CodeRunner: A local sandbox for your AI agents

CodeRunner helps you sandbox your AI agents and its actions inside a sandbox.

Key use case: You can run multiple Claude Code or AI agents in our sandbox without any fear of data loss and exfilteration.

For cloud managed VMs for agents, we have launched - InstaVM - Instant computers for AI agents

Quick Start

Prerequisites: Mac with macOS and Apple Silicon (M1/M2/M3/M4), Python 3.10+

git clone https://github.com/instavm/coderunner.git
cd coderunner
chmod +x install.sh
./install.sh

Stop and resume

Stop the sandbox when you are done:

container stop coderunner

Resume the same sandbox later, preserving uploads, kernels, and installed packages:

container start coderunner

To start over with a clean sandbox, delete the container and run the installer again:

container delete coderunner && ./install.sh

Disable outbound network access

By default, code running in the sandbox has unrestricted network access. To run it on a host-only network with no internet access:

CODERUNNER_NETWORK=none ./install.sh

In this mode, the MCP server is available at http://127.0.0.1:8222/mcp. The setting is fixed when the container is created; the installer refuses to resume a container with a different network mode.

Run Claude Code inside a Sandbox

./install.sh (if not already done)

container exec -it coderunner /bin/bash

root@coderunner:/app# npm install -g @anthropic-ai/claude-code

Other Integration Options

MCP server will be available at: http://coderunner.local:8222/mcp

The installer creates ~/.coderunner/venv for the Claude Desktop proxy. For the other Python examples, install their dependencies in your own virtualenv:

pip install -r examples/requirements.txt

1. Claude Desktop Integration

Configure Claude Desktop to use CodeRunner as an MCP server:

1. Copy the example configuration:

   cd examples
   cp claude_desktop/claude_desktop_config.example.json claude_desktop/claude_desktop_config.json
   

2. Edit the configuration file and replace the placeholder paths:

   • Replace /path/to/your/python with $HOME/.coderunner/venv/bin/python using the full path to your home directory
   • Replace /path/to/coderunner with the actual path to your cloned repository

   Example after editing:

   {
     "mcpServers": {
       "coderunner": {
         "command": "/Users/yourname/.coderunner/venv/bin/python",
         "args": ["/Users/yourname/coderunner/examples/claude_desktop/mcpproxy.py"]
       }
     }
   }
   

3. Update Claude Desktop configuration:

   • Open Claude Desktop
   • Go to Settings → Developer
   • Add the MCP server configuration
   • Restart Claude Desktop

4. Start using CodeRunner in Claude: You can now ask Claude to execute code, and it will run safely in the sandbox!

2. Claude Code CLI

Use CodeRunner with Claude Code CLI for terminal-based AI assistance:

Quick Start:

# 1. Install and start CodeRunner (one-time setup)
git clone https://github.com/instavm/coderunner.git
cd coderunner
sudo ./install.sh

# 2. Install the Claude Code plugin
claude plugin marketplace add https://github.com/instavm/coderunner-plugin
claude plugin install instavm-coderunner

# 3. Reconnect to MCP servers
/mcp

Installation Steps:

1. Navigate to Plugin Marketplace: