AI Memory

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Provide persistent, ranked, and cryptographically attested memory storage across diverse AI models and agent workflows.

AI Memory is a universal, persistent memory substrate built in a single Rust binary designed to seamlessly integrate with any MCP-capable client, including Claude, ChatGPT, Grok, and local models. It enables AI assistants to retain architecture decisions, user preferences, and learned corrections across sessions using either local SQLite or scalable PostgreSQL with Apache AGE and pgvector. Beyond simple recall, the system incorporates cryptographic attestation, a coordination substrate with action DAGs and leases for multi-agent swarms, lifecycle management, and fine-grained governance to prevent context drift and ensure long-term consistency.

주요 기능

01Multi-agent coordination primitives including action DAGs, TTL-bounded leases, routines, and signed signals
0256 GitHub stars
03Dual storage engine support for embedded SQLite (FTS5) and PostgreSQL + Apache AGE with pgvector
04Flexible access interfaces providing MCP tools, HTTP REST APIs, and an extensive CLI surface
05Dynamic memory lifecycle management with auto-promotion, decay scoring, and derivation lineage tracking
06Cryptographic trust layer featuring Ed25519 write attestation, sidechain transcripts, and signed-event chains

사용 사례

01Retaining architectural decisions, developer preferences, and coding guidelines permanently across disparate AI developer tools
02Coordinating work across a heterogeneous fleet of autonomous agents with leases, execution DAGs, and verifiable attestation
03Empowering enterprise-grade knowledge graph and vector retrieval workflows within localized or distributed AI deployments