What is kindly-web-search-mcp-server?
kindly-web-search-mcp-server is a AI tool that Kindly Web Search MCP Server: Web search + robust content retrieval for AI coding tools (Claude Code, Codex, Cursor, GitHub Copilot, Gemini, etc.) and AI agents (Claude Desktop, OpenClaw, etc.). Suppo. It has a Nerq Trust Score of 68/100 (C). 151 GitHub stars. Published by Shelpuk-AI-Technology-Consulting. Last analyzed November 2026.
Why This Score
- ⚠️ Security: 0/100 — Some security concerns
- ⚠️ Maintenance: 0/100 — Maintenance activity is low
- ⚠️ Community: 151 stars, 0 downloads — Growing community
- ✅ Transparency: License: MIT — Clear licensing
Trust & Safety Overview
What kindly-web-search-mcp-server Does
kindly-web-search-mcp-server is a agent in the AI tool category. Kindly Web Search MCP Server: Web search + robust content retrieval for AI coding tools (Claude Code, Codex, Cursor, GitHub Copilot, Gemini, etc.) and AI agents (Claude Desktop, OpenClaw, etc.). Supports Serper, Tavily, and SearXNG.. It is published by Shelpuk-AI-Technology-Consulting and is open source. With 151 GitHub stars and 0 downloads, it has a growing community of users and contributors.
Who Should Use kindly-web-search-mcp-server
kindly-web-search-mcp-server is suitable for evaluation and non-critical use. Review the trust score breakdown before using in production.
Details
| Author | Shelpuk-AI-Technology-Consulting |
|---|---|
| Category | AI tool |
| License | MIT |
| Type | agent |
| Source | View on GitHub |
| Security Score | 0/100 |
| Activity Score | 0/100 |
How to Get Started
Check the trust score before installing:
curl nerq.ai/v1/preflight?target=shelpuk-ai-technology-consulting-kindly-web-search-mcp-server
Setup guide · Full safety report · Production review · Is it safe?
Safer Alternatives
| Tool | Trust | Stars |
|---|---|---|
| openclaw | 75 | 218.2K |
| tensorflow | 62 | 193.9K |
| AutoGPT | 65 | 181.9K |
| n8n | 69 | 177.3K |
| ollama | 64 | 163.0K |
Frequently Asked Questions
Last updated November 2026. Trust scores based on automated analysis of public data.