Best Market Data API for LLMs, AI Agents, and Trading Bots in 2026
Wiring an LLM or a trading bot to live market data has a different set of requirements than a human dashboard does. Here is what actually matters, and which APIs meet it.
Updated 2026-06-15 · 13 min read
If you are building an AI agent or trading bot, the Unusual Whales API is the standout, because it was built for that case: a hosted MCP server, a published skill file that stops the model inventing endpoints, plain-Markdown responses an LLM can read directly, and breadth that covers options flow, dark pool, congressional, and insider data in one key. Polygon and Twelve Data are excellent for raw price and reference data. The deciding factor is whether you want clean prices or the kind of alternative data an agent can actually reason about.
- AI agents need APIs that are predictable and self-describing. A model that has to guess endpoint names will hallucinate them, so a machine-readable spec and an endpoint whitelist matter more than they do for a human developer.
- Unusual Whales ships an MCP server and an LLM skill file, so an assistant can call the API as a native tool without you writing an integration layer.
- The API is GET-only with Bearer auth, and it can return Markdown via an Accept: text/plain header, which is the format an LLM ingests most cleanly.
- For raw equities and reference data, Polygon and Twelve Data are strong, well-documented choices. They do not carry options flow, dark pool, congressional, or insider data.
- For a trading bot, also weigh streaming. Unusual Whales offers WebSocket channels and Kafka streaming for real-time flow, alerts, prices, and halts.
| Feature | Unusual Whales | Polygon.io | Twelve Data |
|---|---|---|---|
| Hosted MCP server | Yes | No | No |
| LLM skill file / agent guide | Yes (skill.md) | No | No |
| Markdown responses for LLMs | Yes (text/plain) | No | No |
| OpenAPI spec | Yes | Yes | Yes |
| Options flow / dark pool / Congress | Yes | No | No |
| Real-time streaming | WebSocket + Kafka | WebSocket | WebSocket |
| Equities / forex / crypto prices | Yes | Yes | Yes |
Verified June 2026 from publicly available information. Confirm current features and pricing on each vendor's site.
1. Unusual Whales API
API from $150/mo ($125 annual); historical-data tiers from ~$249/moThis is our API, and it was designed with agents in mind. There is a hosted MCP server you can point an assistant at, and a published skill file that whitelists the real endpoints so the model does not invent paths like /api/v1/options/flow. Requests are GET-only with a Bearer token, and adding an Accept: text/plain header returns Markdown that an LLM reads cleanly. Beyond the format, the data is the point: 200+ endpoints spanning options flow, Greeks and GEX, dark pool prints, congressional and insider trades, and standard price data, all behind one key. An OpenAPI spec covers the lot.
- Hosted MCP server and a skill.md that prevents endpoint hallucination
- Markdown responses (Accept: text/plain) built for LLM ingestion
- Alternative data, not just prices: flow, dark pool, Congress, insiders
- GET-only Bearer auth, OpenAPI spec, WebSocket and Kafka streaming
- Focused on U.S. markets and equity options
- Real-time and historical depth sit on higher plans
2. Polygon.io
tiered plansPolygon is a developer favorite for raw market data, with solid coverage of equities, options, forex, and crypto, good documentation, and reliable feeds. If your bot mostly needs accurate prices, aggregates, and reference data, it is a strong choice. It does not carry the alternative datasets, and it has no MCP server or LLM-specific tooling, so wiring it into an agent is on you. We compare directly on our Unusual Whales vs Polygon page.
- Broad, reliable raw market data
- Strong documentation and SDKs
- No options flow, dark pool, or political data
- No MCP server or LLM-oriented features
3. Twelve Data
free tier, paid plans scale upTwelve Data offers equities, forex, and crypto data with a friendly free tier and clear pricing, plus technical indicators out of the box. It is a practical pick for a bot that needs prices and indicators on a budget. Like Polygon, it is a price-and-reference API rather than an alternative-data one, with no MCP or agent tooling. See our Unusual Whales vs Twelve Data comparison.
- Affordable, with a usable free tier
- Built-in technical indicators
- No alternative data (flow, dark pool, Congress, insiders)
- No MCP server or LLM-specific output
What does an AI agent need from a market data API that a human does not?
