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 KSroido · MCP Server · ★ 80
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Kagi-Session2API-MCP safe to install? View the security audit →
Kagi Session2API MCP Server Free Kagi Search MCP server — session tokens, no API key needed English | 中文文档 Access Kagi search and summarizer via session tokens — completely free. Works with Claude Desktop, Cursor, Windsurf, Cline, Hermes and any MCP-compatible AI coding assistant/agent. ⭐ Star History ⚠️ EndUser Warning: This project uses Kagi session tokens to access search and summarizer features without the official paid API. This may violate Kagi's Terms of Service. Potential consequences include account suspension or permanent ban. Use at your own risk. The authors assume no liability for any acc
| Stars | 80 |
| Forks | 6 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 74.8624231166987/100 |
| Open Issues | 2 |
| Last Updated | 2026-05-26 |
| Created | 2026-05-01 |
| Platforms | browser, claude-code, cli, mcp, python |
| Est. Tokens | ~6k |
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Kagi-Session2API-MCP is Free Kagi Search MCP server — access search and summarizer via session tokens, no API key needed. Works with Claude Desktop, Cursor, Windsurf, Hermes and any MCP client.. It is categorized as a MCP Server with 80 GitHub stars.
Kagi-Session2API-MCP is primarily written in Python. It covers topics such as ai-agent, ai-coding, claude-desktop.
You can find installation instructions and usage details in the Kagi-Session2API-MCP GitHub repository at github.com/KSroido/Kagi-Session2API-MCP. The project has 80 stars and 6 forks, indicating an active community.
The top alternatives to Kagi-Session2API-MCP on Agent Skills Hub include notion-mcp-server, deterministic-agent-control-protocol, google-analytics-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: