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 your actual Python path (e.g., /usr/bin/python3 or /opt/homebrew/bin/python3)
   • Replace /path/to/coderunner with the actual path to your cloned repository

   Example after editing:

   {
     "mcpServers": {
       "coderunner": {
         "command": "/opt/homebrew/bin/python3",
         "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!

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:

   

2. Add the InstaVM repository:

   

3. Execute Python code with Claude Code:

   

That's it! Claude Code now has access to all CodeRunner tools:

• execute_python_code - Run Python code in persistent Jupyter kernel
• navigate_and_get_all_visible_text - Web scraping with Playwright
• list_skills - List available skills (docx, xlsx, pptx, pdf, image processing, etc.)
• get_skill_info - Get documentation for specific skills
• get_skill_file - Read skill files and examples

Learn more: See the plugin repository for detailed documentation.

Create or edit ~/.config/opencode/opencode.json:

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "coderunner": {
      "type": "remote",
      "url": "http://coderunner.local:8222/mcp",
      "enabled": true
    }
  }
}

After saving the configuration:

1. Restart OpenCode
2. CodeRunner tools will be available automatically
3. Start executing Python code with full access to the sandboxed environment

1. Set your OpenAI API key:

   export OPENAI_API_KEY="your-openai-api-key-here"
   

2. Run the client:

   python examples/openai_agents/openai_client.py
   

3. Start coding: Enter prompts like "write python code to generate 100 prime numbers" and watch it execute safely in the sandbox!

{
  "theme": "Default",
  "selectedAuthType": "oauth-personal",
  "mcpServers": {
    "coderunner": {
      "httpUrl": "http://coderunner.local:8222/mcp"
    }
  }
}

{
  "mcpServers": {
    "coderunner": {
      "command": "/path/to/venv/bin/python",
      "args": [
        "/path/to/coderunner/examples/claude_desktop/mcpproxy.py"
      ],
      "disabled": false,
      "autoApprove": [
        "execute_python_code"
      ]
    }
  }
}