[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-76149":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":10,"languages":10,"totalLinesOfCode":10,"stars":11,"forks":12,"watchers":13,"openIssues":13,"contributorsCount":14,"subscribersCount":14,"size":14,"stars1d":15,"stars7d":16,"stars30d":17,"stars90d":14,"forks30d":14,"starsTrendScore":18,"compositeScore":19,"rankGlobal":10,"rankLanguage":10,"license":20,"archived":21,"fork":21,"defaultBranch":22,"hasWiki":21,"hasPages":21,"topics":23,"createdAt":10,"pushedAt":10,"updatedAt":37,"readmeContent":38,"aiSummary":39,"trendingCount":14,"starSnapshotCount":14,"syncStatus":40,"lastSyncTime":41,"discoverSource":42},76149,"awesome-trading-agents","LLMQuant\u002Fawesome-trading-agents","LLMQuant","Curated list of LLM-driven trading agents, MCP servers, and agent skills for market research, strategy, and execution.","",null,208,26,1,0,16,30,76,48,4.29,"Creative Commons Zero v1.0 Universal",false,"master",[24,25,26,27,28,29,30,31,32,33,34,35,36],"agent-skills","agentic-ai","ai-trading","awesome","awesome-list","claude-skills","financial-ai","fintech","llm-agents","mcp","mcp-servers","prediction-markets","trading-agents","2026-06-12 02:03:40","\u003C!--lint disable awesome-heading double-link-->\n\n\u003Cdiv align=\"center\">\n\n\u003Cimg src=\"assets\u002Fheader-generated-v2.png\" alt=\"Awesome Trading Agents — The Trading Agentic Stack\" width=\"760\" \u002F>\n\n\u003Cp>\u003Cstrong>English\u003C\u002Fstrong> · \u003Ca href=\"README.zh-CN.md\">简体中文\u003C\u002Fa>\u003C\u002Fp>\n\n\u003Cp>\n  \u003Ca href=\"https:\u002F\u002Fawesome.re\">\u003Cimg src=\"https:\u002F\u002Fawesome.re\u002Fbadge.svg\" alt=\"Awesome\" \u002F>\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fgithub.com\u002FLLMQuant\u002Fawesome-trading-agents\u002Fstargazers\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fstars\u002FLLMQuant\u002Fawesome-trading-agents?style=flat\" alt=\"GitHub stars\" \u002F>\u003C\u002Fa>\n  \u003Ca href=\"LICENSE\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLicense-CC0%201.0-lightgrey.svg\" alt=\"License: CC0-1.0\" \u002F>\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Ftopics\u002Ftrading-agents\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Ftopics-trading--agents%20%C2%B7%20mcp--servers%20%C2%B7%20agent--skills-blue\" alt=\"Topics\" \u002F>\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fgithub.com\u002FLLMQuant\u002Fawesome-trading-agents\u002Fcommits\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Flast-commit\u002FLLMQuant\u002Fawesome-trading-agents\" alt=\"Last commit\" \u002F>\u003C\u002Fa>\n  \u003Ca href=\"README.zh-CN.md\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fbilingual-zh%20%C2%B7%20en-708090\" alt=\"Bilingual\" \u002F>\u003C\u002Fa>\n\u003C\u002Fp>\n\n\u003C\u002Fdiv>\n\nAwesome Trading Agents collects open-source projects where LLMs help research markets, make trading decisions, or connect agents to market data and execution tools. The list focuses on three building blocks: Agents, MCPs, and Skills. It does not try to cover classic quant libraries, time-series models, or reinforcement-learning trading bots; those are better served by [`georgezouq\u002Fawesome-ai-in-finance`](https:\u002F\u002Fgithub.com\u002Fgeorgezouq\u002Fawesome-ai-in-finance) and [`wilsonfreitas\u002Fawesome-quant`](https:\u002F\u002Fgithub.com\u002Fwilsonfreitas\u002Fawesome-quant). Entries are selected for public code or artifacts, clear LLM-driven behavior, recent activity, useful documentation, a distinct role, and visible adoption. Stewarded by the [LLMQuant](https:\u002F\u002Fllmquant.com) community.\n\n> [!TIP]\n> **If you only read three:**\n>\n> - **Agents** — [TauricResearch\u002FTradingAgents](#agents-tradingagents) · [virattt\u002Fai-hedge-fund](#agents-ai-hedge-fund) · [HKUDS\u002FAI-Trader](#agents-ai-trader)\n> - **MCPs** — [alpacahq\u002Falpaca-mcp-server](#mcps-alpaca) · [krakenfx\u002Fkraken-cli](#mcps-kraken-cli) · [financial-datasets\u002Fmcp-server](#mcps-financial-datasets)\n> - **Skills** — [tradermonty\u002Fclaude-trading-skills](#skills-claude-trading-skills) · [himself65\u002Ffinance-skills](#skills-finance-skills) · [RKiding\u002FAwesome-finance-skills](#skills-alphaear)\n\n> [!NOTE]\n> Dates are not shown after every item. We still check recent activity before adding or updating a project; the README only keeps details that help readers choose a project, such as official status, forks, or useful pairings.\n\n\u003C!--lint disable awesome-toc-->\n## Contents\n\n- [**Agents**](#agents)\n  - [Multi-agent trading systems](#agents-multi-agent)\n  - [Single-agent end-to-end traders](#agents-single-agent)\n  - [Research \u002F equity-research copilots](#agents-research-copilots)\n  - [Real-money \u002F competition experiments](#agents-real-money)\n  - [Prediction-market specialists](#agents-prediction-market)\n  - [Benchmarks & evaluations](#agents-benchmarks)\n  - [Strategy coding \u002F self-improving agents](#agents-strategy-coding)\n- [**MCPs**](#mcps)\n  - [Market data \u002F data providers](#mcps-market-data)\n  - [Brokerage \u002F exchange trading](#mcps-brokerage)\n  - [Research tools \u002F analysis](#mcps-research-tools)\n  - [TradingView bridge](#mcps-tradingview)\n  - [Prediction markets](#mcps-prediction-market)\n  - [Strategy \u002F backtesting platforms](#mcps-backtesting)\n- [**Skills**](#skills)\n  - [Equity research](#skills-equity-research)\n  - [Crypto \u002F DeFi \u002F on-chain](#skills-crypto)\n  - [Strategy coding & backtesting](#skills-strategy-coding)\n  - [Brokerage execution & portfolio](#skills-brokerage)\n- [**Resources**](#resources)\n  - [Papers](#resources-papers)\n  - [Learn](#resources-learn)\n- [Related awesome lists](#related-awesome-lists)\n\n\u003C!