{"bots":[{"blog":"https://octagonai.co","category":"ai-llm","description":"The most-starred AI-driven Kalshi bot, period. Performs deep fundamental research per market via the Octagon Research API, generates independent probability estimates, computes edge against the live order book, sizes via half-Kelly through a five-gate risk engine (Kelly + Liquidity + Correlation + Concentration + Drawdown). Supports JSON output for agent orchestration.","fetched_at":"2026-05-10","github_owner":"OctagonAI","github_profile_fetched":true,"github_repo":"kalshi-deep-trading-bot","github_user_url":"https://github.com/OctagonAI","id":"octagonai-deep-trading","lesson":"the five-gate risk engine is a model for how serious risk management looks in this space. It's not just position sizing \u2014 it's a stack of independent constraints that all have to pass before a trade fires. Most bots that blow up have failed exactly one of those checks.","name":"OctagonAI / kalshi-deep-trading-bot","name_full":"OctagonAI","stars":206},{"blog":"ryanfrigo.com","category":"ai-llm","description":"Grok-4 integration with multi-agent decision-making and portfolio optimization. Uses 0.25 Kelly sizing with a category scorer that hard-blocks markets scoring below 30 out of 100.","fetched_at":"2026-05-10","github_owner":"ryanfrigo","github_profile_fetched":true,"github_repo":"kalshi-ai-trading-bot","github_user_url":"https://github.com/ryanfrigo","id":"ryanfrigo-ai-trading","lesson":"the author's honest disclosure is unusual in this space \u2014 \"AI ensemble can be 80% confident and still be wrong; no edge on economic releases.\" That kind of upfront refusal to overclaim is rare and worth modeling.","name":"ryanfrigo / kalshi-ai-trading-bot","name_full":"Ryan Frigo","stars":null},{"blog":"https://ai-.mngt.com","category":"ai-llm","description":"Dual-loop architecture: Google TimesFM 2.5 for fast quantitative tick predictions, Gemma 4 31B for slow multi-agent LangGraph debate (Bull, Bear, Volatility Forecaster, and Risk Management personas). Built without an SDK using manual RSA-PSS payload cryptography. React/Vite frontend exposes AI inference thresholds and live P&L.","fetched_at":"2026-05-10","github_owner":"BEXAI","github_profile_fetched":true,"github_repo":"KalshiBot","github_user_url":"https://github.com/BEXAI","id":"bexai-kalshibot","lesson":"the dual-loop pattern (fast model + slow reasoning) is the most sophisticated architecture we've seen in open-source prediction-market bots. Trade only when both loops agree is a strong default.","name":"BEXAI / KalshiBot","name_full":"BEX","stars":null},{"bio":"I love cats, bad puns, and Vim, not necessarily in that order.","blog":"https://awanninger.com","category":"ai-llm","description":"\"Vibe-coded\" generative AI bot \u2014 system-prompts an LLM (Grok) into the role of a professional prediction-market trader. More experimental than productionized, but a useful reference for prompt-engineering approaches to trading.","fetched_at":"2026-05-10","github_owner":"ajwann","github_profile_fetched":true,"github_repo":"kalshi-genai-trading-bot","github_user_url":"https://github.com/ajwann","id":"ajwann-genai-bot","lesson":null,"name":"ajwann / kalshi-genai-trading-bot","stars":null},{"category":"ai-llm","description":"A weather-focused bot that uses Claude Opus to size and approve trades. Quarter-Kelly sizing capped by both maximum contracts and maximum dollar risk per trade. The combination of LLM-as-judge with hard sizing limits is a sensible safety pattern.","fetched_at":"2026-05-10","github_owner":"alanshen421","github_profile_fetched":true,"github_repo":"KalshiWeatherBot","github_user_url":"https://github.com/alanshen421","id":"alanshen421-weatherbot","lesson":null,"name":"alanshen421 / KalshiWeatherBot","name_full":"Alan Shen","show_repo_line":false,"stars":null},{"bio":"ML Engineer @ Scale","blog":"rlafuente.com","category":"quant-mm","description":"The most-cited reference for \"real\" market-making math on Kalshi. Implements multiple MM strategies in parallel, including an Avellaneda-Stoikov model. Dynamic market selection scores by volume and spread; a real-time terminal dashboard (curses) visualizes inventory. Strict deselect-cleanup invariant: