diff --git a/README.md b/README.md index 573ebdd9a..e490c685a 100644 --- a/README.md +++ b/README.md @@ -2479,6 +2479,7 @@ Tools for conducting research, surveys, interviews, and data collection. ### 🔒 Security +- [node-man/dechonet-mcp](https://github.com/node-man/dechonet-mcp) 📇 ☁️ - Domain security reconnaissance for AI agents. 13 tools — DNS + DNSSEC, SSL/TLS chain & grade, HTTP security headers, SPF/DKIM/DMARC email auth, TCP port scan, ASN, RDAP/WHOIS — plus a one-shot `security_scan` returning a 0-100 Health Score (A–F). Free, no API key. `npx -y dechonet-mcp` - [honeylabshq/honeylabs-mcp](https://github.com/honeylabshq/honeylabs-mcp) [![honeylabs-mcp MCP server](https://glama.ai/mcp/servers/honeylabshq/honeylabs-mcp/badges/score.svg)](https://glama.ai/mcp/servers/honeylabshq/honeylabs-mcp) 🐍 ☁️ - Honeypot threat intelligence for AI agents: 90 days of probe data from a sensor network for IP reputation, scanner classification, CVE probing trends, and JA4/JA4H/HASSH fingerprints. Remote MCP, free tier. - [kent-tokyo/shohei](https://github.com/kent-tokyo/shohei) [![kent-tokyo/shohei MCP server](https://glama.ai/mcp/servers/kent-tokyo/shohei/badges/score.svg)](https://glama.ai/mcp/servers/kent-tokyo/shohei) 🦀 ☁️ 🏠 🍎 🪟 🐧 - Rust infrastructure diagnostics MCP server for AI agents: DNS checks, TLS certificate chain inspection, email security, global DNS propagation, and DNS latency benchmarking. - [srinivasan-sundaresan95/orihime](https://github.com/srinivasan-sundaresan95/orihime) [![orihime MCP server](https://glama.ai/mcp/servers/srinivasan-sundaresan95/orihime/badges/score.svg)](https://glama.ai/mcp/servers/srinivasan-sundaresan95/orihime) 🐍 🏠 🍎 🪟 🐧 - Cross-repository code knowledge graph MCP server for Java, Kotlin, JavaScript, and TypeScript. Indexes source into embedded KuzuDB via tree-sitter; 30+ tools for call-flow tracing, multi-hop taint analysis (OWASP/CWE/PCI/STIG reports), entry-point reachability filtering, performance hotspot detection, and license compliance — without reading source files. 95% fewer tokens vs source-reading baseline. `pip install orihime`