AgentCrew — security grade SAFE, quality 73/100

Security audit verdict: SAFE · quality 73/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by saigontechnology · MCP Server · ★ 215

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

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About AgentCrew

AgentCrew Your team of AI specialists for coding, research, and automation. Run multiple focused agents from a desktop app, terminal, or API. What is AgentCrew? AgentCrew lets you build and run a team of specialized AI agents

ai-agentsai-assistantanthropic-claudemcp-clientmodel-context-protocolmulti-agent-systemsterminal-apptool-use

Quick Facts

Stars215
Forks42
LanguagePython
CategoryMCP Server
LicenseApache-2.0
Quality Score73.065575043145/100
Open Issues2
Last Updated2026-09-22
Created2025-02-26
Platformsclaude-code, cli, mcp, python
Est. Tokens~15k

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Frequently Asked Questions

What is AgentCrew?

AgentCrew is Chat application with multi-agents system supports multi-models and MCP. It is categorized as a MCP Server with 215 GitHub stars.

What programming language is AgentCrew written in?

AgentCrew is primarily written in Python. It covers topics such as ai-agents, ai-assistant, anthropic-claude.

How do I install or use AgentCrew?

You can find installation instructions and usage details in the AgentCrew GitHub repository at github.com/saigontechnology/AgentCrew. The project has 215 stars and 42 forks, indicating an active community.

What license does AgentCrew use?

AgentCrew is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

What are the best alternatives to AgentCrew?

The top alternatives to AgentCrew on Agent Skills Hub include turbo-flow, Agentfy, omnicoreagent. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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