--lint enable awesome-toc-->\n\n\u003Ca id=\"agents\">\u003C\u002Fa>\n## Agents\n\n\u003Cp align=\"center\">\n  \u003Cimg src=\"assets\u002Fsection-agents.png\" alt=\"Agents section header\" width=\"760\" \u002F>\n\u003C\u002Fp>\n\nAgents are projects where an LLM is part of the actual research or trading decision. This includes analyst teams, single-agent traders, research copilots, live trading experiments, benchmarks, and tools that write or improve strategies. The TradingAgents forks are listed at the same level as the original project so the section stays easy to scan.\n\n\u003Ca id=\"agents-multi-agent\">\u003C\u002Fa>\n### Multi-agent trading systems\n\n\u003Ca id=\"agents-tradingagents\">\u003C\u002Fa>\n- [TauricResearch\u002FTradingAgents](https:\u002F\u002Fgithub.com\u002FTauricResearch\u002FTradingAgents) - Multi-agent trading framework where analysts, bull\u002Fbear researchers, a trader, risk control, and a portfolio manager debate before making a decision; built with LangGraph.\n- [hsliuping\u002FTradingAgents-CN](https:\u002F\u002Fgithub.com\u002Fhsliuping\u002FTradingAgents-CN) - Chinese-localised TradingAgents fork tuned for A-shares; Tushare \u002F AkShare data sources + Chinese-language reports + A-share regulatory context. *(← fork of TauricResearch\u002FTradingAgents.)*\n- [KylinMountain\u002FTradingAgents-AShare](https:\u002F\u002Fgithub.com\u002FKylinMountain\u002FTradingAgents-AShare) - A-share rewrite; 15 agents + visual UI + OpenClaw \u002F Claude Code integration + one-click Docker deploy. *(← fork of TauricResearch\u002FTradingAgents.)*\n- [oficcejo\u002Faiagents-stock](https:\u002F\u002Fgithub.com\u002Foficcejo\u002Faiagents-stock) - A-share multi-agent analyst team with dragon-and-tiger list tracking, sector-rotation alerts, and a miniqmt execution hook. *(← inspired by TradingAgents.)*\n\u003Ca id=\"agents-ai-trader\">\u003C\u002Fa>\n- [HKUDS\u002FAI-Trader](https:\u002F\u002Fgithub.com\u002FHKUDS\u002FAI-Trader) - \"Agent-native trading platform\"; any AI agent (OpenClaw \u002F nanobot \u002F Claude Code \u002F Codex \u002F Cursor) registers via SKILL.md and trades live on AI4trade.ai; multi-asset + copy-trading + cross-platform sync.\n- [ValueCell-ai\u002Fvaluecell](https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell) - Community finance workspace with research, strategy, and news agents; connects to Binance, OKX, and Hyperliquid; includes macOS and Windows desktop apps.\n- [AI4Finance-Foundation\u002FFinRobot](https:\u002F\u002Fgithub.com\u002FAI4Finance-Foundation\u002FFinRobot) - AI4Finance Foundation's open-source finance AI agent platform; useful for academic-style stock research, market forecasting, and report generation.\n\u003Ca id=\"agents-vibe-trading\">\u003C\u002Fa>\n- [HKUDS\u002FVibe-Trading](https:\u002F\u002Fgithub.com\u002FHKUDS\u002FVibe-Trading) - Personal multi-agent finance workspace from HKUDS Lab; bundles Skills, MCP tools, and swarm presets across A-shares, HK, US, crypto, futures, and forex.\n- [brokermr810\u002FQuantDinger](https:\u002F\u002Fgithub.com\u002Fbrokermr810\u002FQuantDinger) - Open-source AI quant-trading platform; combines multi-agent research, backtesting, live trading, and multi-exchange routing.\n- [The-Swarm-Corporation\u002FAutoHedge](https:\u002F\u002Fgithub.com\u002FThe-Swarm-Corporation\u002FAutoHedge) - \"Spin up an autonomous hedge fund in minutes\"; applies the Swarms framework to market analysis, risk, and execution; CLI \u002F SDK first.\n\u003Ca id=\"agents-langalpha\">\u003C\u002Fa>\n- [ginlix-ai\u002FLangAlpha](https:\u002F\u002Fgithub.com\u002Fginlix-ai\u002FLangAlpha) - \"Claude Code for finance\"; LangChain + LangGraph multi-agent investment workbench; integrates Agents · MCPs · Skills in one repo.\n- [ygwyg\u002FMAHORAGA](https:\u002F\u002Fgithub.com\u002Fygwyg\u002FMAHORAGA) - TypeScript crypto-trading agent focused on social sentiment analysis and adaptive learning; useful if you want a TypeScript implementation.\n- [FinStep-AI\u002FContestTrade](https:\u002F\u002Fgithub.com\u002FFinStep-AI\u002FContestTrade) - Multi-agent trading system where agents compete internally before one view is selected for the final decision.\n- [51bitquant\u002Fai-hedge-fund-crypto](https:\u002F\u002Fgithub.com\u002F51bitquant\u002Fai-hedge-fund-crypto) - Crypto-focused fork of virattt\u002Fai-hedge-fund; multi-timeframe analysis + strategy ensemble + crypto market-data access.