AgentsKit

What it does

Building AI agents in JavaScript means gluing 5 libraries that fight each other. Vercel AI SDK has no runtime. LangChain.js is 200MB of leaky abstractions. MCP is just a protocol. AgentsKit is the missing kit. 12 small packages, 6 formal contracts, nothing locks you in. Swap OpenAI for Claude in one line. Same useChat hook in React AND terminal. 10KB zero-dep core, bundle gates in CI. `npx agentskit init` → working agent in 30 seconds. MIT, solo-built, open roadmap.

Build agents without gluing many libraries together. A composable TypeScript foundation for runtime, tools, memory, RAG, and chat interfaces.

Runtime, tools, memory, RAG, adapters, and headless UI bindings in one foundation. Swap OpenAI for Claude , React for terminal, in-memory for vector DB — without a rewrite. Built for JavaScript and TypeScript teams building agents they can evolve without a rewrite. OpenAI, Anthropic, Gemini, Kimi, local models, or your own adapter use one contract. Compose the agent here. Use AgentsKit Chat when you need its product interface across every surface. Explore Chat → 50 built-in integrations and 184 providers ( 6,297 models) behind a single contract — Slack, Notion, Stripe, OpenAI, Anthropic, and the long tail. Six contracts on one tiny core. Every layer is optional and swappable — click any to…from agentskit.io

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  Hi HN! I’m Tony, co-founder of Inngest. I wanted to share AgentKit, our Typescript multi-agent library we’ve been cooking and testing with some early users in prod for months. Although OpenAI’s Agents SDK has been launched since, we think an Agent framework should offer more deterministic and flexible routing, work with multiple model providers, embrace MCP (for rich tooling), and support the unstoppable and growing community of TypeScript AI developers by enabling a smooth transition to production use cases. This is why we are building AgentKit, and we’re really excited about it for a few…

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