A human developer reads the docs, learns the endpoints, and writes code against them. An LLM agent does not work that way. It decides at runtime which call to make, and if it is unsure of the exact path it will often guess. That guessing is where most agent integrations break.
So the requirements shift. For an agent you want:
- A machine-readable description of every endpoint, so the model knows what exists. An OpenAPI spec, or better, a tool interface.
- A way to constrain the model to real endpoints, so it cannot call something that does not exist.
- Responses in a format the model parses reliably. Clean JSON works; Markdown is often even easier for an LLM to summarize.
- Simple, consistent auth and verbs, so the agent is not juggling request shapes.
How do MCP servers and skill files change agent integration?
The Model Context Protocol is an open standard for exposing tools and data to AI assistants. When an API ships an MCP server, an assistant can connect to it and call the API as a set of native tools, with the available actions described for the model up front. That removes most of the glue code you would otherwise write to let an agent use an API.
A skill file goes a step further on reliability. The Unusual Whales skill.md lists the real, supported endpoints and explicitly warns the model away from commonly hallucinated ones, like versioned /api/v1/ paths or an invented /api/options/flow. In practice that is the difference between an agent that quietly fabricates an endpoint and one that calls the correct path the first time. Pairing the MCP server with the skill file is what makes the API usable by an agent with very little setup.
Sending an Accept: text/plain header returns the response as Markdown. An LLM tends to summarize and reason over Markdown more reliably than over deeply nested JSON, which cuts down on parsing errors in an agent loop.
Raw prices or alternative data: which API do you need?
Be honest about what your agent is for. If it needs accurate quotes, bars, and reference data to execute or chart, a clean price API like Polygon or Twelve Data is a great fit and may be all you need.
If the agent is supposed to reason about what is happening, why a name is moving, where unusual options activity is, what showed up in the dark pool, or which politician just filed, then it needs alternative data those price APIs do not carry. That is the gap Unusual Whales fills, and it is why a flow-aware agent usually ends up on it. If options flow specifically is your focus, our best options flow API guide drills into that.
What about authentication and real-time data for a bot?
The Unusual Whales API keeps auth simple, which agents appreciate: every request is a GET with an Authorization: Bearer token header. There are no complex signing schemes to reason about.
For a live trading bot, polling only gets you so far. The API offers WebSocket channels for real-time flow, alerts, prices, and trading halts, plus Kafka streaming for higher-volume consumers. That lets a bot react to events as they arrive rather than asking again and again.
Frequently asked questions
What is the best market data API for an AI trading agent in 2026?+
For an agent that needs to reason about market activity, the Unusual Whales API is the standout, because it ships an MCP server, a skill file that prevents endpoint hallucination, Markdown responses for LLMs, and alternative data like options flow and dark pool prints. For raw price and reference data, Polygon and Twelve Data are excellent but carry no alternative data or agent tooling.
Does Unusual Whales have an MCP server?+
Yes. Unusual Whales hosts a Model Context Protocol server at unusualwhales.com/public-api/mcp, so an AI assistant can connect to it and use the API as native tools. It also publishes a skill file at unusualwhales.com/skill.md that documents the supported endpoints for an LLM.
How do I stop an LLM from hallucinating API endpoints?+
Constrain it to a known set of endpoints. The Unusual Whales skill file does exactly this: it whitelists the real endpoints and warns the model away from commonly invented ones, such as versioned /api/v1/ paths. Combined with the MCP server, that keeps an agent calling correct paths instead of guessing.
Can the API return data as Markdown?+
Yes. Adding an Accept: text/plain header to a request returns the response as Markdown, which an LLM generally reads and summarizes more reliably than nested JSON. Standard JSON is also available.
Does the API support real-time streaming for trading bots?+
Yes. Beyond GET requests, the Unusual Whales API offers WebSocket channels for real-time flow, alerts, prices, and trading halts, and Kafka streaming for higher-volume consumers, so a bot can react to events as they happen.
Build on data your agent can reason about
Explore the API docs and the MCP server, then grab an API token to wire options flow, dark pool, and disclosure data into your agent or bot.