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E2B

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Cloud code execution sandbox for AI agents - lets LLMs run generated code safely in isolated environments with a Python and JS SDK and free tier.

E2B (Engineer to Business) is an open-source sandboxed cloud environment platform purpose-built for AI coding agents. It gives LLMs and autonomous agents a secure, isolated runtime to execute generated code without risk of local system exposure. Sandboxes start in under 300ms, support Python, Node.js, and custom Docker runtimes, and persist file system state across steps in multi-turn agent workflows. E2B is widely used by AI coding agent builders and integrates directly with LangChain, CrewAI, and Anthropic Claude tool use. The platform offers 50 sandbox hours per month on the free tier and has seen rapid adoption as the default execution layer for the AI coding agent ecosystem.

#code-sandbox
#ai-agents
#developer-tools
#open-source
#llm
Freemium

Free plan available

Update Tool
e2b.dev
Freemium
Pricing Model
Code & Development
Category
2023
Since
Free Plan
Access

Key Features

  • Secure isolated sandbox environments for Python, Node.js, and custom Docker runtimes
  • Sub-300ms cold start time for fast agent iteration across multi-step workflows
  • Persistent file system within each sandbox session - read, write, and execute files
  • Long-running process support for agents that run background tasks during a session
  • Python and TypeScript/JavaScript SDKs with native LangChain and CrewAI integration
  • Custom sandbox templates - build and publish reusable environments with pre-installed packages
  • Free tier includes 50 sandbox hours per month - sufficient for development and small-scale agents

Use Cases

  • AI coding agent developers giving LLMs a safe environment to execute and test generated code
  • Research teams running code-interpreting agents that analyze data and produce reports
  • Startups building AI-powered coding tools that need isolated user code execution at scale
  • Developers prototyping AutoGen or CrewAI agents that require real file system interaction

Pros

  • Open-source SDK with active development and broad framework compatibility for AI agent builders
  • Sub-300ms startup eliminates the latency bottleneck that slows down code-executing agent loops
  • Free tier is genuinely usable for development - 50 hours per month covers most prototyping cycles

Cons

  • Sandbox environments are ephemeral - persistent storage requires external integration
  • Cold start time, while fast, adds latency in ultra-low-latency agent pipelines compared to local execution
  • Custom Docker templates require DevOps familiarity to build and maintain for non-standard environments

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