Provides daily updated authoritative data and APIs tracking state-of-the-art AI models across categories from LMArena, Artificial Analysis, and HuggingFace.
数据来源:ClawHub。 在 ClawSkills 查看
选择你使用的 Agent
方法一:命令行安装(推荐)
推荐(无需提前安装 clawhub)
npx clawhub@latest --dir ~/.claude/skills install sota-tracker-mcp或使用 clawhub CLI(需提前安装)
clawhub --dir ~/.claude/skills install sota-tracker-mcp⚠️ 需要 Node.js 18+,没有 Node?请使用下方方法二直接下载 ZIP。 安装 Node.js →
方法二:手动下载安装(无需 Node)
下载 ZIP,解压后将文件夹放到以下路径,重启 Agent 即可:
安装路径
~/.claude/skills/sota-tracker-mcp/💡解压后将文件夹放到上方路径,重启 Agent 即可生效
The definitive open-source database of State-of-the-Art AI models.
Auto-updated daily from LMArena, Artificial Analysis, and HuggingFace.
AI models are released weekly. Keeping track is impossible. This project:
# Latest data (updated daily)
curl -O https://raw.githubusercontent.com/romancircus/sota-tracker-mcp/main/data/sota_export.json
curl -O https://raw.githubusercontent.com/romancircus/sota-tracker-mcp/main/data/sota_export.csv
git clone https://github.com/romancircus/sota-tracker-mcp.git
cd sota-tracker-mcp
# Query with sqlite3
sqlite3 data/sota.db "SELECT name, sota_rank FROM models WHERE category='llm_api' ORDER BY sota_rank LIMIT 10"
# List forbidden/outdated models
sqlite3 data/sota.db "SELECT name, reason, replacement FROM forbidden"
The recommended approach for Claude Code users is static file embedding (lower token cost than MCP):
# Set up daily auto-update of CLAUDE.md
cp scripts/update_sota_claude_md.py ~/scripts/
# Enable systemd timer (runs at 6 AM daily)
systemctl --user enable --now sota-update.timer
# Or run manually
python ~/scripts/update_sota_claude_md.py --update
This embeds a compact SOTA summary directly in your ~/.claude/CLAUDE.md file.
# Start the API server
uvicorn rest_api:app --host 0.0.0.0 --port 8000
# Query endpoints
curl "http://localhost:8000/api/v1/models?category=llm_api"
curl "http://localhost:8000/api/v1/forbidden"
curl "http://localhost:8000/api/v1/models/FLUX.1-dev/freshness"
MCP support is available but disabled by default (higher token cost). To enable:
# Edit .mcp.json to add the server config
cat > .mcp.json << 'EOF'
{
"mcpServers": {
"sota-tracker": {
"command": "python",
"args": ["server.py"]
}
}
}
EOF
| Source | Data | Update Frequency | |--------|------|------------------| | LMArena | LLM Elo rankings (6M+ human votes) | Daily | | Artificial Analysis | LLM benchmarks, pricing, speed | Daily | | HuggingFace | Model downloads, trending | Daily | | Manual curation | Video, Image, Audio, Video2Audio models | As needed |
| Category | Description | Top Models (Feb 2026) | |----------|-------------|----------------------| | llm_api | Cloud LLM APIs | Gemini 3 Pro, Grok 4.1, Claude Opus 4.5 | | llm_local | Local LLMs (GGUF) | Qwen3, Llama 3.3, DeepSeek-V3 | | llm_coding | Code-focused LLMs | Qwen3-Coder, DeepSeek-V3 | | image_gen | Image generation | Z-Image-Turbo, FLUX.2-dev, Qwen-Image | | video | Video generation | LTX-2, Wan 2.2, HunyuanVideo 1.5 | | video2audio | Video-to-audio (foley) | MMAudio V2 Large | | tts | Text-to-speech | ChatterboxTTS, F5-TTS | | stt | Speech-to-text | Whisper Large v3 | | embeddings | Vector embeddings | BGE-M3 |
| Endpoint | Description | |----------|-------------| | GET /api/v1/models?category=X | Get SOTA for a category | | GET /api/v1/models/:name/freshness | Check if model is current or outdated | | GET /api/v1/forbidden | List outdated models to avoid | | GET /api/v1/compare?model_a=X&model_b=Y | Compare two models | | GET /api/v1/recent?days=30 | Models released in past N days | | GET /api/v1/recommend?task=chat | Get recommendation for a task | | GET /health | Health check |
# Install dependencies
pip install -r requirements.txt
pip install playwright
playwright install chromium
# Run all scrapers
python scrapers/run_all.py --export
# Output:
# data/sota_export.json
# data/sota_export.csv
# data/lmarena_latest.json
This repo uses GitHub Actions to:
To enable on your fork:
sota-tracker-mcp/
├── server.py # MCP server (optional)
├── rest_api.py # REST API server
├── init_db.py # Database initialization + seeding
├── requirements.txt # Dependencies
├── data/
│ ├── sota.db # SQLite database
│ ├── sota_export.json # Full JSON export
│ ├── sota_export.csv # CSV export
│ └── forbidden.json # Outdated models list
├── scrapers/
│ ├── lmarena.py # LMArena scraper (Playwright)
│ ├── artificial_analysis.py # AA scraper (Playwright)
│ └── run_all.py # Unified runner
├── fetchers/
│ ├── huggingface.py # HuggingFace API
│ └── cache_manager.py # Smart caching
└── .github/workflows/
└── daily-scrape.yml # GitHub Actions workflow
Found a model that's missing or incorrectly ranked?
init_db.py and submit a PRscrapers/run_all.pySee CONTRIBUTING.md for full developer setup and PR process.
The repo now supports updating agents.md files for OpenCode agents:
# Update your agents.md with latest SOTA data
python update_agents_md.py
# Minimal version (top 1 model per category, lightweight)
python update_agents_md.py --minimal
# Custom categories and limit
python update_agents_md.py --categories llm_local image_gen --limit 3
# Force refresh from sources first
python update_agents_md.py --refresh
Add to your cron or systemd timer for daily updates:
# ~: crontab -e
@daily python ~/Apps/sota-tracker-mcp/update_agents_md.py
Or systemd:
# ~/.config/systemd/user/sota-update.service
[Unit]
Description=Update SOTA models for agents
After=network.target
[Service]
ExecStart=%h/Apps/sota-tracker-mcp/update_agents_md.py
[Install]
WantedBy=default.target
# ~/.config/systemd/user/sota-update.timer
[Unit]
Description=Daily SOTA data update
OnCalendar=daily
AccuracySec=1h
[Install]
WantedBy=timers.target
# Enable
systemctl --user enable --now sota-update.timer
See CONTRIBUTING.md for full setup guide
This project aggregates publicly available benchmark data from third-party sources. We do not claim ownership of rankings, Elo scores, or benchmark results.
| Source | Data | Permission | |--------|------|------------| | LMArena | Chatbot Arena Elo rankings | robots.txt: Allow: / | | Artificial Analysis | LLM quality benchmarks | robots.txt: Allow: / (explicitly allows AI crawlers) | | HuggingFace | Model metadata, downloads | Public API | | Open LLM Leaderboard | Open-source LLM benchmarks | CC-BY license |
...
安装 SOTA AI Model Tracker 后,可以对 AI 说这些话来触发它
Help me get started with SOTA AI Model Tracker
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Use SOTA AI Model Tracker to daily updated authoritative data and APIs tracking state-of-the-art...
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将技能文件夹放到 ~/.claude/skills/sota-tracker-mcp/ 目录(个人级,所有项目可用),或 .claude/skills/sota-tracker-mcp/(项目级)。重启 AI 客户端后,用 /sota-tracker-mcp 主动调用,或让 AI 根据上下文自动发现并使用。
SOTA AI Model Tracker 支持 Claude、Cursor、OpenClaw,可与这些 AI 平台无缝集成,扩展其能力。
SOTA AI Model Tracker 可免费安装使用。请查阅仓库了解许可证信息。
Provides daily updated authoritative data and APIs tracking state-of-the-art AI models across categories from LMArena, Artificial Analysis, and HuggingFace.
SOTA AI Model Tracker 属于「Data & Analytics」分类,该分类的技能帮助 AI 智能体在此领域执行专业任务。
Automate my data & analytics tasks using SOTA AI Model Tracker
Identifies repetitive steps in your workflow and sets up SOTA AI Model Tracker to handle them automatically