Recall FAQs

Question 1

How does Recall MCP ensure privacy and operate offline?

Accepted Answer

Recall MCP prioritizes privacy by using 100% offline local embeddings via MiniLM-L6-v2, eliminating the need for external API keys or an internet connection for vectorization. Its SQLite-backed memory ensures all data remains local and under your control.

Question 2

How does Recall MCP manage the lifecycle of memories?

Accepted Answer

It includes an automatic memory decay and garbage collection system, inspired by human memory. Memories transition from STRONG to MEDIUM to WEAK based on inactivity, and eventually, expired memories are hard deleted. Instructions are immune to this decay process.

Question 3

What is Recall MCP and what problem does it solve?

Accepted Answer

Recall MCP is a fully local, offline-first persistent memory system that gives AI agents the ability to remember, search, and forget information across sessions. It acts as a 'shared brain,' solving the problem of ephemeral AI memory and enabling knowledge sharing across multiple agents.

Question 4

Can multiple AI agents share the same memory database?

Accepted Answer

Yes, Recall MCP is designed for multi-agent support. It allows multiple AI agents (e.g., Claude, Gemini, Codex) to connect to and share the same memory database simultaneously, fostering collaborative intelligence and knowledge sharing.

Question 5

What kind of search capabilities does Recall MCP offer?

Accepted Answer

It features a powerful hybrid search combining FTS5 full-text search with 384-dimensional vector similarity. This allows agents to retrieve memories based on both keywords and semantic meaning, offering comprehensive and relevant results.

Recall

Recall

Key Features

Use Cases

Key Features

Use Cases