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LLM-driven context and memory management with wide-recall + precise-reranking RAG architecture. Features multi-dimensional retrieval (vector/timeline/knowledge graph), short/long-term memory, and complete MCP support (HTTP/WebSocket/SSE).
Self-hosted coordination layer for AI agent fleets. Shared semantic memory, tasks, agent-to-agent messages, session handoffs, and a background archivist that synthesizes cross-agent knowledge. Any HTTP client participates — Claude Code, AutoGen, raw scripts.