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Install dependencies

uv sync

Prerequisites

• Python ≥ 3.13
• uv package manager (recommended) or pip

Install uv if you don't have it:

curl -LsSf https://astral.sh/uv/install.sh | sh

Build standalone binary (requires pyinstaller)

pip install pyinstaller pyinstaller --clean code-memory.spec

Installation

Install with pip

pip install code-memory

Install & Run

```bash

Install from PyPI

pip install code-memory

Build package

uv build

Method 2: Offline pip Install

1. Download the wheel from PyPI on a connected machine
2. Transfer and install: pip install code-memory-*.whl
3. Pre-cache the model as above
4. Run offline

Quickstart

Shared SSE Server (Reduce Memory Usage)

By default, each MCP host project launches its own code-memory process, which loads the embedding model (~1–2 GB) once per project. To avoid this, you can run a single shared instance over SSE (Server-Sent Events) and point all your MCP hosts at it.

Configure Your MCP Host

You can use either uvx (requires Python) or the standalone binary (no dependencies).

Configure MCP hosts to use the shared server

Instead of launching a new process, point your MCP host at the running SSE endpoint.

Claude Desktop

{
  "mcpServers": {
    "code-memory": {
      "url": "http://127.0.0.1:8765/sse"
    }
  }
}

VS Code (Copilot / Continue)

{
  "servers": {
    "code-memory": {
      "url": "http://127.0.0.1:8765/sse"
    }
  }
}

Claude Code (CLI) — .mcp.json

{
  "mcpServers": {
    "code-memory": {
      "url": "http://127.0.0.1:8765/sse"
    }
  }
}

Tip: Configure uvx code-memory --transport sse to start via a single-instance service manager (e.g. systemd user service, launchd agent, or another one-time login/startup mechanism) so the shared server starts automatically.

Security: The SSE endpoint is unauthenticated. Keep the default --host 127.0.0.1 so only local processes can connect; do not bind to 0.0.0.0 or a public interface unless you've put authentication in front of it.

Configuration

CLI Options

Environment Variables

Example:

CODE_MEMORY_LOG_LEVEL=DEBUG uvx code-memory

Gemini CLI / Gemini Code Assist

Add to your MCP settings (e.g. ~/.gemini/settings.json):

{
  "mcpServers": {
    "code-memory": {
      "command": "uvx",
      "args": ["code-memory"]
    }
  }
}

VS Code (Copilot / Continue)

Add to .vscode/mcp.json in your workspace:

{
  "servers": {
    "code-memory": {
      "command": "uvx",
      "args": ["code-memory"]
    }
  }
}

Troubleshooting