Best Sandbox & Execution Top 20
Top 20 most popular open-source Sandbox & Execution projects, ranked by GitHub Stars.
Daytona
72.4k StarsDaytona provides secure development-environment infrastructure for coding agents and automation workflows, serving as a runtime base for remote execution tasks.
DeerFlow
67.0k StarsAn open-source long-horizon SuperAgent harness by ByteDance that researches, codes, and creates with sandboxes, memories, tools, skills, subagents and message gateway for complex tasks.
CUA
16.0k StarsCUA provides open-source infrastructure for Computer-Use Agents, including sandboxes, SDKs, and benchmarks to train and evaluate AI agents that control full desktops (macOS, Linux, Windows).
Context Mode
14.4k StarsContext Mode is a context window optimization tool for AI coding agents that sandboxes tool output for 98% context reduction across 12 major platforms.
E2B
12.2k StarsE2B provides secure cloud sandboxes for AI agents, supporting code execution, file operations, and isolated compute as an execution layer for coding and automation workflows.
OpenSandbox
10.6k StarsOpenSandbox is an open-source, secure, fast, and extensible sandbox runtime for AI agents, developed by Alibaba.
Databend
9.3k StarsA Data Agent Ready Warehouse unifying Analytics, Search, AI, and Python Sandbox in one system. Runs on your S3 with built-in vector search, full-text search, and Python execution for AI-powered data analysis.
Steel Browser
7.0k StarsSteel Browser is an open-source browser sandbox purpose-built for AI agents and applications. It provides a full browser API with session management, proxy integration, and built-in anti-detection, enabling web automation without infrastructure headaches.
Microsandbox
6.0k StarsSecure, local, cross-platform and programmable sandboxes for AI agents. Provides strict resource isolation using microVM technology.
CubeSandbox
5.4k StarsA high-performance, secure sandbox service for AI agents by Tencent Cloud, built on RustVMM and KVM with hardware-level isolation, sub-60ms cold start, <5MB memory overhead, and E2B SDK compatibility.
Magicrew
4.8k StarsOpen-source all-in-one AI productivity platform combining a generalist AI agent, workflow engine, instant messaging, and online documents
Agent Sandbox
4.6k StarsAll-in-One Sandbox for AI Agents that combines Browser, Shell, File, MCP and VSCode Server in a single Docker container, providing a secure isolated execution environment for agents.
WebContainer
4.6k StarsDev environments in your web app — run Node.js runtime environments in the browser with full sandboxing, no server-side execution needed.
Judge0
4.2k StarsA mature open-source code execution and online judge system supporting multi-language compilation, resource limits, and API access, suitable for agent code execution tasks.
Sandcastle
4.1k StarsA TypeScript tool for orchestrating sandboxed coding agents with secure execution environments powered by sandcastle.run.
Sandbox Runtime
4.0k StarsAn experimental lightweight isolated runtime from Anthropic for executing agent tasks in a sandboxed environment.
Arrow
3.5k StarsArrow is the first UI framework for the agentic era, tiny and performant with built-in WASM sandboxes for safe code execution, purpose-built for building AI agent interfaces.
Amazon Bedrock Agentcore Samples
2.8k StarsAmazon Bedrock Agentcore samples that accelerate AI agents into production with scale, reliability, and security for real-world deployment.
Moltis
2.7k StarsA secure persistent personal agent server in Rust. One binary, sandboxed execution, multi-provider LLMs, voice, memory, and MCP tools.
Codel
2.4k StarsFully autonomous AI Agent that can perform complicated tasks and projects using terminal, browser, and editor with sandboxed execution.
Related Articles
Agent Evaluation and Testing: From Vibe Checks to End-to-End Pipelines
Most teams evaluate agents by checking a few examples. Real evaluation needs layered metrics, non-rotting datasets, and judges that push back. This article provides runnable code patterns and a practical decision framework.
Sandboxing AI Agents: Isolation Strategies for Safe Code Execution
Comparing container, WebAssembly, and process-level isolation approaches, with practical code for safely executing agent-generated code.
Browser Agents in Practice: Architecture and Pitfalls of AI-Controlled Browsers
Breaking down three abstraction layers for browser automation—from raw Playwright to structured extraction—with production patterns, runnable code, and common pitfalls.