stop worker \u2192 cancel all resting orders \u2192 verify cleanup before exit. Per-market 3-contract cap, 20 global. Inventory risk aversion increases as inventory approaches limits.","fetched_at":"2026-05-10","github_owner":"rodlaf","github_profile_fetched":true,"github_repo":"KalshiMarketMaker","github_user_url":"https://github.com/rodlaf","id":"rodlaf-marketmaker","lesson":"the cleanup invariant matters more than people think. A bot that crashes with resting orders on the book can take losses you never modeled. The \"verify cleanup\" step isn't paranoid; it's the difference between a controlled shutdown and a financial event.","name":"rodlaf / KalshiMarketMaker","name_full":"Rodney Lafuente-Mercado","stars":195},{"bio":"I write code sometimes.","blog":"nikhilnd.github.io","category":"quant-mm","description":"Probability-band MM around S&P close estimates. Originally a QuantSC student project from Spring 2023. Cleaner than its origin suggests; useful as an introductory MM reference.","fetched_at":"2026-05-10","github_owner":"nikhilnd","github_profile_fetched":true,"github_repo":"kalshi-market-making","github_user_url":"https://github.com/nikhilnd","id":"nikhilnd-mm","lesson":null,"name":"nikhilnd / kalshi-market-making","name_full":"Nikhil Deorkar","stars":null},{"bio":"you don't need a different story","blog":"https://juicetin.bearblog.dev","category":"quant-mm","description":"Public-facing repo of an algorithm the author actually ran on the platform. Smaller in scope than the others, but the fact that it represents real production code (not theoretical work) makes it valuable as a \"what does live MM code look like\" reference.","fetched_at":"2026-05-10","github_owner":"orangejuicetin","github_profile_fetched":true,"github_repo":"kalshi_market_maker","github_user_url":"https://github.com/orangejuicetin","id":"orangejuicetin-mm","lesson":null,"name":"orangejuicetin / kalshi_market_maker","name_full":"Justin Choi ","stars":null,"twitter":"orange_juicetin"},{"bio":"I don't predict the market, I model uncertainty","blog":"https://yllvaranwar.vercel.app/","category":"quant-mm","description":"Self-described \"enterprise-grade\" quant system with a Telegram control interface. Claims institutional-quality risk management. The Telegram-as-control-plane pattern shows up across many bots in this list \u2014 it's become the de facto remote management standard.","fetched_at":"2026-05-10","github_owner":"yllvar","github_profile_fetched":true,"github_repo":"Kalshi-Quant-TeleBot","github_user_url":"https://github.com/yllvar","id":"yllvar-quant-telebot","lesson":null,"name":"yllvar / Kalshi-Quant-TeleBot","name_full":"yllvar","stars":null},{"category":"arbitrage","description":"Cross-platform sports arbitrage between Kalshi and Polymarket. Written in Rust. The highest-starred arbitrage bot in the ecosystem.","fetched_at":"2026-05-10","github_profile_fetched":true,"github_user_url":"https://github.com/meloner3","id":"meloner3-poly-kalshi-sports","label_repo_as":"Strategy","lesson":"Rust shows up disproportionately in arbitrage code. The latency margins on cross-platform arb are tight enough that the language choice matters \u2014 Python's GIL becomes a real constraint when you're racing other bots for a 3\u00a2 spread.","name":"meloner3 / poly-kalshi-sports-bot","show_repo_line":false,"stars":131},{"bio":"Founder @ Glacier21\r\n\r\nhttps://Glacier21.com/","category":"arbitrage","description":"Watches 10,000+ markets across Polymarket and Kalshi for arbitrage opportunities. Includes a FastAPI web UI with real-time opportunities, a built-in backtesting engine, dual data mode (simulation vs real), and a kill switch.","fetched_at":"2026-05-10","github_owner":"ImMike","github_profile_fetched":true,"github_repo":"polymarket-arbitrage","github_user_url":"https://github.com/ImMike","id":"immike-poly-arb","lesson":"the dual data mode pattern (sim/real toggle behind one interface) is the right way to ship a bot. You can validate the same code path in simulation before flipping the switch \u2014 fewer \"well it worked in dev\" failures.","name":"ImMike / polymarket-arbitrage","name_full":"Mike","stars":82,"twitter":"DistrictCrypto"},{"category":"arbitrage","description":"Sentence-transformer