Enables AI agents to perform offline cybersecurity research and penetration testing by querying a local knowledge base of curated security data, with tools for searching, answering, and status checking.
Provides instant access to authoritative security documentation from organizations like OWASP, NIST, and major cloud providers through natural language semantic search. It enables users to retrieve security best practices, frameworks, and vulnerability information directly from a locally cached knowledge base.
Enables AI agents to search, retrieve, and summarize content from workplace tools including Google Drive, Notion, Slack, and Confluence through secure Model Context Protocol.
Exposes the MITRE ATT\&CK framework to LLMs and AI assistants via the Model Context Protocol, enabling querying of techniques, tactics, groups, software, and mitigations.
A local security knowledge base that indexes documentation like CVEs and CWEs using hybrid keyword and semantic search. It enables LLM agents to query indexed materials via MCP for accurate, offline retrieval during security audits and code reviews.