AI agents can read information from project notes, but that information is often lost when the conversation ends. Developers need a simple way to turn useful notes into durable, searchable memory that an agent can retrieve in future interactions.
In this session, we’ll build a practical workflow that connects a notes application to Oracle AI Agent Memory using Model Context Protocol (MCP). We’ll show how project notes can be transformed into typed memories, stored in Oracle AI Database, and retrieved when they are relevant to a later agent request.
What we’ll cover:
- Understanding the difference between conversation context and durable agent memory
- Connecting an external notes source to Oracle AI Agent Memory using MCP
- Extracting and classifying useful information as facts, preferences, or guidelines
- Storing and searching memories with the oracleagentmemory Python package
- Using a simple frontend to inspect the memory workflow
- Retrieving relevant memories across separate agent sessions
Duration: 1 hour
