Best Polymarket API for AI Agents

The ranking rewards whoever does the specific job best, not whoever has the most features. The full matrix that underpins it covers 10 providers across historical prices, historical L2, resolution, free tiers, and bulk export. Facts below were verified against public pricing and docs pages on September 24, 2026, and recorded in our provider matrix.

• 1. PolyOrderbooks — for agent-native data: REST-first 250ms history with a Python SDK, an MCP server for Cursor and Claude, and Backtest AI that turns plain-English strategies into replayable tests.
• 2. Official Polymarket APIs — for authoritative live state and, per its docs, a documented MCP server for querying markets and prices.
• 3. Dune Analytics (Dune API) — for agents that think in SQL: the Dune API runs queries against on-chain tables with a community client and official MCP server.
• 4. Predexon — for multi-venue data behind one key, including premium wallet endpoints an agent can reason over.
• 5. PolymarketData — for broad discovery queries, though with more market noise for an agent to filter.
• 6. PolyTest — for a clean JSON snapshot API purpose-built for Up/Down backtesting loops.
• 7. DepthFeed — for live and historical depth with a bearer-token REST API on paid plans.

Measured coverage is the part a marketing page cannot answer. Our archive captures order books every 250ms and serves every plan, including free Starter, at that same 250ms query resolution. Competitors in the matrix cap documented L2 detail at 1-minute (PolymarketData), at 8 levels per snapshot (PolyTest), or rely on self-reported sub-second claims that conflict across their own pages (PolyTest, PolyBackTest). Resolution is not the only axis. Read the matrix row for interval-sampled versus event-driven capture (Telonex, DepthFeed), for on-chain-only limits that exclude the off-chain book entirely (Dune), and for archives that stop at coverage end or endpoint shutdown (polyReplay, Dome). Each listed product is the best answer for a specific job, and none is the best answer for every job.

Free tiers matter when the honest answer is the official API — which it usually is for live prices. Every provider in the matrix lists its free tier; where the free tier is only a sample or a trial, the row says so. If the job is historical depth, expect to pay for it, because depth history is the expensive thing to keep.

An AI agent needs the data to arrive with its units attached: price, side, bound, UTC second, and the reference behind each number. A stable schema and an MCP server beat a huge SDK, because the agent calls tools by structure rather than by styled examples.

The workflow that proves the point is a market simulation: the agent pulls the market list, subscribes to the frames for one contract, and produces a one-paragraph report naming the executable side. If the provider's endpoint preserves that side information, the agent narrative stays honest; if it only exposes summary fields, the agent loses the venue's defining signal.

Caching matters at the agent tier: a reprice spike triggers many concurrent reads, and the division between live reads and archive reads keeps the agent from hammering one endpoint.

Agent reliability is a schema property, so the evaluation is simple: paste a reprice-window question into the candidate's MCP tools and check that the answer names the executable side and its UTC second. Passing that is table stakes; anything less is summarisation.

Prefer providers with a published, versioned schema and an MCP server, since those are the two things an agent can actually verify.

Test with a reprice-window prompt, not a steady-state prompt; the empty-side second is where agent pipelines reveal their data gaps.

Keep a human audit path: every agent answer should be able to point back to a timestamped raw frame in the archive.

• Full provider matrix
• Order book data
• Price history
• Data download