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Agent API overview

Alphio Agent API gives developers programmatic access to Alphio's market intelligence and (eventually) trade execution. Currently in Coming Soon status.

Find it at: not yet publicly available. Early-access signup runs through Contact Us — see section 5.

warning

Agent API is not yet publicly available. Sign up for early access via Contact Us. Schedule announced separately.

1. Data API today, Agent API tomorrow​

The Agent API ships in two phases:

  • v1 — read-only Data API. A stable surface over Alphio's market intelligence layer. Endpoints cover symbol search, market news, fundamentals, earnings, calendars, market indicators, AI top picks, and whales tracking. Read-only, no trade execution.
  • v2 — programmatic agent capabilities. Trade execution across the three rails, portfolio reads, agentic chat, backtesting, and webhook delivery. This is the full "Agent API" surface; v1 is the foundation it builds on.

Most developers will start on v1 because the data endpoints are the largest stable surface and don't require connection setup (broker, wallet, USDC) on the API side.

2. Read-only Data API surface (v1 plan)​

The v1 surface mirrors what Alphio already serves to its web and mobile clients, exposed as a developer-facing API. Endpoint categories:

  • Symbol search — popular stocks / crypto, trending features, default discovery feeds.
  • Market news & sentiment — market-wide news stream and sentiment signals.
  • AI top picks — daily top-pick stock and crypto lists curated by Alphio AI.
  • Symbol fundamentals — snapshot, valuation, and financials for a given ticker.
  • Earnings — earnings calendar, AI predictions, post-earnings analysis, transcripts.
  • Calendars — economic, IPO, crypto, webcast schedules.
  • Market indicators — fear-greed index, sentiment, daily / weekly digest content.
  • Whales tracking — institutional positions and US congressional trade disclosures.

A preview of the exact endpoints (paths, query parameters) is on the Data API preview page.

3. Programmatic agent capabilities (v2 roadmap)​

v2 turns the API from "read Alphio data" into "operate Alphio". Themes on the roadmap:

  • Trade execution — place / cancel orders across all three rails (Stock Trading, Hyperliquid Perpetuals, Prediction Markets) with the same check → preview → submit semantics as the Trade Modal.
  • Portfolio reads — positions, orders, balances per connected account.
  • Agentic chat — send a prompt and receive Alphio AI's research / plan / execution output, including tool-call traces.
  • Backtest — run a strategy against historical data and pull the result set.
  • Webhooks — push notifications for fills, signal events, watchlist alerts, and AI task completions.

Each capability rolls out independently; not all v2 themes will launch on day one.

4. Pricing models​

Two pricing paths are planned, chosen by how you authenticate:

  • API Key (subscription-bundled). Bundled into Alphio's paid subscriptions. Your subscription tier sets your quota and feature access. See Authentication for key issuance.
  • x402 (pay-as-you-go). Pay per request in USDC via the x402 protocol — no subscription required. Each request includes the payment, settled on-chain by the protocol. See Authentication.
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Exact request-level pricing for x402, and the per-tier API quota numbers, are still being finalized. Confirm with the product team before integrating against specific pricing assumptions.

5. Early access​

Agent API is not openly available yet. To get on the early-access list:

  • Use Contact Us from the docs site footer or your Account page.
  • The waitlist is reviewed by the product team; selected developers receive credentials and an integration guide ahead of public launch.

The exact public launch date is announced separately. Watch this Agent API section for new pages as they ship.

Agent Instructions: Querying This Documentation

If you need information not on this page, you can query the docs dynamically by sending a GET request with the ask query parameter:

GET https://docs.alphio.ai/trade/agent-api/overview.md?ask=<question>

The question should be specific, self-contained, and written in natural language. The response includes a direct answer plus relevant excerpts and sources.