semantic matching to find equivalent markets across platforms. Jaccard similarity + date/entity hints + optional LLM verification (12 parallel workers via Chutes.ai). PM2 process management; FastAPI + SSE for live updates.","fetched_at":"2026-05-10","github_profile_fetched":true,"github_user_url":"https://github.com/Rezzecup","id":"rezzecup-poly-kalshi-arb","label_repo_as":"Strategy","lesson":"semantic matching for cross-platform market identification is the under-appreciated half of arbitrage. Most arb bots match on string equality and miss obvious pairs. The semantic approach generalizes much better.","name":"Rezzecup / polymarket-kalshi-arbitrage-bot","name_full":"Rezzecup","show_repo_line":false,"stars":16,"twitter":"chain_sats"},{"category":"arbitrage","description":"Specifically targets Bitcoin 1-Hour Price markets between Polymarket and Kalshi \u2014 the most cross-listed contract type with the highest gap frequency.","fetched_at":"2026-05-10","github_owner":"CarlosIbCu","github_profile_fetched":true,"github_repo":"polymarket-kalshi-btc-arbitrage-bot","github_user_url":"https://github.com/CarlosIbCu","id":"carlosibcu-btc-arb","lesson":null,"name":"CarlosIbCu / polymarket-kalshi-btc-arbitrage-bot","name_full":"CarlosIbCu","stars":null},{"blog":"https://pmxt.dev","category":"arbitrage","description":"Auto-detects and executes arbitrage between Polymarket and Kalshi. Built on the pmxt.dev framework. The author has a useful companion blog post: \"How I built a risk-free arbitrage bot for Polymarket-Kalshi.\"","fetched_at":"2026-05-10","github_owner":"realfishsam","github_profile_fetched":true,"github_repo":"prediction-market-arbitrage-bot","github_user_url":"https://github.com/realfishsam","id":"realfishsam-pm-arb","lesson":null,"name":"realfishsam / prediction-market-arbitrage-bot","name_full":"Samuel EF. Tinnerholm","stars":null},{"category":"arbitrage","description":"General Kalshi arb bot. Smaller scope, useful as a reference implementation for arb basics.","github_owner":"vladmeer","github_profile_fetched":"404","github_repo":"kalshi-arbitrage-bot","id":"vladmeer-arb","lesson":null,"name":"vladmeer / kalshi-arbitrage-bot","stars":null},{"bio":"Hi I'm J. Luis, im passionate about building and iterating and scrapping and repeating\r\n\r\n\r\nBerkeley 25' CS + DS","blog":"suislanchez.com","category":"asset-class","description":"Trades Kalshi KXHIGH temperature markets plus Polymarket. Uses 31-member GFS ensemble forecasts via Open-Meteo plus BTC 5-min microstructure signals. 15% Kelly sizing capped at 5% of bankroll and $75\u2013100 per trade. React 3-column dashboard (signals, weather, trades) with FastAPI backend; Brier score tracking; simulation mode with virtual bankroll and equity curves. Reported max profit of $1.8k.","fetched_at":"2026-05-10","github_profile_fetched":true,"github_user_url":"https://github.com/suislanchez","id":"suislanchez-weather","lesson":"ensemble forecasts crush single-model forecasts on Kalshi weather markets. The 31-member GFS ensemble is free via Open-Meteo. The Brier score tracking inside the dashboard \u2014 explicit measurement of forecast calibration \u2014 is what separates serious weather bots from beginners.","name":"suislanchez / polymarket-kalshi-weather-bot","name_full":"Luis Sanchez","show_repo_line":false,"stars":116,"subcategory":"weather","twitter":"iamsuislanchez"},{"category":"asset-class","description":"NWS/NOAA weather edge trading. Forecast horizon weighting (near-term 1.0, 3-day 0.75, 7-day 0.45) with regional NWS accuracy discount. Fixed $25 per position; Telegram alerts.","github_profile_fetched":"404","id":"cobra88giga-weather","lesson":"the horizon-weighting scheme (closer forecast = more confidence) approximates the empirical accuracy decay of point forecasts. It's a simple heuristic that captures most of what a more complex Bayesian update would do.","name":"cobra88giga / kalshi-weather-bot","show_repo_line":false,"stars":71,"subcategory":"weather"},{"bio":"I am a senior at Duke studying CS. Passionate in utilizing AI/ML and software engineering to facilitate human productivity and automate inefficient processes.","blog":"https://edmond-niu.dev/","category":"asset-class","description":"Custom