Master E2B with our step-by-step tutorial, detailed feature walkthrough, and expert tips.
Sign up for free E2B account at e2b.dev and receive $100 in usage credits for immediate sandbox experimentation without upfront costs Install the E2B SDK using pip install e2b for Python or npm install e2b for JavaScript to access programmatic sandbox control capabilities Initialize your first sandbox using the SDK quickstart guide and execute a simple Python or Node.js script to verify functionality Explore pre
built templates from the template gallery including Python data science, web automation, and specialized computational environments Integrate E2B with your AI framework using comprehensive examples for LangChain, AutoGen, or custom implementations with detailed documentation
💡 Quick Start: Follow these 2 steps in order to get up and running with E2B quickly.
Explore the key features that make E2B powerful for ai infrastructure & sandboxes workflows.
secure AI sandboxes is a core E2B capability covered in the staged data and revised against the latest curl research available for this run.
Adding code interpreter features inside AI products.
virtual computers for agents is a core E2B capability covered in the staged data and revised against the latest curl research available for this run.
Running isolated research, data analysis, and file transformation workloads.
code interpreter infrastructure is a core E2B capability covered in the staged data and revised against the latest curl research available for this run.
Giving computer-use or background agents temporary virtual machines with quotas.
computer-use and background agents is a core E2B capability covered in the staged data and revised against the latest curl research available for this run.
Adding code interpreter features inside AI products.
Secure MCPs is a core E2B capability covered in the staged data and revised against the latest curl research available for this run.
Running isolated research, data analysis, and file transformation workloads.
E2B provides secure cloud sandboxes for executing AI-generated code. It is most commonly used by developers building AI agents, coding copilots, and data-analysis assistants who need a safe, isolated environment to run untrusted code produced by LLMs without risking their own infrastructure.
E2B uses Firecracker microVMs rather than containers, which provides hardware-level isolation with a dedicated kernel per sandbox. This is significantly more secure than container isolation (shared host kernel) when running untrusted LLM-generated code, while still booting in under a second.
E2B offers native SDK integrations and documented patterns for LangChain, LlamaIndex, OpenAI Assistants API, Anthropic Claude tool use, and the Vercel AI SDK. The Python and TypeScript SDKs make it straightforward to plug sandbox execution into any custom agent loop.
Yes. E2B Desktop is a sandbox variant that provides a full Linux desktop environment accessible via VNC, allowing computer-use agents to control a browser, IDE, or arbitrary GUI applications. This is the same primitive used by many production browser-automation and computer-use agents.
E2B has a free Hobby tier with $100 of compute credit to start. The Pro plan is $150/month and includes higher concurrency, longer sandbox lifetimes, and team features, plus per-second compute usage charges. Enterprise pricing covers self-hosted/on-prem deployments, SOC 2, and custom SLAs.
Now that you know how to use E2B, it's time to put this knowledge into practice.
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Tutorial updated March 2026