Open-source alternatives to Codesandbox Client

Coder is a self-hosted platform for provisioning and managing isolated, containerized development environments. It provides a centralized infrastructure for teams to deploy ephemeral workspaces on private cloud or on-premises hardware, ensuring consistent toolchains and dependencies across distributed development environments. The platform distinguishes itself through its focus on secure, infrastructure-as-code governance and autonomous agent integration. It allows organizations to define reusable, versioned environment templates that integrate with existing identity providers and role-based

The sandbox-sdk is a development kit designed for building secure, isolated execution environments on a global edge network. It provides a framework for creating ephemeral, containerized workspaces that allow developers to run untrusted code, manage build tasks, and host automated scripts without compromising host system security. By leveraging a serverless runtime, the platform enables the deployment of these environments directly at the network edge to ensure low-latency performance. The platform distinguishes itself by integrating language models with sandboxed execution, facilitating the

Open Interpreter is an autonomous agent runtime that translates natural language instructions into executable code to interact with local software and operating systems. It functions as an orchestration framework that connects language models to a secure execution environment, enabling the development of agents capable of managing system resources and performing complex tasks. To ensure safety, the system mandates explicit user verification before executing any generated code and provides robust isolation through containerized sandboxing. The project distinguishes itself through its deep inte

This project is an autonomous AI software engineering orchestrator and development loop manager. It implements a system for managing AI coding agents that execute iterative development cycles, processing technical requirements through a persistent task queue based on priority and dependencies. The system synchronizes development progress with GitHub by converting issues and comments into actionable plans and automating pull requests and status updates. It provides a secure execution layer by running coding operations within an isolated sandbox environment to protect the host file system. To

Acontext is an LLM orchestration backend and agent memory framework designed to manage session state and knowledge for AI agents. It functions as a context manager and orchestration layer that integrates model providers with a secure code sandbox and a zero-knowledge data store. The project is distinguished by its approach to knowledge distillation, capturing agent learnings as reusable Markdown skills and structured memory files. It provides a secure execution environment where shell commands and scripts run in isolated containers with the ability to mount these persistent skill files direct

Devika is an autonomous AI software engineering system designed to plan, write, and debug code from high-level natural language instructions. It functions as an agentic software engineer that decomposes complex objectives into actionable coding steps for autonomous execution. The system integrates cloud-based and self-hosted large language models through a provider-agnostic layer, allowing for multi-model reasoning and code completion. It distinguishes itself by combining these models with a sandboxed execution environment for running code across different operating systems and a web-browsing

Drone is a container-based continuous integration and delivery platform, source control management system, and artifact registry. It functions as a hosted workspace provider for cloud-based developer environments and a system for hosting and versioning code repositories. The platform executes build and deployment pipelines within isolated containers, using declarative configurations to automate software delivery. It includes a centralized registry for managing and versioning compiled binaries and build outputs to ensure consistent deployments across environments. The system covers a broad ca

This project is an interactive programming curriculum and educational system designed to teach computer science and software engineering. It provides a structured set of courses and professional roadmaps focused on backend engineering, DevOps, and systems fundamentals. The platform is distinguished by an AI-powered coding tutor that provides Socratic guidance and contextual hints to help students find solutions independently. It features a browser-based code sandbox using WebAssembly to eliminate local environment setup, alongside automated test-based grading and spaced-repetition logic to re

This project is an interactive coding learning platform and open-source educational courseware designed for mastering web development. It provides a browser-based environment where users can engage with a structured curriculum covering front-end, back-end, and data visualization skills through hands-on exercises. The platform distinguishes itself by integrating a browser-based code sandbox and a nonprofit technical partnership portal. This framework allows learners to transition from guided lessons to building and maintaining real-world software applications for nonprofit organizations. The

