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E2

E2B

@FoundryLabs, Inc.8600

E2B is an open-source runtime for executing AI-generated code in secure cloud sandboxes. Made for agentic & AI use cases.

ai-agents
code-execution
sandbox
cloud-runtime
llm-tool

E2B is an open-source cloud runtime designed for executing AI-generated code within secure sandboxes. It serves as a crucial tool for developing and deploying agentic and AI-powered applications, providing a robust and isolated environment for code execution.

What it does: E2B offers virtual machines (sandboxes) where AI agents can run code, perform data analysis, visualize data, interact with the internet, and execute terminal commands. It's built to be LLM-agnostic, working seamlessly with models from OpenAI, Anthropic, Mistral, Llama, and more.

How to use: Developers integrate E2B into their applications using client SDKs. For JavaScript/TypeScript, use @e2b/code-interpreter (via npm install @e2b/code-interpreter). For Python, use e2b-code-interpreter (via pip install e2b-code-interpreter).

Example (Python):

from e2b_code_interpreter import Sandbox

with Sandbox() as sandbox:
    sandbox.run_code("x = 1")
    execution = sandbox.run_code("x+=1; x")
    print(execution.text)

Key Features:

  • Fast Startup: Sandboxes launch in less than 200ms with no cold starts.
  • Language Agnostic: Supports any AI-generated code (Python, JavaScript, Ruby, C++, etc.) that can run on a Linux environment.
  • Secure: Powered by Firecracker microVMs for running untrusted code safely.
  • Long Sessions: Sandboxes can run for up to 24 hours.
  • Customization: Install any package or system library, and create custom sandbox templates.
  • Self-hosting: Option to deploy E2B within your own AWS or GCP VPC.

E2B is trusted by leading companies like Perplexity, Hugging Face, Groq, and Lindy for various use cases including data analysis, code testing, deep research, and workflow automation.

# mcpServer Config

No mcpServer Config instructions provided.
Transport:
streamable
Language:
Python
Updated: 11/2/2025