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Sota Tracker Mcp

**The definitive open-source database of State-of-the-Art AI models.**.

Rating: 4.2 (250 reviews)
Downloads: 4,155 downloads
Version: 1.0.0

Overview

**The definitive open-source database of State-of-the-Art AI models.**.

Complete Documentation

View Source →

SOTA Tracker

The definitive open-source database of State-of-the-Art AI models.

Auto-updated daily from LMArena, Artificial Analysis, and HuggingFace.

Why This Exists

AI models are released weekly. Keeping track is impossible. This project:

Curates authoritative data - LMArena Elo rankings, manual curation for video/image/audio models
Updates daily via GitHub Actions
Exports to JSON/CSV/SQLite - Use in your own projects
Provides multiple interfaces - Static files, REST API, or MCP server

Quick Start: Use the Data

Option 1: Download JSON/CSV

bash

# 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

Option 2: Clone and Query Locally

bash

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# List forbidden/outdated models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"

Option 3: Use with Claude Code (Recommended)

The recommended approach for Claude Code users is static file embedding (lower token cost than MCP):

bash

# 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.

Option 4: REST API

bash

# 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"

Option 5: MCP Server (Optional)

MCP support is available but disabled by default (higher token cost). To enable:

bash

# Edit .mcp.json to add the server config
cat > .mcp.json << 'EOF'
{
  "mcpServers": {
    "sota-tracker": {
      "command": "python",
      "args": ["server.py"]
    }
  }
}
EOF

Data Sources

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

REST API Endpoints

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

Run Your Own Scraper

bash

# 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

GitHub Actions (Auto-Update)

This repo uses GitHub Actions to:

Daily: Scrape all sources, update database, commit changes
Weekly: Create a tagged release with JSON/CSV exports

To enable on your fork:

Fork this repo
Go to Settings → Actions → Enable workflows
Data will auto-update daily at 6 AM UTC

File Structure

text

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

Contributing

Found a model that's missing or incorrectly ranked?

For manual additions: Edit init_db.py and submit a PR
For scraper improvements: Edit files in scrapers/
For new data sources: Add a new scraper and update run_all.py

See CONTRIBUTING.md for full developer setup and PR process.

OpenCode / Agents.md Integration

The repo now supports updating agents.md files for OpenCode agents:

bash

# 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

Automation

Add to your cron or systemd timer for daily updates:

cron

# ~: crontab -e
@daily python ~/Apps/sota-tracker-mcp/update_agents_md.py

Or systemd:

bash

# ~/.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

Data Attribution & Legal

This project aggregates publicly available benchmark data from third-party sources. We do not claim ownership of rankings, Elo scores, or benchmark results.

Data Sources (Used With Permission)

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

Disclaimer

All benchmark scores and rankings are the intellectual work of their respective sources
This project provides aggregation and tooling, not original benchmark data
Data is scraped once daily to minimize server load
If you are a data source and wish to be excluded, please open an issue

Fair Use

This project:

Aggregates factual data (not copyrightable)
Adds value through tooling (API server, unified format, forbidden list)
Attributes all sources with links
Does not compete commercially with sources
Respects robots.txt permissions

License

MIT - See LICENSE for details.

The code in this repository is MIT licensed. The data belongs to its respective sources (see attribution above).

Installation

Terminal bash


openclaw install sota-tracker-mcp

Copied!

💻Code Examples

sqlite3 data/sota.db "SELECT name, reason, replacement FROM forbidden"

sqlite3-datasotadb-select-name-reason-replacement-from-forbidden.txt

### Option 3: Use with Claude Code (Recommended)

The recommended approach for Claude Code users is **static file embedding** (lower token cost than MCP):

python ~/scripts/update_sota_claude_md.py --update

python-scriptsupdatesotaclaudemdpy---update.txt

This embeds a compact SOTA summary directly in your `~/.claude/CLAUDE.md` file.

### Option 4: REST API

curl "http://localhost:8000/api/v1/models/FLUX.1-dev/freshness"

curl-httplocalhost8000apiv1modelsflux1-devfreshness.txt

### Option 5: MCP Server (Optional)

MCP support is available but disabled by default (higher token cost). To enable:

EOF

eof.txt

## Data Sources

| Source | Data | Update Frequency |
|--------|------|------------------|
| [LMArena](https://lmarena.ai/leaderboard) | LLM Elo rankings (6M+ human votes) | Daily |
| [Artificial Analysis](https://artificialanalysis.ai) | LLM benchmarks, pricing, speed | Daily |
| [HuggingFace](https://huggingface.co) | Model downloads, trending | Daily |
| Manual curation | Video, Image, Audio, Video2Audio models | As needed |

## Categories

| 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 |

## REST API Endpoints

| 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 |

## Run Your Own Scraper

# data/lmarena_latest.json

-datalmarenalatestjson.txt

## GitHub Actions (Auto-Update)

This repo uses GitHub Actions to:
- **Daily**: Scrape all sources, update database, commit changes
- **Weekly**: Create a tagged release with JSON/CSV exports

To enable on your fork:
1. Fork this repo
2. Go to Settings → Actions → Enable workflows
3. Data will auto-update daily at 6 AM UTC

## File Structure

└── daily-scrape.yml # GitHub Actions workflow

--daily-scrapeyml--github-actions-workflow.txt

## Contributing

Found a model that's missing or incorrectly ranked?

1. **For manual additions**: Edit `init_db.py` and submit a PR
2. **For scraper improvements**: Edit files in `scrapers/`
3. **For new data sources**: Add a new scraper and update `run_all.py`

See [CONTRIBUTING.md](CONTRIBUTING.md) for full developer setup and PR process.

## OpenCode / Agents.md Integration

The repo now supports updating `agents.md` files for OpenCode agents:

python update_agents_md.py --refresh

python-updateagentsmdpy---refresh.txt

### Automation

Add to your cron or systemd timer for daily updates:

example.sh

# 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

example.sh

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"

example.sh

# 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

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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

Overview

Complete Documentation

SOTA Tracker

Why This Exists

Quick Start: Use the Data

Option 1: Download JSON/CSV

Option 2: Clone and Query Locally

Option 3: Use with Claude Code (Recommended)

Option 4: REST API

Option 5: MCP Server (Optional)

Data Sources

Categories

REST API Endpoints

Run Your Own Scraper

GitHub Actions (Auto-Update)

File Structure

Contributing

OpenCode / Agents.md Integration

Automation

Data Attribution & Legal

Data Sources (Used With Permission)

Disclaimer

Fair Use

License

Installation

💻Code Examples

sqlite3 data/sota.db "SELECT name, reason, replacement FROM forbidden"

python ~/scripts/update_sota_claude_md.py --update

curl "http://localhost:8000/api/v1/models/FLUX.1-dev/freshness"

EOF

# data/lmarena_latest.json

└── daily-scrape.yml # GitHub Actions workflow

python update_agents_md.py --refresh

Tags

Quick Info

Ready to Install?

Resources

Related Skills

4claw

Aap Passport

Adaptive Suite

Adversarial Prompting