A lightweight AI Agent Skills secure engine built in Rust, featuring a built-in native system-level sandbox, zero dependencies, and fully local execution. Provides three-layer security defense (install-time scan, pre-execution authorization, runtime sandbox) with 100% security test score, 40ms hot start, and ~10MB memory footprint.
A multi-language backend framework that unifies APIs, background jobs, queues, workflows, streams, and AI agents with a single core primitive (Step), featuring built-in observability and state management. Supports TypeScript, Python, and JavaScript under Apache-2.0 license.
A small, modular agent framework for building LLM-powered applications in Python with streaming and optional Rust bindings.
A secure, durable runtime for AI agents that executes untrusted code in isolated WebAssembly sandboxes with fine-grained resource control including CPU, memory, timeout limits and permission management.
A minimal, secure Python interpreter written in Rust for AI agents, featuring microsecond startup latency and state snapshotting.
A high-throughput, low-latency inference framework designed for serving generative AI and reasoning models in multi-node distributed environments.
A lightweight coding agent that runs locally in your terminal to assist with development tasks.
Wren Engine is the semantic engine for MCP clients and AI agents, enabling accurate data access, semantic understanding, and governance for AI systems.
A curated list of SDKs, frameworks, libraries, and tools for creating, monitoring, debugging and deploying autonomous AI agents, maintained by the E2B team.
A developer tool that adds autocomplete and AI capabilities to your existing terminal on macOS & Linux platforms, built with Rust.
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