\n\u003Ca id=\"agents-prism-insight\">\u003C\u002Fa>\n- [dragon1086\u002Fprism-insight](https:\u002F\u002Fgithub.com\u002Fdragon1086\u002Fprism-insight) - Korean-market-focused multi-agent stock-analysis and trading system; built-in MCP integration.\n- [Tomortec\u002FCryptoTradingAgents](https:\u002F\u002Fgithub.com\u002FTomortec\u002FCryptoTradingAgents) - Multi-agent LLM crypto-trading framework; applies the TradingAgents idea to crypto trading.\n- [EthanAlgoX\u002FLLM-TradeBot](https:\u002F\u002Fgithub.com\u002FEthanAlgoX\u002FLLM-TradeBot) - Multi-agent crypto-trading system; Binance real-time execution + adaptive strategy switching; combines ideas from TradingAgents and nof1.ai.\n- [huygiatrng\u002FAlpacaTradingAgent](https:\u002F\u002Fgithub.com\u002Fhuygiatrng\u002FAlpacaTradingAgent) - TradingAgents-style multi-agent framework connected to Alpaca for US-equity trading. *(→ pairs with: [alpacahq\u002Falpaca-mcp-server](#mcps-alpaca).)*\n- [Yaolinwang\u002FAITD](https:\u002F\u002Fgithub.com\u002FYaolinwang\u002FAITD) - \"AI Trading Agent for Everyone\"; multi-agent project designed for retail users.\n- [flash131307\u002Fmulti-agent-investment](https:\u002F\u002Fgithub.com\u002Fflash131307\u002Fmulti-agent-investment) - Multi-agent equity-research system that lets LLM agents gather evidence, then uses a separate math layer to produce BUY \u002F NEUTRAL \u002F SELL.\n\u003Ca id=\"agents-oracle3\">\u003C\u002Fa>\n- [YichengYang-Ethan\u002Foracle3](https:\u002F\u002Fgithub.com\u002FYichengYang-Ethan\u002Foracle3) - Multi-venue (Kalshi \u002F Polymarket \u002F Solana) prediction-market autonomous agent; Wang-Transform pricing + Kelly criterion + cross-venue arbitrage.\n- [Ganador1\u002FFenixAI_tradingBot](https:\u002F\u002Fgithub.com\u002FGanador1\u002FFenixAI_tradingBot) - LangGraph + Ollama + CrewAI autonomous trading agent; local-LLM first.\n- [ryan-yuuu\u002Fcrypto-trading-arena](https:\u002F\u002Fgithub.com\u002Fryan-yuuu\u002Fcrypto-trading-arena) - Open-source crypto-trading arena; Claude \u002F Claude Code agents compete head-to-head on live crypto data.\n- [FareedKhan-dev\u002Fmulti-agent-trading-system](https:\u002F\u002Fgithub.com\u002FFareedKhan-dev\u002Fmulti-agent-trading-system) - \"Deep Thinking Trading System\" tutorial implementation; beginner-friendly multi-agent example design.\n- [Tanglumy\u002FFinance-Bro](https:\u002F\u002Fgithub.com\u002FTanglumy\u002FFinance-Bro) - Persona-styled finance \"bro\" trading-and-investment agent; uses the persona as the main interaction style.\n- [liangdabiao\u002Fautogen-financial-analysis](https:\u002F\u002Fgithub.com\u002Fliangdabiao\u002Fautogen-financial-analysis) - Microsoft AutoGen-based multi-agent financial-analysis system; VaR \u002F Monte Carlo \u002F factor models \u002F visualization integration.\n\n> [!NOTE]\n> Also useful here: [guangxiangdebizi\u002FTradingAgents-MCPmode](#mcps-tradingagents-mcpmode) turns TradingAgents-style research into MCP tools. The full entry is in MCPs · Research tools \u002F analysis.\n\n> Also see: [chrisworsey55\u002Fatlas-gic](#agents-atlas-gic) is listed under single-agent traders, but it is relevant here because it replaces debate with continuous self-research.\n\n\u003Ca id=\"agents-single-agent\">\u003C\u002Fa>\n### Single-agent end-to-end traders\n\n\u003Ca id=\"agents-ai-hedge-fund\">\u003C\u002Fa>\n- [virattt\u002Fai-hedge-fund](https:\u002F\u002Fgithub.com\u002Fvirattt\u002Fai-hedge-fund) - Widely forked LLM-driven equity-trading repo; analyst personas (Buffett \u002F Munger \u002F Cathie Wood) propose, the portfolio manager decides.\n- [TraderAlice\u002FOpenAlice](https:\u002F\u002Fgithub.com\u002FTraderAlice\u002FOpenAlice) - \"Your one-person Wall Street\"; single agent covering research → entry → hold → exit; Claude Agent SDK + Trading-as-Git approval workflow + cross-asset UTA account design.\n\u003Ca id=\"agents-atlas-gic\">\u003C\u002Fa>\n- [chrisworsey55\u002Fatlas-gic](https:\u002F\u002Fgithub.com\u002Fchrisworsey55\u002Fatlas-gic) - General Intelligence Capital's self-improving trading agent; focuses on continuous self-research rather than agent debate.\n- [Gajesh2007\u002Fai-trading-agent](https:\u002F\u002Fgithub.com\u002FGajesh2007\u002Fai-trading-agent) - AI trading agent on Hyperliquid; single-LLM-driven execution; shows direct Hyperliquid integration.\n- [kweinmeister\u002Fagentic-trading](https:\u002F\u002Fgithub.com\u002Fkweinmeister\u002Fagentic-trading) - Trading-workflow example built on Google ADK + A2A interop; an alternative implementation outside LangGraph.\n- [danilobatson\u002Fai-trading-agent-gemini](https:\u002F\u002Fgithub.com\u002Fdanilobatson\u002Fai-trading-agent-gemini) - LunarCrush social-sentiment + Google Gemini crypto-trading agent; built with Next.js 15, Inngest, and Supabase.\n- [alsk1992\u002FCloddsBot](https:\u002F\u002Fgithub.com\u002Falsk1992\u002FCloddsBot) - Open-source AI trader across 1000+ markets, including Polymarket, Kalshi, Binance, Hyperliquid, Solana, and several EVM chains.\n- [hkirat\u002Fai-trading-agent](https:\u002F\u002Fgithub.com\u002Fhkirat\u002Fai-trading-agent) - \"Trade using LLMs\"; minimal TypeScript demo from Harkirat Singh; common on-ramp for TS learners.