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 TesslateAI · MCP Server · ★ 619
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is OpenSail safe to install? View the security audit →
OpenSail OpenSail is the open-source alternative to Codex App, Claude Desktop, Cursor, and Cowork for agentic software work. Docs · Quickstart · Join Discord · Releases Build AI apps, agents, workflows, and automations you can inspect, run, share, and own. Turn recurring work from Slack, email, spreadsheets, tickets, approvals, and internal tools into runnable software. Manage your fleet of agents. Connect real systems. Add approvals, budgets, permissions, logs, schedules, and human review. Run it on your infrastructure. Use any model. Open source. Your cloud, your code, your control. <a href="
| Stars | 619 |
| Forks | 104 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 57.6790722454574/100 |
| Open Issues | 102 |
| Last Updated | 2026-05-30 |
| Created | 2025-10-29 |
| Platforms | claude-code, codex, docker, k8s, mcp, python |
| Est. Tokens | ~1837k |
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OpenSail is OpenSail is the open-source alternative to Codex App, Claude Desktop, Cursor, and Cowork for agentic software work.. It is categorized as a MCP Server with 619 GitHub stars.
OpenSail is primarily written in Python. It covers topics such as agents, ai, automation.
You can find installation instructions and usage details in the OpenSail GitHub repository at github.com/TesslateAI/OpenSail. The project has 619 stars and 104 forks, indicating an active community.
OpenSail is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to OpenSail on Agent Skills Hub include flow-like, agents, concierge. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
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: