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 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.
Hybrid semantic search (dense vector + BM25) over local knowledge bases and codebases, exposed as MCP tools for AI agents to search and list knowledge bases.
A high-precision local knowledge base server enabling AI agents to navigate, search, and reason about complex codebases using hybrid semantic, lexical, and graph retrieval.
Local-first context retrieval engine that serves precise documentation chunks to coding agents via MCP, ensuring high-confidence context for code generation.
Creates a local database of indexed technical documentation from web crawls and local files, enabling AI agents to efficiently search and retrieve documentation through MCP tools.