\n\n\u003Ca id=\"agents-research-copilots\">\u003C\u002Fa>\n### Research \u002F equity-research copilots\n\n- [ZhuLinsen\u002Fdaily_stock_analysis](https:\u002F\u002Fgithub.com\u002FZhuLinsen\u002Fdaily_stock_analysis) - Daily LLM-driven stock-screening dashboard; multi-channel push (WeChat \u002F Feishu \u002F Telegram \u002F Discord \u002F Slack \u002F email); 11 built-in strategies + agent stock-Q&A; deploy-by-GitHub-Actions.\n- [AmadeusGB\u002Falpha-arena](https:\u002F\u002Fgithub.com\u002FAmadeusGB\u002Falpha-arena) - Live AI-agent competition and research platform; uses real-market conditions to improve agents.\n- [TNT-Likely\u002FPanWatch](https:\u002F\u002Fgithub.com\u002FTNT-Likely\u002FPanWatch) - PanWatch \u002F \"盯盘侠\"; AI-driven stock-monitoring assistant; multi-account positions + agent analysis + PWA mobile.\n- [HKUSTDial\u002FDeepEar](https:\u002F\u002Fgithub.com\u002FHKUSTDial\u002FDeepEar) - DeepEar \u002F \"顺风耳\"; HKUSTDial's open-source deep-research and signal-tracking framework; joint multimodal news + price tracking.\n- [kamathhrishi\u002Ffinance-agent](https:\u002F\u002Fgithub.com\u002Fkamathhrishi\u002Ffinance-agent) - Earnings-call \u002F SEC-filing \u002F news Q&A agent; clean RAG-over-disclosures implementation.\n\n> Also relevant: [ginlix-ai\u002FLangAlpha](#agents-langalpha) and [oficcejo\u002Faiagents-stock](#agents-tradingagents) both include research-copilot screens, but their main entries stay with the multi-agent systems they belong to.\n\n\u003Ca id=\"agents-real-money\">\u003C\u002Fa>\n### Real-money \u002F competition experiments\n\n\u003Ca id=\"agents-llm-trading-lab\">\u003C\u002Fa>\n- [LuckyOne7777\u002FLLM-Trading-Lab](https:\u002F\u002Fgithub.com\u002FLuckyOne7777\u002FLLM-Trading-Lab) - Real-money six-month experiment; ChatGPT manages a real US-equity micro-cap portfolio under strict pre-defined rules; ships with a 40-page evaluation paper.\n- [195440\u002Fnof1.ai](https:\u002F\u002Fgithub.com\u002F195440\u002Fnof1.ai) - Open-source autonomous AI trading agent from the nof1 family; TypeScript port.\n- [oficcejo\u002Falpha-arena-okx](https:\u002F\u002Fgithub.com\u002Foficcejo\u002Falpha-arena-okx) - OKX re-implementation of nof1.ai's Alpha Arena; DeepSeek \u002F Qwen3-Max as decision-makers; useful when comparing Chinese-language nof1 projects.\n- [wfnuser\u002FOpenNof1](https:\u002F\u002Fgithub.com\u002Fwfnuser\u002FOpenNof1) - \"Your custom 24\u002F7 AI trading agent\"; open-source implementation of the nof1.ai Alpha Arena approach.\n- [kojott\u002FLLM-trader-test](https:\u002F\u002Fgithub.com\u002Fkojott\u002FLLM-trader-test) - Lightweight teaching testbed for the nof1.ai Alpha Arena approach.\n\n\u003Ca id=\"agents-prediction-market\">\u003C\u002Fa>\n### Prediction-market specialists\n\n- [ryanfrigo\u002Fkalshi-ai-trading-bot](https:\u002F\u002Fgithub.com\u002Fryanfrigo\u002Fkalshi-ai-trading-bot) - Grok-4-driven Kalshi prediction-market multi-agent trading system; portfolio optimization + 5-gate risk engine.\n- [OctagonAI\u002Fkalshi-trading-bot-cli](https:\u002F\u002Fgithub.com\u002FOctagonAI\u002Fkalshi-trading-bot-cli) - AI-native CLI for Kalshi and Polymarket; researches an event, estimates probability, then compares it with the live order book.\n- [jvnhaoWen\u002FPolyAgent](https:\u002F\u002Fgithub.com\u002FjvnhaoWen\u002FPolyAgent) - Polymarket-focused multi-skill trading agent; focused single-venue Polymarket LLM agent.\n\n> Also useful here: [agent-next\u002Fpolymarket-paper-trader](#mcps-polymarket-paper-trader) is listed under MCPs because it is a paper-trading simulator, but it is built for AI agents.\n\n> Also see: [YichengYang-Ethan\u002Foracle3](#agents-oracle3) is listed with multi-agent systems above, and it is especially relevant here for multi-venue prediction-market arbitrage.\n\n\u003Ca id=\"agents-benchmarks\">\u003C\u002Fa>\n### Benchmarks & evaluations\n\n- [ulab-uiuc\u002Flive-trade-bench](https:\u002F\u002Fgithub.com\u002Fulab-uiuc\u002Flive-trade-bench) - Live-market evaluation for trading agents; UIUC ULab's live-eval benchmark; distinct from backtest-only benchmarks.\n- [Open-Finance-Lab\u002FAgenticTrading](https:\u002F\u002Fgithub.com\u002FOpen-Finance-Lab\u002FAgenticTrading) - Open-Finance-Lab's academic framework + dataset for agent-trading research.\n- [vals-ai\u002Ffinance-agent](https:\u002F\u002Fgithub.com\u002Fvals-ai\u002Ffinance-agent) - Finance-agent benchmark \u002F task suite from vals-ai.\n\u003Ca id=\"agents-deepfund\">\u003C\u002Fa>\n- [HKUSTDial\u002FDeepFund](https:\u002F\u002Fgithub.com\u002FHKUSTDial\u002FDeepFund) - Multi-agent fund-investment benchmark; LLM analysts evaluate stocks in a unified trading arena with leaderboard.\n\n\u003Ca id=\"agents-strategy-coding\">\u003C\u002Fa>\n### Strategy coding \u002F self-improving agents\n\n- [paperswithbacktest\u002Fpwb-alphaevolve](https:\u002F\u002Fgithub.com\u002Fpaperswithbacktest\u002Fpwb-alphaevolve) - DeepMind AlphaEvolve-style agent that uses an LLM to write and improve trading strategies for backtesting.