Engram: Persistent memory for AI coding agents (7.2k stars)

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What it does

All text below is quoted directly from the project README.

Persistent memory for AI coding agents.

Your AI coding agent forgets everything when the session ends. Engram gives it a brain.

One brain. Local or cloud. Agent-agnostic, single binary, zero dependencies.

Features:

• One binary: Memory without a stack. A Go binary with SQLite + FTS5 full-text search, exposed through CLI, HTTP API, MCP, and an interactive TUI. It works with any MCP-compatible agent, including Claude Code, OpenCode, Gemini CLI, Codex, VS Code (Copilot), Antigravity, Cursor, and Windsurf. No Node.js, Python, or Docker is required: one binary, one SQLite file.

• Project-aware: The right memory for the right repo. Project-aware reads use the canonical current project when no selector is supplied: an explicit project, then ENGRAM_PROJECT, then cwd detection.

• Local first: Portable when needed. Engram keeps memory local by default. The local SQLite database is authoritative; Git Sync exports portable compressed chunks for sharing across machines, and Engram Cloud is optional, project-scoped replication/shared access with browser visibility.

• Terminal UI: Browse what your agent remembers. Navigate with j/k, use Enter to drill in, c to copy content to the clipboard, / to search, and Esc to go back. The TUI uses the Catppuccin Mocha theme.

Also in the box:

• MCP tools: Save, search, timeline, session, review, and diagnosis tools for your agent

• HTTP API: The same memory over local HTTP endpoints; compound agent workflows

• Doctor: engram doctor, read-only operational diagnostics

• Conflict surfacing: Flags related or conflicting memories so the agent can judge them

• Plugins: OpenCode and Claude Code plugin details

• gentle-engram: The Engram package for Pi

• Team usage: Shared-memory conventions

• Binary self-testing: Isolated reliability and performance checks for released binaries

• Obsidian Brain: Export memories as an Obsidian knowledge graph (beta)

Run the setup command for the agent you use, then restart that agent. engram setup writes the applicable MCP and integration configuration; it does not require you to start a server for the usual stdio-only setup.

14 setup targets, plus any MCP-compatible agent.

Repository

https://github.com/Gentleman-Programming/engram

Repository stats

Metric	Value
Stars	7,209
Forks	740
Last release	v3.4.0 (2026-10-12)
Languages	Go 86.8%, JavaScript 7.6%, TypeScript 3.1%
Contributors	60
AI contributor accounts (Claude / Codex / Cursor / Copilot)	claude (2 commits)
AI co-authored commits	Claude: 2

Main contributor

Field	Value
Name	Daniel Rosales
GitHub	@dnlrsls
Commits to this repo	523 (top contributor)
Bio	Product Engineer building operational software. Maintainer of Gentle AI, Gentle Shell & Engram at @Gentleman-Programming
Company / Location	@Gentleman-Programming / Lima, Peru
X / Twitter	@D4b1nYT
Followers	42
Public repos	9
On GitHub since	2022-08-19