It is a TypeScript library designed to create and orchestrate AI Agents, enabling developers to build, test, and deploy reliable AI applications at scale.
It is a TypeScript library designed to create and orchestrate AI Agents, enabling developers to build, test, and deploy reliable AI applications at scale. AgentKit provides a framework for constructing AI Agents, ranging from single model inference calls to complex multi-agent systems that utilize tools. The library is built with orchestration at its core, allowing developers to compose simple single-agent systems or entire networks of agents that collaborate on tasks.
AgentKit offers simple and composable primitives, making it easy to build various types of agents, from basic Support Agents to semi-autonomous Coding Agents. It supports integration with popular AI models, including OpenAI, Anthropic, Gemini, and any OpenAI API-compatible models. Additionally, it provides a powerful tools-building API with support for Claude MCP, enabling developers to create custom tools for their agents.
The library integrates seamlessly with other AI libraries and products, such as E2B, Browserbase, and Neon, enhancing its functionality and flexibility. When combined with the Inngest Dev Server, AgentKit provides local live traces and input/output logs, aiding in debugging and monitoring agent behavior.
AgentKit organizes agents into networks, which include a router to determine which agent should handle a specific task. The system’s memory is recorded as Network State, which can be utilized by the router, agents, or tools to collaborate effectively. This orchestration-aware system allows for runtime customization, enabling dynamic and powerful AI workflows.
For beginners, AgentKit offers a guided tour to help users build their first application. Experienced developers can explore the “Getting Started” section or the “How AgentKit Works” section to understand the library’s architecture. The SDK reference provides detailed information about AgentKit’s primitives, while examples showcase practical use cases. AgentKit is ideal for developers looking to create scalable, reliable, and customizable AI agent systems.
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