temporal transformer ensemble with XGBoost. XGBoost achieves 1.55\u00b0F MAE; the custom temporal transformer achieves 1.0\u00b0F MAE. Optuna Bayesian hyperparameter search. Converts continuous forecasts to integer probability mass functions across bracket boundaries. Fractional Kelly with a 2% bankroll cap. Full frontend dashboard with auth.","fetched_at":"2026-05-10","github_profile_fetched":true,"github_user_url":"https://github.com/EddieTGH","id":"eddietgh-weather","lesson":"the accuracy ceiling on day-of weather forecasts is around 1\u00b0F MAE for the best ML models. That's tight enough to often pick the right 2\u00b0F bracket. If you're going to compete with this kind of bot, you need either a better model (hard) or different markets (easier).","name":"EddieTGH / kalshi-weather-predictor","name_full":"Edmond Niu","show_repo_line":false,"stars":null,"subcategory":"weather"},{"bio":"I currently build thinking systems that imitate understanding","blog":"https://akshatgurbuxani.github.io/","category":"asset-class","description":"Daily climate event forecasting that maps directly into trades.","fetched_at":"2026-05-10","github_owner":"akshatgurbuxani","github_profile_fetched":true,"github_repo":"Kalshi-Weather-Forecasting-Financial-Trading","github_user_url":"https://github.com/akshatgurbuxani","id":"akshat-weather","lesson":null,"name":"akshatgurbuxani / Kalshi-Weather-Forecasting-Financial-Trading","name_full":"Akshat Gurbuxani","stars":null,"subcategory":"weather"},{"category":"asset-class","description":"Pre-positions 15\u201360 minutes before CPI, Fed, NFP, and GDP releases using Bloomberg consensus deviation signals. Exits within 10 minutes after each release. $40 per position. Telegram alerts before entry, at release, and on exit. Historical resolution pattern matching.","github_profile_fetched":"404","id":"cobrashadow88-economic","lesson":"the pre-position-then-exit-fast pattern avoids the post-release reprice race entirely. You're trading the gap between consensus drift and market positioning, not racing the print itself. The discipline of exiting within 10 minutes is what makes this strategy work \u2014 most traders hold too long and give back the edge.","name":"cobrashadow88 / kalshi-economic-trader","show_repo_line":false,"stars":107,"subcategory":"economics"},{"bio":"Data Scientist/Researcher/Statistician","blog":"https://ayush-hb.com/","category":"asset-class","description":"BTC trader on 15-minute and 1-hour intervals. Self-described as \"risk-averse and profitable.\" Smaller in scope than the dual-strategy bots below, but the focused approach is refreshing.","fetched_at":"2026-05-10","github_owner":"Bh-Ayush","github_profile_fetched":true,"github_repo":"Kalshi-CryptoBot","github_user_url":"https://github.com/Bh-Ayush","id":"bh-ayush-cryptobot","lesson":null,"name":"Bh-Ayush / Kalshi-CryptoBot","name_full":"Ayush Bharadwaj","stars":null,"subcategory":"crypto"},{"category":"asset-class","description":"XGBoost model trained on 70k historical BTC candles via Kraken WebSocket. Dual SWING/SCALPER strategy. Kelly with volatility-regime overlay. Concurrent monitoring for stop-loss, take-profit, flash-crash, and time-to-expiry. systemd units plus a custom watchdog. Circuit-breaker events via Telegram.","github_profile_fetched":"404","id":"danielsilvaperez-trading","lesson":"the dual-strategy pattern \u2014 different time horizons, different sizing, same execution \u2014 is a good way to extract value from a single underlying without doubling infrastructure. The circuit-breaker layer is non-optional for any bot that touches real money.","name":"danielsilvaperez / kalshi-trading-bot","show_repo_line":false,"stars":null,"subcategory":"crypto"},{"bio":"Author of The Quant's Playbook\r\n\r\nQuantitative Finance, Sports Betting Algorithms, and more","blog":"https://quantgalore.substack.com/","category":"asset-class","description":"S&P 500 daily bracket trading. Tight scope, well-executed.","fetched_at":"2026-05-10","github_profile_fetched":true,"github_user_url":"https://github.com/quantgalore","id":"quantgalore-trading","lesson":null,"name":"quantgalore / kalshi-trading","name_full":"Quant