Memento FAQs

Question 1

Can I integrate Memento with my existing development environment and AI tools?

Accepted Answer

Absolutely. Memento offers cross-platform persistent storage via a SQLite backend and integrates seamlessly with popular IDEs (Zed, Cursor, VSCode, Claude Desktop), CLI agents (Gemini CLI, Claude CLI), and through its Python and REST APIs. It's designed to be accessible from all your development tools.

Question 2

What is Memento and what problem does it solve?

Accepted Answer

Memento is an MCP (Model Context Protocol) server designed to provide intelligent, persistent knowledge bases for AI assistants and developers. It solves the problem of ephemeral AI memory by offering confidence tracking, semantic relationship mapping, and cross-platform persistent storage, making knowledge accessible and smarter over time.

Question 3

How does Memento ensure knowledge quality and relevance?

Accepted Answer

Memento features an Intelligent Confidence System that automatically decays unused knowledge, boosts confidence when knowledge is successfully validated, and protects critical memories from decay. This ensures your knowledge base remains relevant and up-to-date, with search results ranked by confidence and importance.

Question 4

What kind of relationships can Memento track between pieces of knowledge?

Accepted Answer

Memento supports over 35 predefined semantic relationship types, such as SOLVES, CAUSES, IMPROVES, and USED_IN. This allows you to map complex connections between concepts, enabling advanced graph navigation and pattern detection within your knowledge base.

Question 5

How do I interact with Memento to store and retrieve information?

Accepted Answer

Memento supports natural language interaction, allowing you to store and retrieve memories through conversations with your AI assistant (e.g., 'Remember that...' or 'What do you remember about...?'). Additionally, it provides programmatic access via a Python API and REST API for more structured operations.

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