How does Engram ensure data privacy and security?

Engram is 100% local, storing all memories and embeddings in an on-device SQLite database. It has zero cloud dependencies, meaning no data ever leaves your machine, and includes automated secret detection to prevent sensitive information from being stored.

What is Engram and why should I use it?

Engram is a local-first memory server that gives AI agents persistent memory, running entirely on your machine. It eliminates cloud dependencies, API keys, and privacy concerns, offering complete data control and a simple two-minute setup.

What AI agents is Engram compatible with?

Engram provides first-class Model Context Protocol (MCP) integration, making it compatible with popular AI agents like Claude Desktop, Claude Code, Cursor, Cline, and Windsurf. It also offers a REST API for custom integrations.

What unique memory features does Engram offer?

Engram includes hybrid search combining vector similarity with full-text search (FTS5), smart deduplication to merge similar memories, automated secret detection, a memory feedback loop, namespace isolation, temporal queries, and a built-in web dashboard.

Engram

Name: Engram
Author: HBarefoot

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Provides persistent, local-first memory for AI agents using SQLite and local embeddings, ensuring zero cloud dependencies and enhanced privacy.

概要

Engram is a powerful local-first memory server designed to give AI agents like Claude, Cursor, and Windsurf the ability to remember information across sessions without relying on any external cloud services or API keys. It runs entirely on your local machine, utilizing a SQLite database and local embedding models for complete data privacy and cost-free operation. This approach eliminates the complexities and overhead associated with traditional cloud-based AI memory solutions, making it an ideal choice for developers seeking a secure, private, and easy-to-set-up memory layer for their AI applications.

主な機能

0 GitHub stars
First-class Model Context Protocol (MCP) integration for AI agents
Automated secret detection to block sensitive information from being stored
Hybrid search combining vector similarity with full-text search (FTS5)
Fully local memory storage with SQLite and on-device embeddings
Smart deduplication that automatically detects and merges similar memories

ユースケース

Provide AI agents with persistent, long-term memory across sessions and different client applications
Export project context and AI agent learnings as structured documentation in various formats
Organize and isolate AI agent memories by project, client, or specific scope using namespaces

概要

主な機能

0 GitHub stars
First-class Model Context Protocol (MCP) integration for AI agents
Automated secret detection to block sensitive information from being stored
Hybrid search combining vector similarity with full-text search (FTS5)
Fully local memory storage with SQLite and on-device embeddings
Smart deduplication that automatically detects and merges similar memories

ユースケース

Provide AI agents with persistent, long-term memory across sessions and different client applications
Export project context and AI agent learnings as structured documentation in various formats
Organize and isolate AI agent memories by project, client, or specific scope using namespaces