\n- [Miasyster\u002FQuantGPT](https:\u002F\u002Fgithub.com\u002FMiasyster\u002FQuantGPT) - Agent-driven A-share factor research engine; 8 MCP tools span hypothesis → backtest → score → WQ BRAIN submission. *(Distinct from rnikitin\u002FQuantGPT.)*\n\n> Note: [`TauricResearch\u002FTrading-R1`](https:\u002F\u002Fgithub.com\u002FTauricResearch\u002FTrading-R1) is not listed yet because its terminal has not launched. It can be added once the project is publicly usable.\n\n\u003Ca id=\"mcps\">\u003C\u002Fa>\n## MCPs\n\n\u003Cp align=\"center\">\n  \u003Cimg src=\"assets\u002Fsection-mcps.png\" alt=\"MCPs section header\" width=\"760\" \u002F>\n\u003C\u002Fp>\n\nMCPs are servers that let an agent call external tools through the Model Context Protocol. In this list, they mostly cover market data, broker or exchange actions, research tools, and backtesting services.\n\n> [!NOTE]\n> Same author to compare: `guangxiangdebizi\u002F` maintains [FinanceMCP](#mcps-financemcp) for data access and [TradingAgents-MCPmode](#mcps-tradingagents-mcpmode) for TradingAgents-style research tools. They solve different problems, so they stay in separate sections.\n\n\u003Ca id=\"mcps-market-data\">\u003C\u002Fa>\n### Market data \u002F data providers\n\n\u003Ca id=\"mcps-financial-datasets\">\u003C\u002Fa>\n- [LLMQuant\u002Fdata-mcp](https:\u002F\u002Fgithub.com\u002FLLMQuant\u002Fdata-mcp) - LLMQuant Data's official MCP server, positioned as the \"knowledge harness for AI-native finance\"; covers semantic search over a 50k+ quant wiki and 1.2k+ research papers, US equity OHLCV + dividends\u002Fsplits, crypto klines & snapshots (Binance Spot), 50+ curated macro indicators (FRED, etc.), SEC 10-K\u002F10-Q full-text browse & read, and three-way 13F institutional holdings queries (manager → holdings \u002F ticker → holders \u002F top managers).\n- [financial-datasets\u002Fmcp-server](https:\u002F\u002Fgithub.com\u002Ffinancial-datasets\u002Fmcp-server) - Financial Datasets' first-party MCP; US-equity + crypto fundamentals (3 statements + ratios) + prices + news.\n- [6551Team\u002Fopennews-mcp](https:\u002F\u002Fgithub.com\u002F6551Team\u002Fopennews-mcp) - 84+ news-source aggregation (Bloomberg \u002F Reuters \u002F FT \u002F CoinDesk and more) + AI impact-scoring \u002F trading-signal + WebSocket streaming.\n- [BlockRunAI\u002Fblockrun-mcp](https:\u002F\u002Fgithub.com\u002FBlockRunAI\u002Fblockrun-mcp) - Real-time data MCP with pay-per-call x402 payments; covers search, research, quotes, crypto, X, and Twitter.\n\u003Ca id=\"mcps-financemcp\">\u003C\u002Fa>\n- [guangxiangdebizi\u002FFinanceMCP](https:\u002F\u002Fgithub.com\u002Fguangxiangdebizi\u002FFinanceMCP) - Tushare + Binance MCP spanning A-shares \u002F HK \u002F US \u002F funds \u002F bonds \u002F macro \u002F stablecoins \u002F crypto \u002F financial news.\n- [saidsurucu\u002Fborsa-mcp](https:\u002F\u002Fgithub.com\u002Fsaidsurucu\u002Fborsa-mcp) - Turkish BIST + US-equity + fund data MCP serving regional markets outside China and the US.\n- [aahl\u002Fmcp-aktools](https:\u002F\u002Fgithub.com\u002Faahl\u002Fmcp-aktools) - Stock and crypto data MCP built on akshare \u002F aktools; broad market-data coverage through the AKShare ecosystem.\n- [elsejj\u002Fmcp-cn-a-stock](https:\u002F\u002Fgithub.com\u002Felsejj\u002Fmcp-cn-a-stock) - A-share-only data MCP; single-market deep coverage instead of multi-source aggregation.\n- [massive-com\u002Fmcp_massive](https:\u002F\u002Fgithub.com\u002Fmassive-com\u002Fmcp_massive) - Massive (formerly Polygon.io) first-party MCP; multi-asset market-data coverage.\n- [Alex2Yang97\u002Fyahoo-finance-mcp](https:\u002F\u002Fgithub.com\u002FAlex2Yang97\u002Fyahoo-finance-mcp) - Full-feature Yahoo Finance MCP; historical prices + fundamentals + option chains + news; Yahoo wrapper.\n- [stefanoamorelli\u002Fsec-edgar-mcp](https:\u002F\u002Fgithub.com\u002Fstefanoamorelli\u002Fsec-edgar-mcp) - SEC EDGAR MCP; 10-K \u002F 10-Q \u002F 8-K \u002F insider trades \u002F filings reader; common filings entry across awesome-lists.\n- [zwldarren\u002Fakshare-one-mcp](https:\u002F\u002Fgithub.com\u002Fzwldarren\u002Fakshare-one-mcp) - A-share data MCP backed by the AKShare-One normalizer; an alternative implementation within the AKShare ecosystem.\n- [imbenrabi\u002FFinancial-Modeling-Prep-MCP-Server](https:\u002F\u002Fgithub.com\u002Fimbenrabi\u002FFinancial-Modeling-Prep-MCP-Server) - FMP MCP with 250+ tools for fundamentals, market intelligence, and ETFs.\n- [narumiruna\u002Fyfinance-mcp](https:\u002F\u002Fgithub.com\u002Fnarumiruna\u002Fyfinance-mcp) - Minimal yfinance MCP; a lightweight Yahoo Finance data option.\n- [OctagonAI\u002Foctagon-mcp-server](https:\u002F\u002Fgithub.com\u002FOctagonAI\u002Foctagon-mcp-server) - MCP for filings, earnings calls, financials, stock data, private-market deals, and web research.\n\n\u003Ca id=\"mcps-brokerage\">\u003C\u002Fa>\n### Brokerage \u002F exchange trading\n\n\u003Ca id=\"mcps-alpaca\">\u003C\u002Fa>\n- [alpacahq\u002Falpaca-mcp-server](https:\u002F\u002Fgithub.com\u002Falpacahq\u002Falpaca-mcp-server) - Alpaca's official MCP for market data plus paper or live trading in equities, ETFs, options, and crypto. *(← used by: [tradermonty\u002Fclaude-trading-skills](#skills-claude-trading-skills), [staskh\u002Ftrading_skills](#skills-trading-skills), [huygiatrng\u002FAlpacaTradingAgent](#agents-tradingagents).)*\n\u003Ca id=\"mcps-kraken-cli\">\u003C\u002Fa>\n- [krakenfx\u002Fkraken-cli](https:\u002F\u002Fgithub.com\u002Fkrakenfx\u002Fkraken-cli) - Kraken's official AI-native CLI with an embedded MCP; covers crypto, xStocks, forex, derivatives, paper trading, and bundled SKILL.md packs.\n\u003Ca id=\"mcps-koreainvestment\">\u003C\u002Fa>\n- [koreainvestment\u002Fopen-trading-api](https:\u002F\u002Fgithub.com\u002Fkoreainvestment\u002Fopen-trading-api) - Korea Investment & Securities official SDK; includes a Trading MCP, strategy builder, and backtester.\n- [okx\u002Fagent-trade-kit](https:\u002F\u002Fgithub.com\u002Fokx\u002Fagent-trade-kit) - OKX official MCP for spot, perpetuals, futures, options, and grid bots.\n- [ariadng\u002Fmetatrader-mcp-server](https:\u002F\u002Fgithub.com\u002Fariadng\u002Fmetatrader-mcp-server) - Representative MT5 MCP; lets LLMs trade through any MetaTrader 5 broker; MCP connector for a major retail-forex platform.\n- [Qoyyuum\u002Fmcp-metatrader5-server](https:\u002F\u002Fgithub.com\u002FQoyyuum\u002Fmcp-metatrader5-server) - Alternative MT5 MCP for quotes, trading, and history; uses MCP resources as well as tools.\n- [rcontesti\u002FIB_MCP](https:\u002F\u002Fgithub.com\u002Frcontesti\u002FIB_MCP) - Representative IBKR MCP; exposes Interactive Brokers TWS \u002F Gateway as MCP tools; aimed at professional-broker workflows.\n- [code-rabi\u002Finteractive-brokers-mcp](https:\u002F\u002Fgithub.com\u002Fcode-rabi\u002Finteractive-brokers-mcp) - Alternative IBKR MCP in TS \u002F JS; complements rcontesti's Python build.\n- [taylorwilsdon\u002Fquantconnect-mcp](https:\u002F\u002Fgithub.com\u002Ftaylorwilsdon\u002Fquantconnect-mcp) - Independent QuantConnect MCP focused on strategy research and workflow automation.\n\n> Also useful for Skills readers: [krakenfx\u002Fkraken-cli](#mcps-kraken-cli) includes 50 bundled SKILL.md packages. The main entry is here because it is primarily an exchange trading tool.\n\n\u003Ca id=\"mcps-research-tools\">\u003C\u002Fa>\n### Research tools \u002F analysis\n\n- [wshobson\u002Fmaverick-mcp](https:\u002F\u002Fgithub.com\u002Fwshobson\u002Fmaverick-mcp) - Personal stock-analysis MCP for fundamentals, technical indicators, and screening.\n- [mnemox-ai\u002Ftradememory-protocol](https:\u002F\u002Fgithub.com\u002Fmnemox-ai\u002Ftradememory-protocol) - Memory MCP for AI trading agents; records decision rationale, outcomes, and review evidence with 17 MCP tools and 35+ REST endpoints.\n\u003Ca id=\"mcps-tradingagents-mcpmode\">\u003C\u002Fa>\n- [guangxiangdebizi\u002FTradingAgents-MCPmode](https:\u002F\u002Fgithub.com\u002Fguangxiangdebizi\u002FTradingAgents-MCPmode) - TradingAgents refactored as MCP tools for multi-agent equity research.\n- [QuantMLResearch\u002FAI-Kline](https:\u002F\u002Fgithub.com\u002FQuantMLResearch\u002FAI-Kline) - Stock-analysis tool combining classic technical analysis, AI prediction, and MCP access.\n- [wbsu2003\u002Fstock-scanner-mcp](https:\u002F\u002Fgithub.com\u002Fwbsu2003\u002Fstock-scanner-mcp) - Stock scanner MCP for prices, scoring, technical reports, and AI summaries.\n\n> Also relevant: [dragon1086\u002Fprism-insight](#agents-prism-insight) is listed under Agents; this section mentions it because it has built-in MCP support for research.\n\n\u003Ca id=\"mcps-tradingview\">\u003C\u002Fa>\n### TradingView bridge\n\n- [atilaahmettaner\u002Ftradingview-mcp](https:\u002F\u002Fgithub.com\u002Fatilaahmettaner\u002Ftradingview-mcp) - 30+-tool TradingView MCP; 6 backtest strategies + Reddit sentiment + news + multi-exchange; many tools work without an API key.\n\n\u003Ca id=\"mcps-prediction-market\">\u003C\u002Fa>\n### Prediction markets\n\n\u003Ca id=\"mcps-polymarket\">\u003C\u002Fa>\n- [caiovicentino\u002Fpolymarket-mcp-server](https:\u002F\u002Fgithub.com\u002Fcaiovicentino\u002Fpolymarket-mcp-server) - 45-tool Polymarket MCP; real-time monitoring and explicit order-safety guards.\n\u003Ca id=\"mcps-polymarket-paper-trader\">\u003C\u002Fa>\n- [agent-next\u002Fpolymarket-paper-trader](https:\u002F\u002Fgithub.com\u002Fagent-next\u002Fpolymarket-paper-trader) - Polymarket paper-trading simulator; MCP server + real-time order book + strategy backtesting; built for AI agents.\n\n\u003Ca id=\"mcps-backtesting\">\u003C\u002Fa>\n### Strategy \u002F backtesting platforms\n\n- [whchien\u002Fai-trader](https:\u002F\u002Fgithub.com\u002Fwhchien\u002Fai-trader) - Backtrader-based framework with 20+ strategies, multi-market support, CLI tools, and an embedded MCP for agent workflows.\n\n\u003Ca id=\"skills\">\u003C\u002Fa>\n## Skills\n\n\u003Cp align=\"center\">\n  \u003Cimg src=\"assets\u002Fsection-skills.png\" alt=\"Skills section header\" width=\"760\" \u002F>\n\u003C\u002Fp>\n\nSkills are reusable instructions and workflows for Claude Code or other agent systems. They help an agent repeat a trading task reliably, such as researching a stock, checking options, backtesting a strategy, or managing a portfolio. When a Skill is designed to work with a listed MCP, the entry shows `→ pairs with`.