MAXIA Oracle
UnclaimedMulti-source price feed for AI agents, aggregating and reconciling real-time market data.
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Tracked since2026
0 reviews trackedThe Bottom Line
Entry price
Free plan available, paid tiers above
Biggest pro
High data integrity and reliability through multi-source aggregation and reconciliation.
Biggest con
Historical data retention is limited to 30 days.
TL;DR - MAXIA Oracle
- Aggregates real-time price data from six independent sources for AI agents.
- Provides a transparent audit trail with divergence figures for data validation.
- Offers a comprehensive API and client libraries for easy integration into agent frameworks.
Pricing: Free plan available
Best for: Growing teams
What is MAXIA Oracle?
MAXIA Oracle provides a robust and reliable multi-source price feed specifically designed for autonomous AI agents. It aggregates and reconciles real-time price data from six independent upstream sources, including Pyth Hermes, Chainlink, Coinpaprika, RedStone, Pyth Solana, and Uniswap v3 TWAP. This approach ensures data integrity and allows agents to make informed decisions by providing a divergence figure for outlier detection.
The platform offers a comprehensive API with 17 distinct tools, enabling agents to retrieve aggregated prices, batch prices, source statuses, historical data, and even set up price alerts. It supports various agent frameworks through dedicated client libraries for Python and TypeScript ecosystems, including LangChain, CrewAI, AutoGen, and LlamaIndex. MAXIA Oracle is ideal for developers building AI agents that require highly accurate, verifiable, and manipulation-resistant market data for decentralized finance (DeFi), trading, and other data-sensitive applications.
Its key benefit lies in its transparency and auditability, presenting all contributing sources and their divergences rather than a black-box aggregated figure. This empowers agents to implement their own policies for handling data discrepancies, fostering trust and autonomy.
Available on: Web
Pros & Cons
Pros
- High data integrity and reliability through multi-source aggregation and reconciliation.
- Transparency in data sourcing, showing all contributing sources and their divergences.
- Easy integration with popular AI agent frameworks via dedicated client libraries.
- Flexible pricing model with a generous free tier and pay-per-call option.
- No sign-up, dashboard, or email required for the free tier, enabling quick prototyping.
Cons
- Historical data retention is limited to 30 days.
- The free tier has a daily request limit of 100, which might be restrictive for high-volume testing.
- Pay-per-call option is currently limited to USDC on Base mainnet via x402 protocol.
Key Features
Multi-source price aggregation (Pyth Hermes, Chainlink, Coinpaprika, RedStone, Pyth Solana, Uniswap v3 TWAP)Divergence figure for outlier detection and data validationAggregated price retrieval for single or batch symbolsAccess to individual source statuses and heartbeatsHistorical price snapshots with 30-day retentionOne-shot webhook price alertsClient libraries for Python and TypeScript agent frameworks (LangChain, CrewAI, AutoGen, LlamaIndex)Direct on-chain reads from Chainlink and Pyth Solana
Pricing Plans
Pricing checked Jun 17, 2026
Free tier
$0 / day
- 100 requests / day / key
- Every endpoint, no feature gating
- Issued on-demand by POST /api/register
- Keyed by header, nothing client-side on Base
Pay-per-call · x402
$0.001 / request
- 0.001 USDC per single request
- 0.005 USDC per batch (up to 50)
- Coinbase x402 facilitator, with on-chain fallback
- Anonymous — no key required
Reviews
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MAXIA Oracle FAQ
How does MAXIA Oracle ensure the reliability of its price data?
MAXIA Oracle aggregates and reconciles real-time price data from six independent upstream sources, including Pyth Hermes and Chainlink. This multi-source approach, combined with divergence figures for outlier detection, ensures high data integrity and reliability for AI agents.
Which teams would benefit most from using MAXIA Oracle?
Teams developing AI agents for decentralized finance (DeFi), trading, and other data-sensitive applications would find MAXIA Oracle particularly useful. Its focus on verifiable and manipulation-resistant market data supports informed decision-making for autonomous agents.
How does MAXIA Oracle compare to Chainlink for data sourcing?
MAXIA Oracle differentiates itself from Chainlink by providing transparency in its data sourcing, showing all contributing sources and their divergences rather than a single aggregated figure. This allows AI agents to implement custom policies for handling data discrepancies.
What kind of historical data is available through MAXIA Oracle?
MAXIA Oracle provides access to historical price data through its API. However, historical data retention is limited to 30 days, which is a consideration for applications requiring longer-term historical analysis.
Does MAXIA Oracle include a free tier for developers?
Yes, MAXIA Oracle offers a generous free tier that allows for quick prototyping without requiring sign-up, a dashboard, or an email. This tier has a daily request limit of 100, and paid plans are available for higher usage.
How does MAXIA Oracle support integration with AI agent frameworks?
MAXIA Oracle provides dedicated client libraries for popular AI agent frameworks within the Python and TypeScript ecosystems. These include LangChain, CrewAI, AutoGen, and LlamaIndex, facilitating easy integration for developers.
Can AI agents use MAXIA Oracle to detect price outliers?
Yes, MAXIA Oracle provides a divergence figure for outlier detection, allowing AI agents to identify and react to unusual price movements. This transparency empowers agents to make more informed decisions by understanding data discrepancies.
Source: oracle.maxiaworld.app