by Shelpuk-AI-Technology-Consulting · MCP Server · ★ 398
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
Flagged: sudo usage. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 398 |
| Forks | 33 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 71/100 |
| Open Issues | 2 |
| Last Updated | 2026-10-10 |
| Created | 2026-01-02 |
| Platforms | browser, claude-code, codex, gemini, mcp, python |
| Est. Tokens | ~20k |
Improve AI-generated code quality by 20% Web search + robust content retrieval for AI coding tools. Kindly Web Search is a part of the Shelpuk AI Technology Consulting agentic suite – a set of tools that together improve the code quality produced by AI coding agents by 15–20%. Works with Claude Code, Codex, Antigravity, Cursor, Windsurf, and any agent that supports skills or MCP servers.
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: