MemClaw
Provides governed shared memory for multi-agent, multi-tenant AI fleets, enabling agents to store, recall, and compound knowledge.
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Provides governed shared memory for multi-agent, multi-tenant AI fleets, enabling agents to store, recall, and compound knowledge.
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MemClaw is an open-source memory system designed for multi-tenant, multi-agent AI fleets. It allows agents to collaboratively store what they learn, find collective knowledge, and continually improve through interactions, avoiding repeated mistakes. Unlike single-agent memory solutions, MemClaw is architected from the ground up for production-scale deployments involving dozens or thousands of agents, prioritizing latency, token efficiency, and robust governance. It transforms plain text into searchable, self-improving memory, fostering a continuous loop of writing, recalling, and compounding knowledge across the fleet.