\n\n\u003Ca id=\"skills-equity-research\">\u003C\u002Fa>\n### Equity research\n\n\u003Ca id=\"skills-claude-trading-skills\">\u003C\u002Fa>\n- [tradermonty\u002Fclaude-trading-skills](https:\u002F\u002Fgithub.com\u002Ftradermonty\u002Fclaude-trading-skills) - Large Skill pack for US-equity investors, covering market analysis, breadth, regimes, screening methods, options, Alpaca portfolio management, and research workflows. *(→ pairs with: [alpacahq\u002Falpaca-mcp-server](#mcps-alpaca).)*\n\u003Ca id=\"skills-finance-skills\">\u003C\u002Fa>\n- [himself65\u002Ffinance-skills](https:\u002F\u002Fgithub.com\u002Fhimself65\u002Ffinance-skills) - Skill pack for multiple asset classes, covering valuation, earnings review, option payoffs, ETF checks, liquidity, social research, and geopolitical-risk analysis.\n- [JoelLewis\u002Ffinance_skills](https:\u002F\u002Fgithub.com\u002FJoelLewis\u002Ffinance_skills) - Claude Code financial-services Skill pack; 84 skills across investment management, compliance, advisory workflows, trading operations, and portfolio reporting.\n- [quant-sentiment-ai\u002Fclaude-equity-research](https:\u002F\u002Fgithub.com\u002Fquant-sentiment-ai\u002Fclaude-equity-research) - Claude Code research Skill for buy \u002F sell \u002F hold reports using fundamentals, technicals, option flow, insider activity, and sector context.\n\u003Ca id=\"skills-alphaear\">\u003C\u002Fa>\n- [RKiding\u002FAwesome-finance-skills](https:\u002F\u002Fgithub.com\u002FRKiding\u002FAwesome-finance-skills) - Alphaear Skill suite for news, stocks, sentiment, prediction, signal tracking, logic visualization, reporting, and search.\n\n> Also useful here: [HKUDS\u002FVibe-Trading](#agents-vibe-trading) and [ginlix-ai\u002FLangAlpha](#agents-langalpha) both include bundled Skills. Their main entries stay under Agents because they are full agent workspaces, not just Skill packs.\n\n\u003Ca id=\"skills-crypto\">\u003C\u002Fa>\n### Crypto \u002F DeFi \u002F on-chain\n\n- [okx\u002Fonchainos-skills](https:\u002F\u002Fgithub.com\u002Fokx\u002Fonchainos-skills) - OKX official Skills for OnchainOS, covering wallets, token discovery, quotes, DEX swaps, and transaction broadcasting.\n- [okx\u002Fagent-skills](https:\u002F\u002Fgithub.com\u002Fokx\u002Fagent-skills) - OKX bilingual Skills repo with contribution, review, and security guidance; companion to onchainos-skills.\n\n\u003Ca id=\"skills-strategy-coding\">\u003C\u002Fa>\n### Strategy coding & backtesting\n\n\u003Ca id=\"skills-vectorbt-backtesting\">\u003C\u002Fa>\n- [marketcalls\u002Fvectorbt-backtesting-skills](https:\u002F\u002Fgithub.com\u002Fmarketcalls\u002Fvectorbt-backtesting-skills) - Skill for vectorbt backtesting with setup, backtest, optimization, quick stats, strategy comparison, and reusable strategy templates.\n\n\u003Ca id=\"skills-brokerage\">\u003C\u002Fa>\n### Brokerage execution & portfolio\n\n\u003Ca id=\"skills-trading-skills\">\u003C\u002Fa>\n- [staskh\u002Ftrading_skills](https:\u002F\u002Fgithub.com\u002Fstaskh\u002Ftrading_skills) - Skill pack for option traders, covering market data, analysis, scanners, portfolio work, reports, IBKR integration, and MCP tools. *(→ pairs with: [alpacahq\u002Falpaca-mcp-server](#mcps-alpaca), [rcontesti\u002FIB_MCP](https:\u002F\u002Fgithub.com\u002Frcontesti\u002FIB_MCP).)*\n- [koreal6803\u002Ffinlab-ai](https:\u002F\u002Fgithub.com\u002Fkoreal6803\u002Ffinlab-ai) - Taiwan-equity CLI Skill for strategy discovery, backtesting, and feature engineering with FinLab data and ready-made strategy examples.\n\n> Also useful here: [krakenfx\u002Fkraken-cli](#mcps-kraken-cli) includes SKILL.md packages for crypto, xStocks, forex, and derivatives. The full entry is under MCPs because Kraken CLI is mainly an exchange trading tool.\n\n\u003Ca id=\"resources\">\u003C\u002Fa>\n## Resources\n\n\u003Ca id=\"resources-papers\">\u003C\u002Fa>\n### Papers\n\n> Included here: papers that directly introduce or explain a project listed here. For a broader finance-LLM paper, model, and dataset list, see [`DataArcTech\u002FAwesome-FinLLMs`](https:\u002F\u002Fgithub.com\u002FDataArcTech\u002FAwesome-FinLLMs).\n\n- [TradingAgents: Multi-Agents LLM Financial Trading Framework](https:\u002F\u002Farxiv.org\u002Fabs\u002F2412.20138) - Tauric Research team, arXiv 2412.20138 (2024). Introduces the multi-agent debate decision framework: analyst team + bull\u002Fbear researcher debate + trader + risk control + portfolio manager. [paper](https:\u002F\u002Farxiv.org\u002Fabs\u002F2412.20138) · [code](#agents-tradingagents)\n- [LLM-Trading-Lab: Six-Month Real-Money ChatGPT Micro-Cap Experiment](https:\u002F\u002Fgithub.com\u002FLuckyOne7777\u002FLLM-Trading-Lab) - Lucky One, 2025; ships with a 40-page evaluation paper. Forward-only audit of ChatGPT managing a real US-equity micro-cap portfolio for six months under strict pre-defined rules. [paper \u002F repo](https:\u002F\u002Fgithub.com\u002FLuckyOne7777\u002FLLM-Trading-Lab) · [code](#agents-llm-trading-lab)\n- [FinRobot: Open-Source AI Agent Platform for Financial Analysis](https:\u002F\u002Farxiv.org\u002Fabs\u002F2405.14767) - AI4Finance