11 public forecasting agents examples on Kalshi and Polymarket, each with its source.
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Forecasting agents are programs, often built around large language models, that read information about an event and output a probability, then compare it with the market price. Entries here range from research frameworks to agents that have entered public forecasting tournaments.
Common tools here: Python (5), LLMs (4), TypeScript (4), MCP (2), Perplexity API (1). Compare them side by side → · Kalshi bot guide · Polymarket bot guide
Official framework for building AI agents that research and trade Polymarket markets.
Open-source AI agent that operates across Polymarket, Kalshi and other venues.
Toolkit for building AI-automated trading strategies on Kalshi.
Runs deep fundamental research and produces independent probability estimates for Kalshi markets.
Combines the Kalshi API with Perplexity Sonar search to research markets.
MCP server that lets AI assistants query and interact with Kalshi.
MCP server that lets Claude Code, Cursor and other local AI clients read Polymarket markets, track wallets, backtest and run copy-trading loops. It starts in a preview mode that records simulated trades in SQLite; live mode signs CLOB orders with your own wallet key and enforces safety and daily-budget checks.
An AI forecasting bot that posts weekly public progress updates, including a Metaculus medal and its first public benchmark.
Agents that run user-described strategies with set limits on Polymarket and Hyperliquid, via OutLayer connectors.
FastAPI, PostgreSQL and Redis pipeline where a Claude analyst and an OpenAI challenger each estimate a Polymarket market's probability and a rule-based consensus compares them with the price. It ran as a no-money paper experiment from June to October 2026; the author's write-up (in Russian, self-reported) found no edge over market prices and publishes the data and lessons.
TypeScript Cloudflare Worker that discovers liquid Polymarket markets via the public Gamma API, prices them from CLOB order books, flags possible value with an explainable engine, and simulates paper orders with fees, spread and slippage. It uses D1 for storage and Workers AI to read resolution rules, and tracks its own calibration. It never signs transactions or asks for a wallet key.
New public Kalshi & Polymarket builds, each with a source. No spam.
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