Enables LLMs to safely execute code in isolated Docker containers with resource limits and security controls, supporting session management and automatic dependency installation.
Provides a secure, containerized Python sandbox for executing LLM-generated code with multi-layer isolation, along with JSON/CSV validation and workspace state snapshots.
A secure Docker-based environment that allows AI assistants to safely execute code without direct access to the host system by running all code within isolated containers.
Enables AI agents to work in a persistent, isolated Linux workspace with file management, Bash execution, SSH/SFTP access, and durable storage while keeping workloads contained from the host and private networks.
Enables LLMs to automatically diagnose coding errors through codebase search, test execution, and live debugger integration (DAP/V8 CDP). Provides a secure, policy-gated environment for investigating failures while preventing destructive operations.