README
¶
Persistent memory for AI coding agents
Agent-agnostic. Single binary. Zero dependencies.
Installation • Agent Setup • Architecture • Plugins • Contributing • Full Docs
engram
/ˈen.ɡræm/— neuroscience: the physical trace of a memory in the brain.
Your AI coding agent forgets everything when the session ends. Engram gives it a brain.
A Go binary with SQLite + FTS5 full-text search, exposed via CLI, HTTP API, MCP server, and an interactive TUI. Works with any agent that supports MCP — Claude Code, OpenCode, Gemini CLI, Codex, VS Code (Copilot), Antigravity, Cursor, Windsurf, or anything else.
Agent (Claude Code / OpenCode / Gemini CLI / Codex / VS Code / Antigravity / ...)
↓ MCP stdio
Engram (single Go binary)
↓
SQLite + FTS5 (~/.engram/engram.db)
Quick Start
Install
brew install gentleman-programming/tap/engram
Windows, Linux, and other install methods → docs/INSTALLATION.md
Setup Your Agent
| Agent | One-liner |
|---|---|
| Claude Code | claude plugin marketplace add Gentleman-Programming/engram && claude plugin install engram |
| OpenCode | engram setup opencode |
| Gemini CLI | engram setup gemini-cli |
| Codex | engram setup codex |
| VS Code | code --add-mcp '{"name":"engram","command":"engram","args":["mcp"]}' |
| Cursor / Windsurf / Any MCP | See docs/AGENT-SETUP.md |
Full per-agent config, Memory Protocol, and compaction survival → docs/AGENT-SETUP.md
That's it. No Node.js, no Python, no Docker. One binary, one SQLite file.
How It Works
1. Agent completes significant work (bugfix, architecture decision, etc.)
2. Agent calls mem_save → title, type, What/Why/Where/Learned
3. Engram persists to SQLite with FTS5 indexing
4. Next session: agent searches memory, gets relevant context
Full details on session lifecycle, topic keys, and memory hygiene → docs/ARCHITECTURE.md
MCP Tools
| Tool | Purpose |
|---|---|
mem_save |
Save observation |
mem_update |
Update by ID |
mem_delete |
Soft or hard delete |
mem_suggest_topic_key |
Stable key for evolving topics |
mem_search |
Full-text search |
mem_session_summary |
End-of-session save |
mem_context |
Recent session context |
mem_timeline |
Chronological drill-in |
mem_get_observation |
Full content by ID |
mem_save_prompt |
Save user prompt |
mem_stats |
Memory statistics |
mem_session_start |
Register session start |
mem_session_end |
Mark session complete |
Full tool reference → docs/ARCHITECTURE.md#mcp-tools
Terminal UI
engram tui
Navigation: j/k vim keys, Enter to drill in, / to search, Esc back. Catppuccin Mocha theme.
Git Sync
Share memories across machines. Uses compressed chunks — no merge conflicts, no huge files.
engram sync # Export new memories as compressed chunk
git add .engram/ && git commit -m "sync engram memories"
engram sync --import # On another machine: import new chunks
engram sync --status # Check sync status
Full sync documentation → DOCS.md
CLI Reference
| Command | Description |
|---|---|
engram setup [agent] |
Install agent integration |
engram serve [port] |
Start HTTP API (default: 7437) |
engram mcp |
Start MCP server (stdio) |
engram tui |
Launch terminal UI |
engram search <query> |
Search memories |
engram save <title> <msg> |
Save a memory |
engram timeline <obs_id> |
Chronological context |
engram context [project] |
Recent session context |
engram stats |
Memory statistics |
engram export [file] |
Export to JSON |
engram import <file> |
Import from JSON |
engram sync |
Git sync export |
engram version |
Show version |
Documentation
| Doc | Description |
|---|---|
| Installation | All install methods + platform support |
| Agent Setup | Per-agent configuration + Memory Protocol |
| Architecture | How it works + MCP tools + project structure |
| Plugins | OpenCode & Claude Code plugin details |
| Comparison | Why Engram vs claude-mem |
| Contributing | Contribution workflow + standards |
| Full Docs | Complete technical reference |
License
MIT
Inspired by claude-mem — but agent-agnostic, simpler, and built different.
Directories
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| Path | Synopsis |
|---|---|
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cmd
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engram
command
Engram — Persistent memory for AI coding agents.
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Engram — Persistent memory for AI coding agents. |
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internal
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mcp
Package mcp implements the Model Context Protocol server for Engram.
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Package mcp implements the Model Context Protocol server for Engram. |
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server
Package server provides the HTTP API for Engram.
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Package server provides the HTTP API for Engram. |
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setup
Package setup handles agent plugin installation.
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Package setup handles agent plugin installation. |
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store
Package store implements the persistent memory engine for Engram.
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Package store implements the persistent memory engine for Engram. |
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sync
Package sync implements git-friendly memory synchronization for Engram.
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Package sync implements git-friendly memory synchronization for Engram. |
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tui
Package tui implements the Bubbletea terminal UI for Engram.
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Package tui implements the Bubbletea terminal UI for Engram. |
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version
Package version checks for newer engram releases on GitHub.
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Package version checks for newer engram releases on GitHub. |