Skip to main content
hc
Submit
mcpSource-backedReview first Safety ✓ Privacy ✓

Engram MCP Server

Local-first persistent memory MCP server for AI coding agents, backed by a single Go binary, SQLite, FTS5 search, CLI, HTTP API, and TUI.

by Gentleman Programming·added 2026-06-05·
Claude CodeClaude Desktop
HarnessClaude CodeClaude Desktop
Review first — review before installing

Open the source and read safety notes before installing.

Safety notes

  • Engram can save, update, delete, search, compare, judge, merge, and summarize project memories that may influence future agent behavior.
  • Incorrect or stale memories can steer an agent toward bad assumptions, so review saved decisions, architecture notes, and task learnings periodically.
  • Use explicit project selection or repo-local configuration when multiple projects are visible to the MCP server.
  • Cloud sync is opt-in; review project scope, tokens, allowed projects, and repair flows before enabling shared replication.

Privacy notes

  • Memories can contain product plans, architecture decisions, code paths, prompts, implementation notes, incident details, and sensitive lessons learned.
  • Local SQLite storage, exported sync chunks, Git-tracked memory files, cloud replication, HTTP API logs, and TUI copy actions can expose memory content.
  • Do not store secrets, credentials, customer data, or unreleased security details unless the local store and any sync targets are approved for that data.

Prerequisites

  • Engram binary installed through Homebrew, GitHub Releases, Go install, or a source build.
  • MCP-compatible coding agent such as Claude Code, Codex, OpenCode, Gemini CLI, VS Code, Cursor, or Windsurf.
  • Project selection rules for where memories should be written, especially in monorepos or parent workspaces.
  • Optional cloud server configuration only when shared or cross-machine memory replication is desired.

Schema details

Install type
cli
Troubleshooting
No
Source repository stats
Scope
Source repo
Collection metadata
Estimated setup
10 minutes
Difficulty
intermediate
Full copyable content
{
  "mcpServers": {
    "engram": {
      "command": "engram",
      "args": ["mcp"]
    }
  }
}

About this resource

Content

Engram MCP Server gives AI coding agents persistent project memory through a local-first Go binary backed by SQLite and FTS5 search. It exposes memory tools over MCP stdio while also offering CLI, HTTP API, sync, and TUI interfaces for manual inspection and maintenance.

The upstream README describes Engram as agent-agnostic and compatible with MCP clients including Claude Code, Codex, OpenCode, Gemini CLI, VS Code, Cursor, and Windsurf. The core MCP path is engram mcp; setup helpers are available for several agents.

Source Review

These sources were reviewed on 2026-06-05. Prefer the live installation and agent setup docs for current binary distribution, setup helpers, MCP tool modes, project detection, and cloud sync behavior.

Features

  • Single Go binary with no Node, Python, or Docker runtime dependency for local MCP usage.
  • Local SQLite and FTS5-backed memory search.
  • MCP tools for saving, updating, deleting, searching, contextualizing, summarizing, judging, comparing, and merging memories.
  • Session lifecycle helpers for start, end, and summary workflows.
  • Project detection and explicit project selection rules.
  • TUI for inspecting and searching memories outside the agent.
  • Git sync and optional cloud replication for cross-machine or team workflows.
  • Setup helpers for multiple MCP-compatible coding agents.

Installation

After installing the engram binary, configure an MCP client to launch the stdio server:

{
  "mcpServers": {
    "engram": {
      "command": "engram",
      "args": ["mcp"]
    }
  }
}

The upstream docs also provide setup helpers such as engram setup codex, engram setup opencode, and client-specific manual configuration.

Use Cases

  • Preserve architecture decisions and implementation lessons across agent sessions.
  • Recover relevant context after conversation compaction.
  • Search prior work before changing a project again.
  • Share project memories across machines through reviewed sync workflows.
  • Use memory conflict tools to surface contradictory decisions or stale notes.

Safety and Privacy

Persistent memory can be quietly powerful. Review what agents save, prune stale or incorrect entries, and make project selection explicit when the MCP server can see multiple repositories. Bad memories can become bad future instructions.

Memory content may include private architecture, project strategy, prompts, paths, code details, incidents, and customer context. Treat local stores, exported sync chunks, Git sync files, cloud replicas, HTTP API logs, and copied TUI output as sensitive project data.

Duplicate Check

No Gentleman-Programming/engram entry, Engram MCP entry, or matching source URL was found in content/mcp. This is distinct from general memory or notes tools because Engram exposes a coding-agent memory protocol over MCP with local SQLite search and optional sync.

#memory#coding-agents#sqlite#local-first#search

Source citations

Signals

Loading live community signals…

More like this, weekly

A short, calm digest of reviewed Claude resources. Unsubscribe any time.