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 pinkpixel-dev · MCP Server · ★ 132
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is web-scout-mcp safe to install? View the security audit →
Web Scout MCP Server An MCP server for web search using DuckDuckGo and content extraction, with support for multiple URLs and memory optimizations. ✨ Features 🔍 DuckDuckGo Search: Fast and privacy-focused web search capability 📄 Content Extraction: Clean, readable text extraction from web pages 🚀 Parallel Processing: Support for extracting content from multiple URLs simultaneously 💾 Memory Optimizat
| Stars | 132 |
| Forks | 16 |
| Language | JavaScript |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 75.187177184656/100 |
| Open Issues | 1 |
| Last Updated | 2026-07-21 |
| Created | 2025-05-10 |
| Platforms | browser, mcp, node |
| Est. Tokens | ~14k |
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web-scout-mcp is A powerful MCP server extension providing web search and content extraction capabilities. Integrates DuckDuckGo search functionality and URL content extraction into your MCP environment, enabling AI a. It is categorized as a MCP Server with 132 GitHub stars.
web-scout-mcp is primarily written in JavaScript. It covers topics such as ai-assistant, ai-tools, cheerio.
You can find installation instructions and usage details in the web-scout-mcp GitHub repository at github.com/pinkpixel-dev/web-scout-mcp. The project has 132 stars and 16 forks, indicating an active community.
web-scout-mcp is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to web-scout-mcp on Agent Skills Hub include anansi, web-researcher-mcp, graphlit-mcp-server. 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: