Google ADK Memory: How To Add Persistent Memory To Google ADK With Mem0

Google ADK’s default InMemoryMemoryService stores session context only in process RAM, causing agents deployed across Cloud Run or GKE replicas to lose user context after restarts or when requests reach different instances. Integrating Mem0 supplies an external, persistent memory layer that uses vector embeddings and semantic search to retrieve relevant user preferences even when later questions use different wording. The integration uses search and save tool functions registered with ADK agents, while conversation storage can also be automated from Runner final-response events to preserve each interaction without requiring explicit user requests. In multi-agent systems, coordinators and specialist agents can access the same user-scoped memory backend, allowing shared context across agents and replicas while maintaining isolation through authenticated user IDs. Production deployments should validate user identifiers, establish retention and summarization policies, and balance retrieval frequency against latency. Mem0 is positioned as a vendor-independent alternative to Vertex AI Memory Bank for persistent, portable memory across frameworks and cloud environments, whereas ADK’s in-memory service remains appropriate mainly for local prototypes and single-instance demonstrations.

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