Moltworker is an AI agent sandbox and model orchestrator designed for the secure execution of untrusted code and shell commands generated by large language models. It functions as a gateway proxy that routes requests to multiple AI providers through a unified interface, integrating a container runtime backed by S3-compatible object storage to persist state across ephemeral lifecycles. The system distinguishes itself by combining an AI model orchestrator with a headless browser controller for automated web scraping and screenshot capture. It manages the full lifecycle of AI agents, including m

OpenSandbox is a secure execution environment and runtime designed for running untrusted code and scripts generated by AI agents. It utilizes a containerized code execution engine and microVM-based isolation to protect host systems from malicious actions while providing isolated virtual environments. The project features a sandbox server based on the Model Context Protocol to automate the creation and control of virtual workspaces. It supports the deployment of secure remote desktop hosts, including headless web browsers and editor instances, for automated interaction. The system includes an

Fragments is an open-source AI code generation sandbox that produces code automatically based on user prompts and executes it inside isolated cloud environments. The project provides a secure foundation for running AI-generated code by sandboxing execution away from the host system, preventing potential harm while allowing users to see results immediately. The sandbox supports customization through configurable execution environments defined via Dockerfiles, enabling code to run in specific runtimes or frameworks. Users can integrate different language models and model providers by registerin

E2B is a cloud-based infrastructure platform designed to provide secure, isolated execution environments for code and shell commands. It functions as an ephemeral orchestrator that provisions lightweight virtual machines, allowing developers and autonomous agents to run untrusted processes within a sandbox that is completely separated from the host system. The platform distinguishes itself through its focus on programmable, serverless workspaces that support the full lifecycle of cloud-based development. By utilizing hardware-level isolation and snapshot-based resumption, it enables the near-

Bolt.diy is a browser-based integrated development environment designed for full-stack web application construction. It functions as an AI-powered development platform that automates project scaffolding, code generation, and application deployment directly within the browser. The platform distinguishes itself through a secure, isolated execution environment that runs development servers and package managers in a sandboxed container. It utilizes a provider-agnostic model abstraction, allowing users to connect multiple artificial intelligence services to power automated reasoning and code gener

ms-agent is an LLM agent framework and multi-agent orchestration system designed to build autonomous entities that combine large language models with tool calling and structured workflows. It serves as a tool integration platform and workflow engine for executing complex tasks through the coordination of specialized agents. The project distinguishes itself through a multimodal agent workflow engine capable of automating the production of text, images, and video. It features a sandboxed code execution environment for running generated code and quantitative data analysis in isolated containers,

vibesdk is an agentic software development platform and framework designed to coordinate autonomous agents that write, debug, and refine full-stack applications from natural language. It serves as a cloud-native application orchestrator and an LLM-powered code generation framework that converts prompts into functional code through iterative conversations and multi-phase agent behaviors. The project distinguishes itself by providing a complete toolchain for building AI development platforms. This includes the ability to integrate various model providers, construct custom LLM toolkits, and mana

This project provides a system for managing agent context and session memory, featuring an agent context compactor, an AI session memory manager, and a tool output sandbox. It functions as a middleware layer and server extension for the Model Context Protocol to optimize context windows and reduce token usage. The system optimizes agent performance by sandboxing tool outputs and externalizing large data sets, replacing raw I/O with pointers and concise summaries. It employs a persistent knowledge base that indexes session history and tool outputs for retrieval via full-text search, ensuring s

This project provides secure, containerized infrastructure designed for autonomous agents, remote code execution, and cloud development. It functions as a sandboxed environment where AI agents and external processes can execute code, run shell commands, and manage files while remaining isolated from the host system. The system distinguishes itself by implementing the Model Context Protocol, allowing it to act as a standardized tool server that exposes browser and filesystem capabilities to compatible clients. It further integrates headless browser automation, enabling programmatic web navigat

