Retrieve personal memories via semantic search
The agent retrieves specific past memories, advice, or lessons from the user's long-term storage using natural language queries, providing context that persists across different AI sessions and platforms.
How it works
The agent utilizes the Amber MCP server's hybrid semantic search capability to find relevant memories based on the user's natural language query. It searches the user's isolated database for memories related to specific topics, people, or events. The agent retrieves the exact wording and context of these memories to provide accurate, personalized responses that reflect the user's long-term history and preferences.
Prompt
Paste this into an agent that has the servers below connected. Adjust the names and dates to your own.
Search my Amber memory for any past conversations or notes regarding my career goals and the advice I received about them. Retrieve the specific details so I can review my long-term progress and previous guidance.MCP servers it needs
Source
The vendor page this playbook is drawn from, and the passage that supports it.
Hybrid semantic search surfaces the right memory even when you don't recall the exact wording.Amber | Never forget what made you, you