Enables AI agents to store, retrieve, and manage contextual knowledge across sessions using semantic search with PostgreSQL and vector embeddings. Supports memory relationships, clustering, multi-agent isolation, and intelligent caching for persistent conversational context.
Provides mathematical operations (expression evaluation, arithmetic, advanced calculations) through MCP, backed by Temporal workflows for reliability and durability. Demonstrates integration between Model Context Protocol tools and Temporal's Nexus RPC framework with full observability.
Enables academic research through paper search across multiple databases (IACR, CryptoBib, Crossref, Google Scholar), PDF processing, and GitHub repository browsing. Features modular architecture with FastMCP-based proxy server routing to specialized academic tools.