Galore","show_repo_line":false,"stars":36,"subcategory":"crypto"},{"bio":"im noob2.0","category":"asset-class","description":"BTC 15-minute momentum + orderbook skew + OpenClaw AI enrichment. DRY_RUN mode; configurable stop-loss and take-profit cents per position. The orderbook skew signal is under-explored in this space and worth studying.","fetched_at":"2026-05-10","github_profile_fetched":true,"github_user_url":"https://github.com/Razzleberryss","id":"razzleberryss-astrotick","lesson":null,"name":"Razzleberryss / AstroTick","name_full":"Razzleberryss","show_repo_line":false,"stars":10,"subcategory":"crypto"},{"category":"asset-class","description":"NFL, NBA, MLB, NHL game outcomes. Compares Kalshi prices vs sportsbook implied probabilities. Injury feed integration; line movement detection. $30 per entry; $300 daily cap; take-profit at 0.85; stop-loss at 0.08; max 8 open positions.","github_profile_fetched":"404","id":"5000neoliobtc-sports","lesson":"the sportsbook-as-reference pattern is the canonical sports edge. Sportsbook lines move faster than Kalshi for many markets; if you can detect a line move and reprice on Kalshi within seconds, you have a real edge \u2014 at least until the bot population catches up.","name":"5000neoliobtc / kalshi-sports-bot","show_repo_line":false,"stars":95,"subcategory":"sports"},{"category":"asset-class","description":"Seven distinct paper-trading strategies running simultaneously on BTC markets. Designed as an educational reference, and that's exactly what it does well.","fetched_at":"2026-05-10","github_owner":"DeweyMarco","github_profile_fetched":true,"github_repo":"simple-kalshi-bot","github_user_url":"https://github.com/DeweyMarco","id":"deweymarco-simple","lesson":"seven strategies in paper mode, simultaneously, is a great way to figure out which approaches generate which kinds of P&L profiles before you commit real money. We use a similar pattern in our own framework.","name":"DeweyMarco / simple-kalshi-bot","name_full":"Marco Dewey","stars":null,"subcategory":"multi"},{"bio":"Skilled in the areas of continuous integration, continuous delivery, cloud infrastructure, test automation and platforms.","blog":"www.allengeer.com","category":"asset-class","description":"General Python algo bot \u2014 market analysis, position management, risk controls. A reasonable starting framework if you're building from scratch.","fetched_at":"2026-05-10","github_owner":"allengeer","github_profile_fetched":true,"github_repo":"kalshihub","github_user_url":"https://github.com/allengeer","id":"allengeer-kalshihub","lesson":null,"name":"allengeer / kalshihub","name_full":"Allen Geer","stars":null,"subcategory":"multi"},{"category":"sentiment-rl","description":"Monitors Twitter/X, Reddit, and Telegram with five-dimension scoring (source count, velocity, authority, keyword match depth, momentum duration). NLP transformer classifier tuned on prediction-market language. Author claims 5\u201314 minute lead time before Kalshi repricing. Instant Telegram alerts with score breakdown.","github_profile_fetched":"404","id":"foxstacker5000-sentiment","lesson":"the multi-dimensional scoring (vs. a single sentiment number) is the right shape for sentiment signals. A 5-source spike with high authority is genuinely different from a 50-source spike from low-authority accounts; collapsing both to \"high sentiment\" loses the distinction.","name":"foxstacker5000 / kalshi-sentiment-bot","show_repo_line":false,"stars":26},{"category":"sentiment-rl","description":"Bayesian model that distinguishes \"fake\" YES price spikes (low volume + widening spread) from \"real\" repricings (high volume + tightening spread), then fades the fakes. Enters NO when posterior mu > 0.7. Includes a CSV-based backtester tracking price/volume/spread deltas.","fetched_at":"2026-05-10","github_profile_fetched":true,"github_user_url":"https://github.com/andrewkni","id":"andrewkni-bayesian","lesson":"the volume-and-spread joint signal is much stronger than either alone for distinguishing manipulation from real moves. This is the kind of strategy that works only because most participants react to price alone.","name":"andrewkni / bayesian-spike-detector","name_full":"Andrew Ni","show_repo_line":false,"stars":null},{"bio":"MS AI @ Katz, Yeshiva University | Ex Sr. SWE @ Intangles.ai | Ex SWE @ UBS","blog":"http://jpratham.info/","category":"sentiment-rl","description":"DQN agent for hourly BTC threshold markets. Gymnasium-compatible RL environment; multi-day backtesting with policy comparison (random vs. baseline vs. DQN); Streamlit GUI.","fetched_at":"2026-05-10","github_profile_fetched":true,"github_user_url":"https://github.com/Pajamajoker","id":"pajamajoker-rl","lesson":"the RL framing for prediction markets is interesting but reward-shaping is hard. The author's policy comparison framework (always benchmark against a random baseline) is a useful discipline that many ML approaches skip.","name":"Pajamajoker / reinforcement-learning-for-kalshi-trading","name_full":"Prathamesh Joshi","show_repo_line":false,"stars":null},{"category":"tools","description":"Model Context Protocol server with 20+ tools for Claude Code/Desktop integration. Weather forecasting, ensemble analysis, position drift monitoring, safety controls. Designed for conversational trading with Claude.","fetched_at":"2026-05-10","github_profile_fetched":true,"github_user_url":"https://github.com/alexandermazza","id":"alexandermazza-mcp","lesson":"the MCP-as-bot-control-plane pattern is genuinely new. It lets you describe a strategy in natural language and have the LLM operate the trading tools. The safety controls inside the MCP are non-negotiable \u2014 a hallucinating LLM with raw API access is exactly as dangerous as it sounds.","name":"alexandermazza / kalshi-trading-mcp","name_full":"Alex Mazza","show_repo_line":false,"stars":2},{"bio":"I make Python for Finance tutorials on YouTube.","blog":"https://youtube.com/@parttimelarry","category":"tools","description":"Kalshi API + Perplexity Sonar API for research. Streamlit UI. Useful as a \"research assistant\" rather than a fully automated bot.","fetched_at":"2026-05-10","github_profile_fetched":true,"github_user_url":"https://github.com/hackingthemarkets","id":"hackingthemarkets-assistant","lesson":null,"name":"hackingthemarkets / prediction-market-assistant","name_full":"Part Time Larry","show_repo_line":false,"stars":50,"twitter":"PartTimeLarry"},{"category":"tools","description":"Fed implied rate curve visualization and historical comparisons. Jupyter-based; not a bot, but a strong analytics reference for anyone trading Fed markets.","fetched_at":"2026-05-10","github_profile_fetched":true,"github_user_url":"https://github.com/carllman13","id":"carllman13-kalshi-trading","lesson":null,"name":"carllman13 / Kalshi_Trading","show_repo_line":false,"stars":17},{"category":"tools","description":"NBA Kalshi vs. DraftKings backtest covering 876 games and 10 strategy tests. The methodology of running multiple strategy variants over the same historical window is exactly the kind of comparative work this space needs more of.","fetched_at":"2026-05-10","github_profile_fetched":true,"github_user_url":"https://github.com/cameronbrock4-arch","id":"cameronbrock4-dashboard","lesson":null,"name":"cameronbrock4-arch / kalshi-dashboard","show_repo_line":false,"stars":null},{"category":"tools","description":"Cross-platform scanner across Kalshi, Polymarket, and DraftKings for NFL, NBA, MLB, and NHL props. Confidence-scored alerts. The three-platform comparison (vs. the more common two) catches mispricings the bilateral arb bots miss.","fetched_at":"2026-05-10","github_profile_fetched":true,"github_user_url":"https://github.com/abudnick8","id":"abudnick8-prop-edge","lesson":null,"name":"abudnick8 / prop-edge","show_repo_line":false,"stars":null},{"category":"commercial","description":"Our own platform. Web-based no-code bot builder, signal system, encrypted credential storage, sub-50ms order execution. We built it because every open-source option requires maintaining infrastructure, and many traders want the automation without the engineering. Honest disclosure: we're listed here so the catalog is complete; pick the option that fits your needs.","id":"bot-for-kalshi","lesson":null,"name":"Bot for Kalshi","show_repo_line":false,"stars":null},{"category":"commercial","description":"Weather markets specifically. Runs trades through a 62-member hybrid ensemble (NOAA GFS plus AI models). The ensemble size is roughly twice what most open-source weather bots use; it's also a paid product, which is the tradeoff.","id":"predict-and-profit","lesson":null,"name":"Predict & Profit","show_repo_line":false,"stars":null},{"category":"commercial","description":"NOAA-data-driven weather market signals. Data tool rather than a bot \u2014 you still need execution.","id":"kalshi-weather-edge","lesson":null,"name":"Kalshi Weather Edge","show_repo_line":false,"stars":null},{"category":"commercial","description":"Data-backed prediction-market analysis for weather. Similar profile.","id":"weather-edge-finder","lesson":null,"name":"Weather Edge Finder","show_repo_line":false,"stars":null},{"category":"commercial","description":"VPS hosting plus Kalshi bot setup tutorial. Useful if you're running open-source bots and don't want to manage your own infrastructure.","id":"tradingvps","lesson":null,"name":"TradingVPS","show_repo_line":false,"stars":null}],"categories":[{"display":"AI & LLM-Driven Bots","intro":"The newest category. These bots use large language models to process unstructured information \u2014 news articles, research reports, social media \u2014 and turn it into trading signals. They tend to be experimental and resource-hungry but capable of strategies that pure quantitative approaches can't easily express.","key":"ai-llm"},{"display":"Quantitative & Market Making","intro":"The professional side of the ecosystem. These bots use textbook quantitative finance techniques \u2014 many adapted from equity and futures markets \u2014 and apply them to Kalshi's binary contract structure.","key":"quant-mm"},{"display":"Arbitrage Bots","intro":"Cross-platform arbitrage between Kalshi and Polymarket is the largest sub-genre by repo count. The easy arbs in liquid markets are heavily competed; bots in this category increasingly target sports and niche markets where pricing efficiency is lower.","key":"arbitrage"},{"display":"Asset-Class Specific Bots","intro":"The largest category, organized around specific market types. These bots embed domain knowledge \u2014 weather forecasting, crypto microstructure, sports analytics \u2014 into trading logic.","key":"asset-class","subcategories":[{"display":"Weather","key":"weather"},{"display":"Economics","key":"economics"},{"display":"Crypto","key":"crypto"},{"display":"Sports","key":"sports"},{"display":"Multi-strategy / general","key":"multi"}]},{"display":"Sentiment & Reinforcement Learning","intro":"Smaller category, but the most experimental approaches live here. These bots try to extract edge from harder-to-quantify signals \u2014 social sentiment, market-microstructure anomalies, learned policies.","key":"sentiment-rl"},{"display":"Tools & Infrastructure","intro":"Not bots themselves, but infrastructure that bots and traders depend on.","key":"tools"},{"display":"Commercial Platforms","intro":"Not open-source, but part of the landscape any developer should know.","key":"commercial","type":"commercial"}],"counts":{"commercial":5,"open_source_bots":35,"sdks":10},"license":"CC-BY-4.0","sdks":[{"language":"Python","notes":"The official SDK; covers everything","repo":"kalshi-python (official)","stars":null},{"language":"Rust","notes":"50+ endpoints + WebSocket, 31\u2605","repo":"arvchahal/kalshi-rs","stars":31},{"language":"Rust","notes":"Alternative Rust client, 55\u2605","repo":"dpeachpeach/kalshi-rust","stars":55},{"language":"Go","notes":"10\u2605, clean API surface","repo":"ammario/kalshi","stars":10},{"language":"Go","notes":"Alternative Go option","repo":"fsctl/go-kalshi","stars":null},{"language":"Go","notes":"Newer Go client","repo":"arvindh-manian/kalshigo","stars":null},{"language":"C++","notes":"Header-only WebSocket library","repo":"yutaoz/kalshilib-ws","stars":null},{"language":"C++","notes":"General C++ SDK","repo":"RobertLD/kalshi-cpp-sdk","stars":null},{"language":"C#","notes":"5\u2605, .NET ecosystem","repo":"hurley451/KalshiSharp","stars":5},{"language":"TypeScript","notes":"Direct REST + WebSocket implementations","repo":"multiple","stars":null}],"source":"https://botforkalshi.com/blog/open-source-kalshi-bot-ecosystem","updated":"2026-05-10","version":"2026-05-10"}