by NetLops · MCP Server · ★ 131
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. 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 | 131 |
| Forks | 16 |
| Language | Rust |
| Category | MCP Server |
| Quality Score | 69/100 |
| Last Updated | 2026-10-16 |
| Created | 2026-03-22 |
| Platforms | browser, mcp, rust |
| Est. Tokens | ~8k |
SoSearch API A lightning-fast pseudo Web Search Engine API written in Rust — also works as an MCP server for AI agents. This project emulates popular APIs like SerpAPI or Tavily without needing official and expensive API keys, by multiplexing requests to popular engines directly and scraping the results concurrently. Philosophy Performance: Powered by for async concurrent I/O.
These tools work well together with SoSearch for enhanced workflows:
Looking for a SoSearch alternative? If you're comparing SoSearch with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
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Kindly Web Search MCP Server: Web search + robust content retrieval for AI coding tools (Claude Code, Codex, C
专门为 agent 打造的开源 agent 搜索工具，具备 200+的搜索源及多语言搜索能力，覆盖中文/英文/学术/代码/购物/金融/新闻/百科。
An MCP server providing web search and content extraction capabilities. Integrates DuckDuckGo search functiona
Explore other popular mcp server tools:
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: