ECC vs agent-autoloop

MCP rivals. Both tagged mcp, ai-agents, claude-code. Six rounds of real GitHub data, an AI referee, and the crowd picks a side.

Red corner

Blue corner

affaan-m/ECC: 302,647 stars, JavaScript. The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Cod…
KKKKhazix/agent-autoloop: 5,261 stars, TypeScript. 让你的命令行 Agent 在后台自己接活、自己跟进到底；平时不烦你，遇到拿不准的事才发卡片找你拍板。

ECC vs agent-autoloop: tale of the tape

GitHub data as of November 14, 2026

ECC has 57.5 times as many GitHub stars as agent-autoloop (302,647 vs 5,261). In the last 7 days, ECC gained more stars: +3,805 (+1.3%) against +1,400 (+36.3%) for agent-autoloop. ECC saw more development in the last 52 weeks with 3,530 commits, against 215 for agent-autoloop. ECC is the older project (created January 2026), agent-autoloop started in November 2026. ECC is written mainly in JavaScript, agent-autoloop in TypeScript.

	affaan-m/ECC	KKKKhazix/agent-autoloop
Stars	302,647	5,261
Stars gained, last 7 days	+3,805	+1,400
Growth, last 7 days	+1.3%	+36.3%
Avg. stars per day since creation	1,009	478
Forks	44,644	959
Commits, last 52 weeks	3,530	215
Open issues	277	4
Best Repocharts rank today	#1 in Dev Tools	#33 in Rising
Language	JavaScript	TypeScript
License	MIT	MIT
Created	Jan 18, 2026	Nov 3, 2026
Last push	Nov 9, 2026	Nov 14, 2026

Quick answers

Which is more popular, ECC or agent-autoloop?

ECC has 57.5 times as many GitHub stars as agent-autoloop (302,647 vs 5,261) (Repocharts data as of November 14, 2026).

Which is growing faster, ECC or agent-autoloop?

In the last 7 days, ECC gained more stars: +3,805 (+1.3%) against +1,400 (+36.3%) for agent-autoloop.

Which is more actively developed?

ECC saw more development in the last 52 weeks with 3,530 commits, against 215 for agent-autoloop.

What languages are ECC and agent-autoloop written in?

ECC is written mainly in JavaScript, agent-autoloop in TypeScript.

How does RepoClash compare ECC and agent-autoloop?

RepoClash scores both repositories in six rounds (popularity, momentum, activity, community, maintenance and freshness) from public GitHub data, adds an AI referee's verdict and lets developers vote for their favorite. Star counts are updated daily.