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Local, LLM-free memory for AI agents. A single offline Rust binary — deterministic and auditable — that learns from use, forgets the irrelevant, and strengthens what matters. No cloud, no API keys.
The memory & storage engine for AI agents. Multi-model, edge-to-cloud, PostgreSQL-compatible.
Cognitive memory database for AI agents — consolidates duplicates, detects contradictions, fades stale memories via temporal decay. Rust, AGPL, ships as library / MCP server / HTTP cluster.
Git for AI Agent Knowledge. A persistent, versioned memory layer for AI systems. Hybrid GraphRAG retrieval. Runs entirely offline.
Graph database native to the cloud. Embedded, multi-tenant, built on object storage.
A cognition aware database engine for AI agent memory. Purpose built in Rust with WAL, HNSW, knowledge graphs, and speculative context pre assembly. Not a wrapper, a ground up storage engine that thinks.
🧠 A native graph-based memory system for autonomous AI agents, featuring bio-inspired sleep-based memory consolidation and powered by KIP & AndaDB.
The living armor an AI agent inhabits: eternal devouring, eternal evolution, eternal amplification.
Universal memory runtime for AI agents
KalamDB — a lightweight, real-time, storage-efficient SQL database. Designed for per-user data isolation and scalable performance — ideal for the AI era.
Cognitive memory engine for AI agents — temporal decay, contradiction detection, autonomous consolidation, knowledge graph, ANN recall via HNSW. Embeddable Rust library with Python bindings; powers yantrikdb-server (HTTP gateway, MCP server, openraft cluster). AGPL.
privacy-first context graph engine for AI agents and human teams.
Embedded Cypher knowledge graph for Python and Rust. Bundled MCP server, describe() schema, and code-graph parser for LLM agents.
Hash-chained memory for AI coding sessions — decisions, coordination, and doctrine across sessions. Deterministic core; optional LLM assist.
Persistent, encrypted memory for AI agents: one Rust binary, one file, no cloud. 55+ MCP tools, hybrid recall (BM25 + dense + RRF), bi-temporal history, AES-256-GCM. 73.8% on LongMemEval. Local-first, air-gap ready, MIT.
Rust CLI for RBMEM (.rbmem), a structured Rust-Brain memory format with timestamp-protected sections, hierarchy, graph relations, Hermes integration, and Markdown sync.
Persistent cognitive graph memory for AI agents — facts, decisions, reasoning chains, corrections. 16 query types, sub-millisecond. Rust core + Python SDK + MCP server.
Absurdly fast embedded graph database with built-in vector search. Rust core, Node.js and Python connectors, GQL, graph algorithms, all in-process with no server.
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