Curates 500+ open-source AI agent use cases, indexed two ways: by industry vertical (healthcare, finance, legal, retail, and more) and by framework (CrewAI, AutoGen, LangGraph, LlamaIndex, Agno). Each entry links a runnable repo.
Lets teams build, deploy, and manage AI agents from chat, visual workflows, code, knowledge bases, tables, and more than a thousand integrations.
Runs penetration tests autonomously: a multi-agent system (researcher, developer, executor) plans attacks, writes and runs exploit code, and chains 20+ tools like nmap, metasploit and sqlmap in isolated Docker containers — for authorized testing only.
Turns camera, audio, LIDAR and web inputs into robot motion, navigation and speech by routing them through pluggable LLMs and VLMs. Hardware-agnostic Go runtime configured via JSON5, with ROS2/Zenoh middleware for real robots and simulators.
Builds event-driven multi-agent AI systems that use a Solace event mesh for agent-to-agent messaging, task delegation, and artifact exchange. Emphasizes asynchronous orchestration, plugin-based extensibility, and integrations with LLMs and external systems.
Connects to Gmail, Calendar, and meeting notes to build a local, Obsidian-compatible Markdown graph it acts on — drafting emails, briefs, and decks. Memory accumulates instead of resetting each session; runs on local or hosted models, extensible via MCP.
MCP-native agent framework built around the Model Context Protocol from the start, with end-to-end tested Sampling and Elicitation. Define agents and multi-step workflows in Python, run terminal-first, and swap Anthropic, Google or local models.
Drives your computer from natural language: a vision-language model reads raw screenshots and works the mouse and keyboard like a person, controlling any GUI app without APIs or accessibility hooks. Local or remote operator modes on Windows and macOS.
Runs stateful AI agents as Cloudflare Durable Objects — each keeps its own storage and lifecycle, hibernating when idle and waking on demand. Adds WebSocket state sync, type-safe RPC, resumable LLM streaming, MCP roles, and durable workflows.
Hands-on studio to design, test and deploy declaratively configured multi-agent systems built on the Neuro SAN framework. Ships ready examples, an Agent Network Designer UI (nsflow), CLI tooling, and integrations with major LLMs and external tools for rapid prototyping.
Spins up sandboxed VMs and containers (macOS, Linux, Windows, Android) that an AI agent can fully control through one unified SDK, cloud or local, plus a benchmark suite and background drivers that automate native apps without grabbing the cursor.