System 1 decision models (Jev, Laya, Cua-S1) as brain for agents: Browser use, computer use, games and robotics
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System1 Agents is an MCP server that system 1 decision models (Jev, Laya, Cua-S1) as brain for agents: Browser use, computer use, games and robotics. Its tool list has not been published yet over stdio, sse and http, requires no API key, and scores 90/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients - only the file and path differ.
{
"mcpServers": {
"system1-agents": {
"args": [
"-y",
"skills"
],
"command": "npx"
}
}
}Are you the author?
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Give your agents a System 1 decision model. Start from a prebuilt agent or build your own. > Describe the task. Claude Code or Codex runs a prebuilt agent or builds a new one, on Jev, > Laya or Cua-S1 Nano. > Browser use, computer use, robotics and games ship ready to run. > Up to 6× faster and 25× cheaper than a chat model, at the same score.
Run this in your terminal to verify the server starts. Then let us know if it worked - your result helps other developers.
npx -y 'skills' 2>&1 | head -1 && echo "✓ Server started successfully"
After testing, let us know if it worked:
Five weighted categories - click any category to see the underlying evidence.
No known CVEs.
Checked skills against OSV.dev.
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[!NOTE] Give your agents a System 1 decision model. Start from a prebuilt agent or build your own.
Describe the task. Claude Code or Codex runs a prebuilt agent or builds a new one, on Jev, Laya or Cua-S1 Nano. Browser use, computer use, robotics and games ship ready to run.
Up to 6× faster and 25× cheaper than a chat model, at the same score.
Quickstart · From Claude Code or Codex · Benchmarks · Docs
| scenario | Jev | chat model | speedup | Jev cost | chat model cost | more expensive |
|---|---|---|---|---|---|---|
| Browser use (Allrecipes)† | 35.7 s | 138.7 s | 3.89× | $0.091356 | $1.494331 | 16.4× |
| Custom agent (ticket router, 30 tickets) | 12.7 s | 65.3 s | 5.14× | $0.000764 | $0.014800 | 19.4× |
| Computer use (Windows Calculator) | 17.2 s | 30.1 s | 1.75× | $0.000447 | $0.003002 | 6.7× |
| Robotics (ALFWorld) | 7.4 s | 25.7 s | 3.47× | $0.000221 | $0.002800* | 12.7× |
| Games (2048, 20 moves) | 27.1 s | 68.5 s | 2.53× | $0.000447 | $0.006139 | 13.7× |
| Games (Millionaire) | 15.3 s | 21.6 s | 1.41× | $0.000168 | $0.000892 | 5.3× |
| Games (Blackjack) | 2.3 s | 14.7 s | 6.39× | $0.000021 | $0.000531 | 25.3× |
† The first Allrecipes task of the WebVoyager task set (He et al., 2024, Apache-2.0, attribution in NOTICE): a vegetarian lasagna with over 100 reviews, 4.5 stars or more, for 6. The chat model of that row is Claude Fable 5.1 through OpenRouter; both models pay it for the typed search text and the answer. * Estimated; the chat-model run recorded no cost. Each replay below is the episode behind its row, Jev on the left and the chat model on the right, both on the wall clock. The other Allrecipes runs, longer games and the Google Flights driver comparison with its rerun of 2026-09-23: docs/benchmarks.md.
![]() Browser use, WebVoyager's Allrecipes task 0 on the live site, replay at 8× speed | ![]() Computer use, the Windows Calculator, replay at 4× speed |
![]() Ticket router, 30 tickets to five queues, replay at 8× speed |