{"data":{"slug":"hkuds-vibe-trading","name":"Vibe-Trading","tagline":"Vibe-Trading Your Personal Trading Agent","github_url":"https://github.com/HKUDS/Vibe-Trading","owner":"HKUDS","repo":"Vibe-Trading","owner_avatar_url":"https://avatars.githubusercontent.com/u/118165258?v=4","primary_language":"Python","stars":31704,"forks":5158,"topics":["ai-agent","algorithmic-trading","backtesting","fintech","llm","mcp","multi-agent","python","quantitative-finance","trading"],"archived":false,"github_pushed_at":"2026-08-25T08:55:38+00:00","maintenance_label":"Very active","stars_delta_30d":4083,"url":"https://www.graphcanon.com/tools/hkuds-vibe-trading","markdown_url":"https://www.graphcanon.com/tools/hkuds-vibe-trading.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/hkuds-vibe-trading","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=hkuds-vibe-trading","description":"\"Vibe-Trading: Your Personal Trading Agent\"","homepage_url":"https://vibetrading.wiki/","license":"MIT","open_issues":32,"watchers":171,"ai_summary":"A Python-based personal trading agent for algorithmic and quantitative finance with capabilities in backtesting and multi-agent systems.","readme_excerpt":"### One-line install (PyPI)\n\n```bash\npip install vibe-trading-ai\n```\n\nThen run a first research task:\n\n```bash\nvibe-trading init\nvibe-trading run -p \"Backtest a BTC-USDT 20/50 moving-average strategy for 2024 and summarize return and drawdown\"\n```\n\n> **Upgrading from an older version?** 0.1.10 moved to LangChain 1.x. If imports break after `pip install -U vibe-trading-ai` over a pre-0.1.10 install (e.g. langgraph fails to import), recreate the venv or run `pip install --force-reinstall vibe-trading-ai`. A fresh install is unaffected.\n\n> **Package name vs commands:** The PyPI package is `vibe-trading-ai`. Once installed, you get three commands:\n>\n> | Command | Purpose |\n> |---------|---------|\n> | `vibe-trading` | Interactive CLI / TUI |\n> | `vibe-trading serve` | Launch FastAPI web server |\n> | `vibe-trading-mcp` | Start MCP server (for Claude Desktop, OpenClaw, Cursor, etc.) |\n\n```bash\nvibe-trading init              # interactive .env setup\nvibe-trading                   # launch CLI\nvibe-trading serve --port 8899 # launch web UI\nvibe-trading-mcp               # start MCP server (stdio)\n```\n\n---\n\n# COPILOT_GITHUB_TOKEN=gho_xxx         # optional; recommended for Docker/CI\n```\n\nStart Vibe-Trading normally. Its preflight reports whether the SDK can authenticate:\n\n```bash\nvibe-trading\n```\n\nAuthentication priority is `COPILOT_GITHUB_TOKEN`, `GH_TOKEN`, `GITHUB_TOKEN`, stored Copilot CLI credentials, then `gh` credentials. Vibe-Trading does not copy or persist SDK credentials. Host keychain credentials are not automatically available inside Docker, so containers should receive `COPILOT_GITHUB_TOKEN`.\n\n---\n\n### Path A: Docker (zero setup)\n\n```bash\ngit clone https://github.com/HKUDS/Vibe-Trading.git\ncd Vibe-Trading\ncp agent/.env.example agent/.env\n\n---\n\n### Path B: Local install\n\n```bash\ngit clone https://github.com/HKUDS/Vibe-Trading.git\ncd Vibe-Trading\npython -m venv .venv\n\n---\n\n### Quick start\n\nCreate `~/.vibe-trading/agent.json`:\n\n```json\n{\n  \"mcpServers\": {\n    \"my-server\": {\n      \"command\": \"uvx\",\n      \"args\": [\"my-mcp-server\"]\n    }\n  }\n}\n```\n\nRun any CLI command — tools from ordinary external servers are automatically injected into the agent's registry after local tools:\n\n```bash\nvibe-trading run \"use my-server to do X\"\n```\n\n---\n\n## License\n\nMIT License — see [LICENSE](LICENSE)\n\n---\n\n<p align=\"center\">\n  ⭐ If <b>Vibe-Trading</b> helps your research, a star helps more people find it.\n</p>\n\n---\n\n<p align=\"center\">\n  Thanks for visiting <b>Vibe-Trading</b> ✨\n</p>\n<p align=\"center\">\n  <img src=\"https://visitor-badge.laobi.icu/badge?page_id=HKUDS.Vibe-Trading&style=flat\" alt=\"visitors\"/>\n</p>","github_created_at":"2026-04-01T09:52:20+00:00","created_at":"2026-07-11T11:48:25.705055+00:00","updated_at":"2026-08-26T00:01:52.125279+00:00","categories":[{"slug":"ai-agents","name":"AI Agents","url":"https://www.graphcanon.com/categories/ai-agents","markdown_url":"https://www.graphcanon.com/categories/ai-agents.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/ai-agents"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"}],"tags":[{"slug":"ai-agent","name":"ai-agent"},{"slug":"algorithmic-trading","name":"algorithmic-trading"},{"slug":"backtesting","name":"backtesting"},{"slug":"fintech","name":"fintech"},{"slug":"llm","name":"llm"},{"slug":"multi-agent","name":"multi-agent"},{"slug":"python","name":"python"},{"slug":"quantitative-finance","name":"quantitative-finance"}],"trust":{"provenance":{"is_fork":false,"github_id":1198306812,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-26T00:01:51.261Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":6,"days_since_push":0,"last_release_at":"2026-08-20T00:02:31Z","stars_delta_30d":4083,"open_issues_delta_30d":13},"security_summary":{"status":"no_manifest","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:48:27.019Z","medium_count":0,"scan_profile":"mcp_manifest","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-26T00:01:51.772Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-08-26T00:01:51.772Z","managed_saas":false},"has_cli":{"value":true,"source":"pyproject.toml:[project.scripts]","observed_at":"2026-08-26T00:01:51.772Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-08-26T00:01:51.772Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-08-26T00:01:51.772Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-08-26T00:01:51.772Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["You need a customizable Python agent for algorithmic trading tasks specifically designed for quantitative finance scenarios","Your project requires integration of advanced AI capabilities, including LLM functionalities in the domain of quantitative investing"],"when_not_to_use":["Looking for a Java-based solution or tools compatible only with other non-Python languages","Need of out-of-the-box ready solutions without customization options for backtesting and multi-agent systems"],"source":"enrich:decision_facts","observed_at":"2026-07-16T20:35:36.471Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Vibe-Trading: Python-based personal trading agent for fintech applications with backtesting and multi-agent system support."}]}}