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 glincker · MCP Server · ★ 101
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is stacklit safe to install? View the security audit →
Stacklit 108,000 lines of code. 4,000 tokens of index. One command makes any repo AI-agent-ready. No server, no setup. Install and run That is it. Downloads the binary, scans your codebase, generates the index, opens the visual map. One command. Other install options: Or grab a binary from GitHub Releases (macOS, Linux, Windows). CI / GitHub Action Use glincker/stacklit-action to keep the index fresh automatically. Auto-commit on push, or gate PRs with check mode: Add to the job when using mode. What happ
| Stars | 101 |
| Forks | 8 |
| Language | Go |
| Category | MCP Server |
| License | MIT |
| Quality Score | 67.2114209011011/100 |
| Open Issues | 6 |
| Last Updated | 2026-05-07 |
| Created | 2026-04-09 |
| Platforms | claude-code, cli, go, mcp |
| Est. Tokens | ~112k |
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stacklit is One command gives AI agents instant codebase context. ~250 tokens replaces 50,000+ tokens of exploration. Auto-configures Claude Code, Cursor, Aider.. It is categorized as a MCP Server with 101 GitHub stars.
stacklit is primarily written in Go. It covers topics such as ai, ai-agents, ai-coding.
You can find installation instructions and usage details in the stacklit GitHub repository at github.com/glincker/stacklit. The project has 101 stars and 8 forks, indicating an active community.
stacklit is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to stacklit on Agent Skills Hub include octocode, aoci-code, excalidraw-architect-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: