is a real-time research API built specifically for autonomous AI agents. It provides on-demand web research through two tiers: Standard Research ($0.02/query) powered by Perplexity Sonar, and Deep Research ($0.10/query) powered by Perplexity Sonar Pro for comprehensive, expert-level analysis. Agents send a natural-language question via HTTP POST and receive structured JSON back instantly — summary, key facts, sources with URLs, and a confidence score. No API keys, no accounts, no subscriptions. Payment is handled inline via the x402 protocol using USDC on Base mainnet, making it fully autonomous with zero human setup. AgentOracle solves a fundamental problem: AI agents need access to current, real-time information but traditional APIs require human-managed credentials and billing. With x402, an agent discovers pricing through a standard manifest at /.well-known/x402.json, attaches a micropayment header, and gets verified research — all in a single HTTP round trip. Use cases include market intelligence, competitive analysis, fact-checking during reasoning loops, multi-step research workflows, and any scenario where agents need reliable web data without human intervention. Works with LangChain, CrewAI, and any agent framework. MCP server available on GitHub.
Key features and capabilities
- Pay-per-query pricing at $0.02 per research query
- Built on x402 protocol for seamless microtransactions
- Operates on Base mainnet for blockchain integration
- Designed specifically for autonomous AI agent consumption
- On-demand research capability without human intervention
Use cases
- DeFi trading agents researching market conditions and token metrics
- Autonomous research assistants gathering competitive intelligence for businesses
- AI agents verifying factual information before executing transactions
- Web3 applications needing on-chain accessible research capabilities
- Trading bots conducting technical analysis and gathering news sentiment