e2b-dev/e2b

Open-source, secure environment with real-world tools for enterprise-grade agents.

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Summary Information

Updated 3 minutes ago
Added to GitGenius on September 4th, 2026
Created on March 4th, 2023
Open Issues & Pull Requests: 49 (+0)
GitHub issues: Enabled
Number of forks: 1,024
Total Stargazers: 13,697 (+1)
Total Subscribers: 84 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 10.1 hours
Mean response time: 44.1 days
90th percentile: 179.5 days
Tracked items: 267

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 100% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Work labelled "Build System" is answered fastest, typically in about 6 hours, while "cli" waits about 10 months. Only 9% of issues opened in the past year have been closed. Three people close 80% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 24
New in 7 days: 4
Closed in 7 days: 3
Avg open age: 255 days
Stale 30+ days: 0
Stale 90+ days: 0

Recent activity

Opened in 7 days: 4
Closed in 7 days: 3
Comments in 7 days: 3
Events in 7 days: 5

Top labels

  • bug (138)
  • feature (60)
  • sdk (34)
  • cli (13)
  • Improvement (12)
  • Build System (10)
  • Infrastructure (9)
  • question (7)

Detailed Description

E2B is an open-source infrastructure platform that runs AI-generated code in secure isolated sandboxes in the cloud.

The core problem E2B addresses is the need to safely execute code generated by large language models without exposing the host system to risk. It provides sandboxed cloud environments where AI agents can run arbitrary code, system commands, and interactive applications. The platform offers SDKs for both JavaScript and Python to start and control these sandboxes, along with specialized modules for code interpretation and desktop interaction including mouse, keyboard, and screenshot capabilities.

Teams building AI agents, copilots, or applications that need to execute untrusted code should consider E2B. It suits projects where an LLM generates code that must run reliably in isolation, such as code execution tools, data analysis agents, or autonomous software development systems. The platform supports self-hosting on AWS and Google Cloud using Terraform, making it viable for organizations with strict infrastructure requirements. The documentation and cookbook examples demonstrate integration patterns with various LLMs and AI frameworks.

The project maintains active development across multiple language SDKs and specialized packages. The codebase shows ongoing expansion of capabilities, with distinct modules for code interpretation and desktop automation indicating iterative feature development. The infrastructure components are published separately to support self-hosting scenarios, suggesting a commitment to operational flexibility. Documentation and example repositories are actively maintained alongside the core platform.