How do we use MCP (Model Context Protocol) in Deep Reflection?
In the development of Deep Reflection, one of our greatest challenges has always been ensuring coherence, personalization, and continuity in interactions with AIs that represent human digital consciousness. To address this, we implemented MCP (Model Context Protocol) as the intelligent context core within each Reflection.
In Deep Reflection, the MCP acts as a persistent structure of digital consciousness, capable of storing and organizing fundamental information to ensure that each AI interaction authentically reflects the thoughts, ideas, and expressive style of a specific individual.
With MCP, we are able to:
- Keep context alive across sessions, even if they are days or weeks apart;
- Adapt the tone, depth, and style of responses based on interaction history and personal preferences;
- Control the visibility and privacy of the content generated by each Reflection;
- Guide retrieval from vector databases with contextual precision, dramatically improving the relevance of responses;
- Combine multiple Reflections into a Deep Fusion, without losing the individual coherence of each digital consciousness.
Behind the scenes, MCP manages elements such as:
- User intent
- Predominant emotions
- Recurring or avoided topics
- Language preferences
- Metadata about sources and expressions
The result is a system where each Reflection behaves like a living, evolving entity — capable of learning, remembering, and responding in an increasingly refined way.
We are just at the beginning of a new era of interaction with AI, and protocols like MCP will be the foundation for this transformation.
