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The release introduces a user-owned, local-first memory layer that persists AI agent context across sessions and tools, directly addressing the session-reset limitation that causes repeated re-explanation of architectural decisions in tools like Claude Code and Cursor.
The release allows a single `gemini-faf-mcp` binary to serve both local MCP clients and cloud-hosted deployments without any configuration changes, while also resolving a handshake compatibility issue with strict MCP clients.