CubeSandbox is a Kubernetes-based platform for executing AI agents in secure, lightweight environments. It provides a code execution sandbox that uses hardware isolation and dedicated guest kernels to run untrusted code without risking the host system. The project features a network egress firewall that restricts outbound communication via domain allowlists and audit logging. It also includes a container snapshotting manager capable of capturing the runtime memory and disk state of environments to enable instant cloning and recovery. The platform covers cluster orchestration through a web-ba

OpenSandbox is a secure sandbox runtime and containerized code execution engine designed to run AI-generated code and scripts in isolated environments. It serves as a workload orchestrator that prevents host system contamination by utilizing kernel-level isolation to execute arbitrary commands and scripts. The project distinguishes itself by providing a model context server that bridges large language models to the sandbox for performing file operations and system commands. It also includes a remote GUI sandbox that supports browser automation and desktop interfaces via remote access protocol

rlm is an LLM code execution engine and orchestration framework designed to coordinate multiple language model calls and recursive sub-tasks through a programmable environment. It provides a sandboxed REPL environment and a recursive context processor to handle inputs that exceed standard token limits by programmatically decomposing prompts. The project differentiates itself through a reinforcement learning training harness used to teach models how to utilize recursive calls and code execution. It includes a reasoning visualization system that records and renders execution trajectories to ana

Cube Studio is a cloud-native MLOps platform and Kubernetes-based AI orchestrator designed for the entire machine learning lifecycle. It provides a distributed training framework for large-scale model fine-tuning, a GPU resource manager for hardware virtualization, and an ML pipeline orchestrator that uses visual directed acyclic graphs to manage end-to-end workflows. The platform distinguishes itself through its specialized LLM inference server, which supports retrieval-augmented generation and the construction of private knowledge bases. It features a dedicated system for supervised fine-tu

Yao is an LLM agent framework and low-code web app builder designed for orchestrating autonomous AI agents. It provides a platform to design, deploy, and coordinate agents with specialized personas that can plan tasks, utilize external tools, and execute multi-stage pipelines. The project distinguishes itself through a Model Context Protocol server for connecting assistants to external binaries and HTTP services, and a gRPC remote execution engine that allows agents to manage remote servers and devices. It includes a model-agnostic provider bridge that supports dynamic switching between vario

This is an open-source framework for building stateful, durable AI agents that run on Cloudflare Workers. It provides a runtime for long-lived agents that maintain a persistent identity, local SQL storage, and real-time connections, utilizing a lifecycle where agents hibernate when idle and wake on demand. The project distinguishes itself through its multi-channel orchestration, allowing a single agent to be deployed across voice, email, and chat interfaces with unified state. It implements the Model Context Protocol for standardized tool and data exchange and includes a dedicated framework f

container-use is a containerized AI execution environment and code sandbox designed to provide a secure space for AI coding agents to execute commands and build applications. It functions as a workspace orchestrator that provisions isolated containers mapped to git branches, allowing multiple agents to operate in parallel without state conflicts or affecting the host system. The project serves as a Model Context Protocol server, bridging AI agents to containerized environments for standardized tool access. It enables a workflow for reviewing and merging changes made by agents within these iso

Lua is an embeddable scripting language written in ISO C, designed to be integrated into host applications for runtime customization. It provides a C-based scripting engine and a prototype-based object model that utilizes associative arrays and metatables to implement inheritance and complex data structures. The language features a cooperative multitasking system that manages concurrent execution threads via coroutines and an incremental garbage collector for automatic memory management. It includes a safe code sandbox to isolate global state and run untrusted scripts within a protected envir

Humanlayer is an LLM coding agent orchestrator and AI-driven workflow manager designed to coordinate multiple agents in researching, designing, and implementing features across complex codebases. It provides a multi-agent development workspace that groups AI sessions, versioned design artifacts, and worktrees into collaborative team tasks. The system features a bring-your-own-key LLM gateway to connect external AI model subscriptions and API keys. It utilizes remote AI agent daemons to run long-term coding sessions on cloud infrastructure, maintaining progress independently of the user's acti