Digital Brain FAQs

Question 1

Which AI clients are compatible with Digital Brain?

Accepted Answer

Digital Brain is designed to be compatible with any Model Context Protocol (MCP) client. This includes popular AI tools like Claude, Cursor, OpenCode, and GitHub Copilot, allowing for seamless integration into your existing AI workflows.

Question 2

What is Digital Brain and how does it help AI clients?

Accepted Answer

Digital Brain empowers AI clients with persistent long-term memory and semantic search, functioning as a 'Second Brain' for your AI. It allows AI models to store and instantly recall knowledge, code, research, and decisions, overcoming context window limitations.

Question 3

What security measures does Digital Brain implement?

Accepted Answer

Security is a top priority. Digital Brain features Bearer token authentication with multi-key support, ensuring only authorized clients can access data. Additionally, Supabase Row Level Security (RLS) is enabled on the memories table, providing robust data isolation and protection.

Question 4

How does Digital Brain store and retrieve memories?

Accepted Answer

When you store information, Gemini Embedding 2 converts the text into a high-dimensional vector. This vector, along with the original content, is saved in Supabase pgvector. For retrieval, your query is embedded, and a semantic search using cosine similarity quickly returns the most relevant matching memories.

Question 5

What types of information can I store in Digital Brain?

Accepted Answer

You can store a wide array of information including notes, code snippets, research findings, important decisions, conversation logs, and general reference materials. The MCP API provides tools for storing, searching, listing, updating, and deleting memories with optional tags and metadata for better organization.

Digital Brain

Digital Brain

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주요 기능

사용 사례