Foundation, arXiv 2405.14767 (2024). Early academic finance-AI agent platform; multimodal analyst agents tied to the FinGPT model line. [paper](https:\u002F\u002Farxiv.org\u002Fabs\u002F2405.14767) · [code](https:\u002F\u002Fgithub.com\u002FAI4Finance-Foundation\u002FFinRobot)\n- [Time Travel is Cheating: Going Live with DeepFund for Real-Time Fund Investment Benchmarking](https:\u002F\u002Farxiv.org\u002Fabs\u002F2505.11065) - HKUSTDial, arXiv 2505.11065 (2025). Multi-agent fund-investment benchmark with LLM analysts and a trading arena leaderboard. [paper](https:\u002F\u002Farxiv.org\u002Fabs\u002F2505.11065) · [code](#agents-deepfund)\n\n> For broader finance-LLM papers, models, and datasets, see [`DataArcTech\u002FAwesome-FinLLMs`](https:\u002F\u002Fgithub.com\u002FDataArcTech\u002FAwesome-FinLLMs). This list stays focused on usable agent, MCP, and Skill projects.\n\n\u003Ca id=\"resources-learn\">\u003C\u002Fa>\n### Learn\n\n> Included here: public talks, courses, and long-form posts about LLM-driven trading. We skip generic LLM tutorials, generic finance tutorials, and paid courses without a public artifact.\n\n- [Tauric Research GitHub Org](https:\u002F\u002Fgithub.com\u002FTauricResearch) - Tauric Research, ongoing 2024–2026. Official org behind the TradingAgents framework; public README \u002F docs \u002F companion technical reports (arXiv 2412.20138 \u002F 2509.11420); a good place to learn how multi-agent trading systems are built. [link](https:\u002F\u002Fgithub.com\u002FTauricResearch)\n- [AI4Finance Foundation GitHub Org](https:\u002F\u002Fgithub.com\u002FAI4Finance-Foundation) - AI4Finance Foundation, ongoing 2022–2026. Official org behind the FinRobot \u002F FinGPT \u002F FinRL line; ProjectShare \u002F tutorial notebooks \u002F paper companion code; a good place to learn academic finance-AI agents. [link](https:\u002F\u002Fgithub.com\u002FAI4Finance-Foundation)\n\n> Note: the v0.1 Learn section is intentionally short. Future updates can add talks, courses, podcasts, and conference sessions as they become useful to readers.\n\n\u003Ca id=\"contributing\">\u003C\u002Fa>\n## Contributing\n\nWe welcome community contributions: new entries, removal of dead links, and discussion on sub-category boundaries. Start with [CONTRIBUTING.md](CONTRIBUTING.md) (or [CONTRIBUTING.zh-CN.md](CONTRIBUTING.zh-CN.md) in Chinese); the guide puts the AI-native review path, quality bar, submission format, `awesome-lint` check, and bilingual-PR rule in one place. New entries are smoothest via the [Issue: add entry](.github\u002FISSUE_TEMPLATE\u002Fadd-entry.md) template; removals via the [Issue: remove entry](.github\u002FISSUE_TEMPLATE\u002Fremove-entry.md) template.\n\n\u003Ca id=\"related-awesome-lists\">\u003C\u002Fa>\n## Related awesome lists\n\n- [DataArcTech\u002FAwesome-FinLLMs](https:\u002F\u002Fgithub.com\u002FDataArcTech\u002FAwesome-FinLLMs) - Comprehensive finance-LLM paper \u002F model \u002F dataset list (complementary to this list — they cover base models and papers, we cover the application-layer agents · MCPs · Skills).\n- [punkpeye\u002Fawesome-mcp-servers](https:\u002F\u002Fgithub.com\u002Fpunkpeye\u002Fawesome-mcp-servers) - Broad MCP server directory; use this list when you only want trading, research, data, and execution tools.\n- [georgezouq\u002Fawesome-ai-in-finance](https:\u002F\u002Fgithub.com\u002Fgeorgezouq\u002Fawesome-ai-in-finance) - Traditional AI-in-finance list for deep learning, reinforcement learning, and time-series work.\n- [wilsonfreitas\u002Fawesome-quant](https:\u002F\u002Fgithub.com\u002Fwilsonfreitas\u002Fawesome-quant) - Classical quant-library list; useful, but not the focus here.\n- [wangzhe3224\u002Fawesome-systematic-trading](https:\u002F\u002Fgithub.com\u002Fwangzhe3224\u002Fawesome-systematic-trading) - Systematic-trading list for the broader non-agent trading tools.\n\n\u003Ca id=\"maintained-by\">\u003C\u002Fa>\n## Maintained by\n\n\u003Cdiv align=\"center\">\n  \u003Cimg src=\"assets\u002Fllmquant-logo.svg\" alt=\"LLMQuant\" width=\"72\" \u002F>\n  \u003Cbr\u002F>\n  \u003Cstrong>\u003Ca href=\"https:\u002F\u002Fllmquant.com\">LLMQuant\u003C\u002Fa>\u003C\u002Fstrong>\n  \u003Cbr\u002F>\n  \u003Csub>Open-source community for AI, LLMs, and quantitative finance.\u003C\u002Fsub>\n  \u003Cbr\u002F>\u003Cbr\u002F>\n  \u003Ca href=\"https:\u002F\u002Fllmquant.com\">Website\u003C\u002Fa> ·\n  \u003Ca href=\"https:\u002F\u002Fgithub.com\u002FLLMQuant\">GitHub\u003C\u002Fa> ·\n  \u003Ca href=\"https:\u002F\u002Flinkedin.com\u002Fcompany\u002Fllmquant\">LinkedIn\u003C\u002Fa>\n\u003C\u002Fdiv>\n\nThe maintainer team reviews new entries and category changes.\n\n## Star History\n\n[![Star History Chart](https:\u002F\u002Fapi.star-history.com\u002Fsvg?repos=LLMQuant\u002Fawesome-trading-agents&type=Date)](https:\u002F\u002Fwww.star-history.com\u002F#LLMQuant\u002Fawesome-trading-agents&Date) \n","awesome-trading-agents 是一个精选的开源项目列表，汇集了基于大语言模型（LLM）的交易代理、市场连接协议服务器以及相关技能，用于市场研究、策略制定和执行。该项目侧重于三个核心构建模块：代理、市场连接协议（MCP）服务器和技能，旨在通过这些工具帮助用户利用先进的AI技术进行金融市场分析与操作。特别适用于需要借助最新AI技术提升交易决策质量的个人或机构投资者、量化分析师及金融科技开发者。",2,"2026-06-11 03:54:39","CREATED_QUERY"]