--- url: "https://predictiontoolkit.com/tools/finfeedapi/" publisher: "PredictionToolkit" dateModified: "2026-11-03" --- [← Data APIs]() ![FinFeedAPI Prediction Markets logo]() Data API # FinFeedAPI Prediction Markets FinFeedAPI Prediction Markets unifies listings, metadata, trades, quotes, candles and books behind several protocols. It supports both ready-made historical series and raw order-book changes, letting applications choose between a dashboard view and their own reconstruction pipeline. [**3.5**/ 5Editorial rating]() [Editorial assessment]() [Explore the prediction-markets API]() www.finfeedapi.com **Available on:** API · MCP **Pricing:** [See plans and costs ↓]() [Screenshots]() [Explore alternatives]() [Data APIs]() [Historical data]() +1 more [MCP servers]() ## Screenshots and interface Product preview1 / 2 Product and integration navigation. ## What is FinFeedAPI Prediction Markets? Begin by listing exchanges and active market identifiers, then retrieve complete records with outcomes, status and prices. The documented venue list includes Polymarket, Kalshi, Manifold and Myriad; those venues span different market types, so verify endpoint coverage for each one rather than assuming identical data everywhere. REST, JSON-RPC and hosted MCP expose the normalized datasets to ordinary applications and compatible assistants. Historical book files contain adds, updates and deletions rather than reconstructed snapshots. A replay therefore needs both book reconstruction and deliberate handling of processing-time selection versus exchange-event timestamps. ### Who it is for - Developers consolidating data from several prediction venues. - Researchers building historical replay and backtesting datasets. - AI applications requiring discoverable market-data tools. ## Features and coverage - **Exchange and market discovery** List supported venues and active IDs, then obtain full records with outcomes, status and prices. - **Trades and quotes** Retrieve recent or historical activity in a common schema that retains timing information. - **OHLCV history** Request market-level or exchange-level candles using available periods and ascending chronological order. - **Current outcome books** Inspect bids, asks, depth and spread for an individual outcome. - **Raw book events** Download flat-file additions, updates and deletions for your own historical book reconstruction. - **REST, JSON-RPC and hosted MCP** Use the same normalized datasets through these protocols. The hosted MCP exposes venue discovery, market lookup, activity, candles and book queries to compatible AI clients. ## Workflows with FinFeedAPI Prediction Markets ### Build a multi-venue dashboard Use exchange and active-market discovery to build and store an ID list for the dashboard. Load metadata and quotes for those IDs, and request current books only for views that need execution-depth information. ### Reconstruct a historical book Bound the requested period, preserve both event and processing timestamps, and reconstruct the book before comparing its state with trades. ### Connect a market-data assistant Configure the hosted MCP endpoint with an API key. Start with exchange discovery, then issue a request for a specific market. ## Pricing and total cost Billing uses credits. Pay-as-you-go pricing is $5 per 1,000 requests for the first 1,000 requests each day, then $1 per 1,000 requests beyond that daily threshold. Monthly commitments discount purchased credits. ### Pay as you go $1 per credit - No committed monthly spend ### Committed 64 $64/month - Each credit costs $0.85 ### Committed 256 $256/month - Each credit costs $0.75 ### Committed 512 $512/month - Each credit costs $0.70 ### Committed 1024 $1,024/month - Each credit costs $0.65 ### Fees and usage costs - Usage beyond committed credits is charged at the pay-as-you-go rate. **Trial:** Qualified new organizations receive $25 in usage credits. ## Getting started **Before you start:** Processing timestamps and exchange-event timestamps are distinct; choosing the wrong one can misalign a replay. 1. Create an account and obtain an API key, then list exchanges and select the venue IDs needed by the project. 2. Request active market IDs and retrieve complete metadata for a small sample. 3. Choose REST, JSON-RPC or hosted MCP for the application. 4. Set historical ranges, request limits and a credit budget before scaling collection. Historical selection may use processing time while records also carry exchange-event time; a replay must use the appropriate timestamp. [Read the data API documentation]() ## Useful links - [Review credits and pricing]() ### What to check - Processing timestamps and exchange-event timestamps are distinct; choosing the wrong one can misalign a replay. - Raw historical book changes need reconstruction before they form a usable snapshot. - Listed venues have different market types; verify actual endpoint coverage for each target venue. A closer look ## Ratings & reviews Editorial rating **3.5**/ 5 0 user reviews PredictionToolkit editorial ### Our take on FinFeedAPI Prediction Markets Normalized discovery, activity and history across several interfaces provide a practical integration base. Workload design still needs to account for credit pricing and the distinction between processing and exchange timestamps. Based on documented features, setup and access terms. [How we rate]() ### User reviews 0 The main score switches to user ratings after 5 published reviews. **Be the first to share your experience** A specific example helps the next person choose the right tool. ## Related tools [Browse category]() ![Pendulum Flow public archive introduction and capture eras]() ![Pendulum Flow Orderbook Archive logo]()[Pendulum Flow Orderbook Archive]() Dataset**4.0**Editorial Inspect hourly Parquet files and coverage audits before reconstructing historical Polymarket depth. Compare an archive specializing in order-book history. ![ARBITER unified API entry page and sample market view]() ![ARBITER logo]()[ARBITER]() Data API**3.5**Editorial Query normalized markets, historical books, wallet analytics and possible event matches across Polymarket and Kalshi. - Access API Also in APIs and Data Providers. ![Official Dome notice about acquisition and API end of life.]() ![Dome logo]()[Dome]() discontinued Data API**1.0**Editorial Retired hosted API toolkit retained as a reference for existing data and streaming integrations. Compare another toolkit for prediction-market data. ## Frequently asked questions about FinFeedAPI Prediction Markets ### Can I obtain raw order-book changes? Yes. Historical book files provide adds, updates and deletions for your own reconstruction. ### Can an MCP client query the data? Yes. The hosted server uses an API key and exposes discovery and data-retrieval tools. ### Does a commitment change request counting? The commitment discounts purchased credits. Usage after those credits is billed at the pay-as-you-go rate. ### Does this API execute orders? The listed product is a market-data API; its documented role is data discovery and retrieval. In this profile