E2B MCP Server - Sandboxed Code Execution

• 7 atomic tools for Python/JavaScript execution and file management
• Enterprise-grade security validation and error handling
• Complete with proof videos hosted on Google Drive
• Supports package installation and sandbox management

Proof videos: https://drive.google.com/drive/folders/1jkqqiY7brz0OfGZT3MwDdJRfrzMqq9mc?usp=drive_link

Description

This PR adds a production-ready E2B MCP Server that provides secure, sandboxed code execution capabilities for AI
assistants. The server integrates with E2B's cloud sandbox environment to enable safe Python and JavaScript code
execution, file management, and package installation.

Key Features:

• Atomic Tools: 7 well-defined tools (execute_python, execute_javascript, create_file, read_file,
  list_files, install_packages, get_sandbox_info)
• Security-First Design: Input validation, output sanitization, dangerous pattern detection
• Resource Management: Automatic sandbox cleanup, idle timeout handling, resource monitoring
• Multi-language Support: Both Python and JavaScript execution environments
• Enterprise Architecture: Comprehensive logging, error handling, graceful shutdown

Related issue

Contributing a new MCP server to expand Klavis AI's ecosystem as per the submission guidelines.

Type of change

• New MCP feature (non-breaking change which adds functionality)

How has this been tested?

Comprehensive End-to-End Testing:
All 7 tools have been tested with natural language queries in Claude Desktop/Cursor showing:

• Correct tool selection by AI
• Server logs confirming functionality
• Successful results returned to client

Video Proof Available:
https://drive.google.com/drive/folders/1jkqqiY7brz0OfGZT3MwDdJRfrzMqq9mc?usp=drive_link

Test Coverage:

• ✅ Python code execution with package installation
• ✅ JavaScript/Node.js code execution
• ✅ File operations (create, read, list)
• ✅ Package management (pip, npm)
• ✅ Sandbox lifecycle management
• ✅ Security validation and error handling
• ✅ Natural language integration testing

Checklist

• I have performed a self-review of my own code
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• My changes generate no new warnings
• I have added tests that prove my fix is effective or that my feature works
• New and existing tests pass locally with my changes
• Follows Klavis AI MCP Server guidelines (atomic tools, clear descriptions, robust error handling)
• Includes comprehensive README.md with installation and setup instructions
• Provides mandatory proof of correctness videos for all tools
• Implements security best practices and input validation