Enables efficient AI agent operations through sandboxed Python code execution with progressive tool discovery, PII tokenization, and skills persistence, achieving up to 98.7% token reduction by processing data in a sandbox rather than in context.
Enables efficient code execution in a secure sandbox with 98.7% token reduction by allowing agents to write JavaScript/TypeScript code to interact with tools, process data, and maintain state instead of loading all tool definitions into context.
Cuts AI token costs by running user code in a secure sandbox, so data never enters the context window, enabling efficient data processing with MCP protocol.
Provides a secure, containerized Python sandbox for executing LLM-generated code with multi-layer isolation, along with JSON/CSV validation and workspace state snapshots.
Provides sandboxed code execution for AI agents with support for Python, JavaScript, and shell commands. Includes comprehensive safety features like destructive pattern blocking, timeout protection, and restricted file access for secure production use.
Enables LLMs to execute Python code securely in a sandboxed environment. Supports configurable restrictions like no network access and returns results including files.
