{"id":"e2b-api","name":"E2B Code Interpreter API","homepage":"https://e2b.dev","repo_url":"https://github.com/e2b-dev/e2b","category":"developer-tools","subcategories":["code-execution","sandboxing","ai-infrastructure"],"tags":["code-interpreter","sandbox","ai-agents","python","javascript","secure-execution","e2b"],"what_it_does":"E2B provides secure, isolated cloud sandboxes for running AI-generated code. Each sandbox is a full Linux VM that spins up in ~150ms, letting agents execute Python, JavaScript, bash, and other code safely without risk to host systems. Purpose-built for AI agents — supports file uploads, persistent processes, long-running sessions (up to 24 hours), and real-time stdout/stderr streaming.","use_cases":["Executing AI-generated code safely in isolated environments before deploying","Running data analysis pipelines where agents write and test Python code iteratively","Building coding assistants that need to verify their generated code actually works","Hosting interactive Jupyter-like environments for AI-driven data science","Running arbitrary user-submitted code in multi-tenant SaaS platforms","Testing and debugging AI-generated scripts without infrastructure setup","Long-running background computation tasks launched by AI agents"],"not_for":["Persistent compute requiring GPU (use Modal or Replicate for GPU workloads)","Production server hosting — sandboxes are ephemeral compute environments","Very long-running jobs exceeding 24-hour session limits","Teams that need on-premise code execution for compliance reasons"],"best_when":"You need an AI agent to write and run code in a loop (plan-execute-observe), especially for data analysis, coding assistants, or any workflow where validating AI-generated code before trusting it is critical. E2B's fast spin-up and Python SDK are ideal for tight agent loops.","avoid_when":"You need GPU compute, persistent state across many sessions, or heavy ML model inference inside the sandbox. For pure model inference, use Replicate or Together AI instead.","alternatives":[{"id":"modal-api","reason":"Better for GPU workloads and persistent ML inference; E2B is better for short-lived code interpreter sessions"},{"id":"replicate-api","reason":"Better for running pre-built ML models; E2B is better for arbitrary agent-generated code"},{"id":"github-actions","reason":"CI/CD code execution but not designed for low-latency agent loops"}],"af_score":87.4,"security_score":null,"reliability_score":null,"package_type":"mcp_server","discovery_source":["github"],"priority":"low","status":"evaluated","version_evaluated":"current","last_evaluated":"2026-03-01T09:50:05.518260+00:00","performance":{"latency_p50_ms":150,"latency_p99_ms":500,"uptime_sla_percent":99.9,"rate_limits":"Free tier: 1 concurrent sandbox. Paid tiers: up to 100 concurrent sandboxes. No explicit rate limit on API calls.","data_source":"llm_estimated","measured_on":null}}