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 kalil0321 · MCP Server · ★ 1.2k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is reverse-api-engineer safe to install? View the security audit →
CLI tool that captures browser traffic and automatically generates production-ready Python API clients. No more manual reverse engineering—just browse, capture, and get clean API code. Table of Contents Features Installation Quick Start Usage Modes Manual Mode Engineer Mode Agent Mode Collector Mode Tags Configuration Model Selection Agent Configuration SDK Selection [CLI Commands](#-cli-comm
| Stars | 1,174 |
| Forks | 107 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 66.2918675082453/100 |
| Open Issues | 9 |
| Last Updated | 2026-09-20 |
| Created | 2025-12-23 |
| Platforms | browser, claude-code, cli, mcp, python |
| Est. Tokens | ~17k |
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reverse-api-engineer is The agent that turns websites into APIs!. It is categorized as a MCP Server with 1.2k GitHub stars.
reverse-api-engineer is primarily written in Python. It covers topics such as ai, ai-agents, claude.
You can find installation instructions and usage details in the reverse-api-engineer GitHub repository at github.com/kalil0321/reverse-api-engineer. The project has 1.2k stars and 107 forks, indicating an active community.
reverse-api-engineer is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to reverse-api-engineer on Agent Skills Hub include agnix, Unity-MCP, brightdata-mcp. 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: