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The complete toolkit for building AI agents in JavaScript. Lightweight core, React & Terminal UIs, autonomous runtime, tools, skills, memory, RAG and observability. Plug-and-play from chat UI to full agents.

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# AgentsKit.js

**The agent toolkit JavaScript actually deserves.**

A 10 KB core budget. Twenty-five focused packages. Zero lock-in. Six formal contracts that make every adapter, tool, skill, memory, retriever, and runtime substitutable.

[![npm](https://img.shields.io/npm/v/@agentskit/react?label=npm)](https://www.npmjs.com/package/@agentskit/react)
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[![human bridge](https://img.shields.io/badge/human_docs-100%25-2ea44f)](https://raw.githubusercontent.com/AgentsKit-io/agentskit/main/doc-bridge.config.json)

**Tags:** `agentskit` · `ai-agents` · `typescript` · `javascript` · `llm` · `agent-runtime` · `tools` · `rag`

[**Documentation**](https://www.agentskit.io) · [**Discord**](https://discord.gg/zx6z2p4jVb) · [**Roadmap**](https://github.com/orgs/AgentsKit-io/projects/1) · [**Manifesto**](./MANIFESTO.md) · [**Origin**](./ORIGIN.md) · [**Architecture**](./docs/architecture/adrs)

<br />

</div>

---

*You started building an AI agent last week. You're three libraries deep, two of them fight each other, and nothing you wrote is reusable. This is for you.*

> **⭐ If this saves you from gluing five libraries together, [star the repo](https://github.com/AgentsKit-io/agentskit).** AgentsKit is solo-built — a star is the cheapest signal that it's worth continuing, and it's what puts it in front of the next person.

## Verified proof

The current [evidence ledger](./ecosystem-claims.json), generated from repository sources by [`scripts/compute-stats.mjs`](./scripts/compute-stats.mjs), publishes the canonical package, framework, adapter, integration, provider, model, skill, memory, and recipe counts used by every AgentsKit surface.

- The core has zero runtime dependencies and a CI-enforced **10 KB gzipped budget**.
- Every public package has an explicit stability tier, test floor, README, human guide, and agent handoff.
- Numeric claims fail CI when their repository derivation, committed snapshot, or public evidence drifts.

Inspect the machine-readable [claims ledger](./ecosystem-claims.json), [ecosystem contract](./ecosystem.json), and [Doc Bridge index](./llms.txt) instead of trusting a screenshot or an unversioned marketing count.

## Why this exists

**We don't need another framework. We need a kit.**

Building a real AI agent in JavaScript today means cobbling together five libraries that don't fit. Vercel AI SDK is a beautiful chat SDK with no runtime. LangChain.js drags in 200MB and leaks abstractions at every layer. MCP solves tool interop and nothing else. assistant-ui has 53 components and no opinion about how to compose them.

AgentsKit is the missing kit: small, contracted, composable. Start with one package, grow into a full stack, and stay in plain JavaScript the entire time.

> [Origin story](./ORIGIN.md) for the long version. [Manifesto](./MANIFESTO.md) for the principles.

---

## The AgentsKit ecosystem

AgentsKit is not only a package. It is the open-source foundation of a full agent ecosystem:
build from composable parts, start faster with ready agents, follow production patterns, and run the result with enterprise controls.

| Layer | Go to | What it unlocks |
|---|---|---|
| **AgentsKit** | **This repo** | The agent building blocks: adapters, runtime, tools, memory, RAG, UI, evals, observability, and MCP |
| **Registry** | [registry.agentskit.io →](https://registry.agentskit.io) | Ready-to-use agents, tools, and templates you can install instead of starting from blank |
| **Playbook** | [playbook.agentskit.io →](https://playbook.agentskit.io) | Field-tested patterns for designing, evaluating, securing, and operating agents |
| **AKOS** | [akos.agentskit.io →](https://akos.agentskit.io) | The enterprise operating system for deploying, governing, observing, and scaling agents |

The path is simple: compose with **AgentsKit**, learn the patterns in the **Playbook**, reuse agents from the **Registry**, and graduate to **AKOS** when you need enterprise operations.

```mermaid
flowchart LR
  Playbook["Playbook<br/>best practices"]
  Registry["Registry<br/>ready agents"]
  AK["AgentsKit<br/>composable JS packages"]
  AKOS["AKOS<br/>enterprise agent OS"]

Playbook --> AK
  Registry --> AK
  AK --> Registry
  AK --> AKOS
  Playbook --> AKOS
```

Humans get the docs site. Agents get [`llms.txt`](./llms.txt) and [`doc-bridge.config.json`](./doc-bridge.config.json): 24/24 package handoffs, 24/24 human-doc bridges.

---

## Quick start — your first agent, no key required

```bash
npm install @agentskit/core @agentskit/runtime tsx
```

Create `agent.ts`:

```ts
import type { AdapterFactory } from '@agentskit/core'
import { createRuntime } from '@agentskit/runtime'

const localAdapter: AdapterFactory = {
  createSource(request) {
    const task = request.messages.at(-1)?.content ?? 'your task'

return {
      async *stream() {
        yield {
          type: 'text' as const,
          content: `Agent ready. I received: ${task}`,
        }
        yield { type: 'done' as const }
      },
      abort() {},
    }
  },
}

async function main() {
  const runtime = createRuntime({ adapter: localAdapter })
  const result = await runtime.run('Plan my first production agent')
  console.log(result.content)
}

void main()
```

```bash
npx tsx agent.ts
```

It prints `Agent ready. I received: Plan my first production agent`. No account, API key, or network request is required. The [executable fixture](./apps/docs-next/fixtures/first-agent/agent.ts) is byte-synchronized with this README and runs in CI; connect any supported provider later through the same adapter contract.

---

## Before and after

**Before** — the typical "JS agent" stack:

```ts
// Pick your favorite: LangChain, raw fetch, Vercel AI SDK + custom runtime,
// MCP client + custom UI, manual ReAct loop, hand-rolled streaming...
// Then wire memory. Then wire tools. Then wire delegation. Then debug.
```

**After** — AgentsKit:

```ts
import { createRuntime } from '@agentskit/runtime'
import { openai } from '@agentskit/adapters'
import { webSearch, filesystem } from '@agentskit/tools'

const runtime = createRuntime({
  adapter: openai({ apiKey: KEY, model: 'gpt-4o' }),
  tools: [webSearch(), ...filesystem({ basePath: './workspace' })],
})

const result = await runtime.run('Research the top 3 AI frameworks and save a summary')
```

That's an autonomous agent. With a tool registry. With memory. With observability hooks. Two imports, six lines.

Swap providers in **one** line — every other line stays the same:

```ts
import { anthropic, openai, gemini, ollama, deepseek, grok } from '@agentskit/adapters'

useChat({ adapter: anthropic({ apiKey, model: 'claude-sonnet-4-6' }) })
useChat({ adapter: openai({ apiKey, model: 'gpt-4o' }) })
useChat({ adapter: ollama({ model: 'llama3.1' }) })          // local, no key
```

---

## How AgentsKit compares

| | AgentsKit | Vercel AI SDK | LangChain.js | assistant-ui |
|---|---|---|---|---|
| **Core size** | 10KB gzip, zero deps | ~30KB | hundreds of MB transitively | n/a (UI only) |
| **Agent runtime** | First-class (ReAct, tools, skills, delegation, memory, RAG) | None | Yes, but heavy | None |
| **Provider swap** | One line | Route-handler-shaped | Per-class wiring | BYO backend |
| **UI surfaces** | React + Ink + headless | React | None | React |
| **Formal contracts** | Six versioned ADRs | Implicit | Implicit | Implicit |
| **Edge-ready** | Yes (10KB core, no Node-only deps) | Mostly | No | n/a |

### When you should NOT use AgentsKit

We are honest about this:

- **You only need a single OpenAI streaming call.** Use the `openai` SDK directly — AgentsKit is overkill.
- **You're shipping a chat SDK to consumers, not an agent.** Vercel AI SDK is purpose-built for that and excellent.
- **You need Python.** AgentsKit is JavaScript-first by design. Use a Python framework.
- **You require enterprise-grade observability today.** AgentsKit's observability layer is good but young; LangSmith/Arize/Helicone are more mature integrations right now.
- **You need every package frozen today.** `@agentskit/core` is v1.0.0, but the rest of the ecosystem is still graduating package-by-package.

> Full, honest head-to-head with **LangChain.js, Vercel AI SDK, Mastra, LlamaIndex.js, and assistant-ui** → [**AgentsKit vs alternatives**](https://www.agentskit.io/docs/compare).

---

## The packages

Pick what you need. Every package works alone. Combinations work without glue code.

| Package | What it does | Stability |
|---|---|---|
| [`@agentskit/core`](packages/core) | Types, contracts, primitives | stable |
| [`@agentskit/adapters`](packages/adapters) | Provider adapters (OpenAI, Anthropic, Gemini, Ollama, DeepSeek, Grok, …) | beta |
| [`@agentskit/runtime`](packages/runtime) | Autonomous agent runtime (ReAct loop, delegation) | beta |
| [`@agentskit/tools`](packages/tools) | Web search, filesystem, shell, integrations, MCP bridge | beta |
| [`@agentskit/memory`](packages/memory) | Chat + vector + graph + encrypted memory | beta |
| [`@agentskit/rag`](packages/rag) | Plug-and-play retrieval and reranking | alpha |
| [`@agentskit/skills`](packages/skills) | Pre-built behavioral prompts and personas | beta |
| [`@agentskit/observability`](packages/observability) | Console, LangSmith, OpenTelemetry, audit log | beta |
| [`@agentskit/eval`](packages/eval) | Agent evaluation, replay, snapshots | alpha |
| [`@agentskit/sandbox`](packages/sandbox) | Secure code execution | alpha |
| [`@agentskit/react`](packages/react) | React hooks + headless UI | beta |
| [`@agentskit/ink`](packages/ink) | Terminal UI (Ink) components | beta |
| [`@agentskit/vue`](packages/vue) | Vue binding for the shared chat contract | alpha |
| [`@agentskit/svelte`](packages/svelte) | Svelte binding for the shared chat contract | alpha |
| [`@agentskit/solid`](packages/solid) | Solid binding for the shared chat contract | alpha |
| [`@agentskit/react-native`](packages/react-native) | React Native / Expo binding | alpha |
| [`@agentskit/angular`](packages/angular) | Angular binding with Signals + RxJS | alpha |
| [`@agentskit/cli`](packages/cli) | CLI: chat, init, run, ai, dev, doctor | beta |
| [`@agentskit/templates`](packages/templates) | Authoring toolkit for scaffolding skills, tools, adapters | alpha |
| [`@agentskit/mcp`](packages/mcp) | Expose AgentsKit tools as an MCP server (Claude Desktop, Cursor, Windsurf) | beta |
| [`@agentskit/integrations`](packages/integrations) | Plug-and-play service integrations (one descriptor → tools, connectors, triggers, auth) | beta |
| [`@agentskit/tools/validation`](packages/validation) | Runtime JSON-Schema validation of tool-call arguments (Ajv) | beta |
| [`@agentskit/eval/braintrust`](packages/eval-braintrust) | Braintrust scoring pipeline + CI regression alerts | beta |
| [`@agentskit/observability/langfuse`](packages/observability-langfuse) | Langfuse tracing adapter (plan, tool, model, HITL spans) | beta |

### What can you build?

One kit, many shapes. Reach for only what the goal needs:

| Goal | Reach for |
|---|---|
| Streaming chat UI in React | `react` + `adapters` |
| The same chat in Vue / Svelte / Solid / Angular / React Native | the matching binding + `adapters` |
| Terminal or CLI agent | `ink` + `cli` |
| Headless autonomous agent (no UI) | `runtime` + `tools` + `skills` |
| Swap LLM providers with one line | `adapters` (OpenAI, Anthropic, Gemini, Ollama, DeepSeek, Grok, …) |
| Long-term, vector, or encrypted memory | `memory` |
| RAG over your own docs | `rag` + `memory` |
| Multi-agent delegation | `runtime` + `skills` |
| Use your tools from Claude Desktop / Cursor | `mcp` |
| Connect Slack, Teams, email, … | `integrations` |
| Run untrusted or model-generated code | `sandbox` |
| Trace, evaluate, and observe | `observability` + `eval` |

The whole catalog is one `npx @agentskit/cli init` away.

---

## Multi-agent delegation

```ts
import { planner, researcher, coder } from '@agentskit/skills'

const result = await runtime.run('Build a landing page about quantum computing', {
  skill: planner,
  delegates: {
    researcher: { skill: researcher, tools: [webSearch()], maxSteps: 3 },
    coder:      { skill: coder, tools: [...filesystem({ basePath: './src' })], maxSteps: 8 },
  },
})
```

The planner decomposes the task. The researcher and coder execute their parts. Delegation happens through a tool the model already knows how to call — no special syntax to learn.

---

## Terminal chat (Ink)

```bash
npm install -g @agentskit/cli
agentskit chat --provider ollama --model llama3.1
agentskit chat --provider openai --tools web_search,shell --skill researcher
```

The same `useChat` mental model. Real keyboard input. Real streaming. Real tools.

---

## For AI agents reading this

The full public API fits in **under 2,000 tokens**. Paste the [agent-friendly reference](https://www.agentskit.io/docs/get-started/getting-started/for-ai-agents) into your LLM context and start generating real AgentsKit code immediately. We treat agents as first-class consumers of our docs.

---

## Package dependency graph

```mermaid
graph TD
    core["@agentskit/core\n(zero deps · 5 KB)"]

adapters["@agentskit/adapters\nOpenAI · Anthropic · Gemini\nOllama · DeepSeek · Grok"]
    react["@agentskit/react\nReact hooks + headless UI"]
    ink["@agentskit/ink\nTerminal UI (Ink)"]
    runtime["@agentskit/runtime\nReAct loop · delegation"]
    tools["@agentskit/tools\nweb search · filesystem · shell"]
    skills["@agentskit/skills\nresearcher · coder · planner"]
    memory["@agentskit/memory\nSQLite · Redis · file · vector"]
    rag["@agentskit/rag\nplug-and-play RAG"]
    observability["@agentskit/observability\nLangSmith · OpenTelemetry"]
    sandbox["@agentskit/sandbox\nE2B · WebContainer"]
    eval["@agentskit/eval\nbenchmarking · metrics"]
    templates["@agentskit/templates\nskill/tool authoring"]
    cli["@agentskit/cli\nchat · init · run"]

core --> adapters
    core --> react
    core --> ink
    core --> runtime
    core --> tools
    core --> skills
    core --> memory
    core --> rag
    core --> observability
    core --> sandbox
    core --> eval
    core --> templates

cli --> core
    cli --> adapters
    cli --> ink
    cli --> runtime
    cli --> skills
    cli --> tools
    cli --> memory

classDef foundation fill:#1e293b,stroke:#6366f1,color:#f8fafc,font-weight:bold
    classDef ui        fill:#0f172a,stroke:#22d3ee,color:#f8fafc
    classDef agent     fill:#0f172a,stroke:#a78bfa,color:#f8fafc
    classDef data      fill:#0f172a,stroke:#34d399,color:#f8fafc
    classDef ops       fill:#0f172a,stroke:#fb923c,color:#f8fafc
    classDef entry     fill:#0f172a,stroke:#f472b6,color:#f8fafc

class core foundation
    class react,ink ui
    class adapters,runtime,tools,skills agent
    class memory,rag,templates data
    class observability,sandbox,eval ops
    class cli entry
```

**Legend:** purple = provider/execution layer · cyan = UI layer · green = data layer · orange = ops layer · pink = CLI entry point

---

## Architecture and contracts

Six ADRs define the substrate:

| ADR | Contract |
|---|---|
| [0001](./docs/architecture/adrs/0001-adapter-contract.md) | Adapter — LLM provider seam |
| [0002](./docs/architecture/adrs/0002-tool-contract.md) | Tool — function the model calls |
| [0003](./docs/architecture/adrs/0003-memory-contract.md) | Memory — chat history + vector store + embed |
| [0004](./docs/architecture/adrs/0004-retriever-contract.md) | Retriever — context fetching |
| [0005](./docs/architecture/adrs/0005-skill-contract.md) | Skill — declarative persona |
| [0006](./docs/architecture/adrs/0006-runtime-contract.md) | Runtime — the loop that composes them all |

Read these once and you can predict how every package behaves.

---

## Maturity and compatibility

`@agentskit/core` is at **v1.0.0** — API frozen at the minor level, deprecations carry a cycle, contracts pinned to ADRs. The rest of the ecosystem ships on independent beta/alpha tracks with explicit [stability tiers](./docs/STABILITY.md).

AgentsKit targets **Node.js 20+** and modern JavaScript runtimes. Packages ship strict **TypeScript** declarations and dual ESM/CJS output unless their platform binding documents a narrower target. Browser, edge, React Native, Angular, Vue, Svelte, Solid, React, and terminal compatibility is package-specific and declared in each package README and guide.

The current verified release surface is:

- **Stable:** `@agentskit/core`, with six formal contracts pinned to ADRs 0001–0006.
- **Beta/alpha:** every other package graduates independently under the published stability policy.
- **Evidence:** current package, adapter, integration, provider, skill, memory, and recipe counts come from the [generated claims ledger](./ecosystem-claims.json), not this prose.

See the [stability policy](./docs/STABILITY.md), [core v1 release notes](./docs/RELEASE-CORE-V1.md), and [public roadmap](https://github.com/orgs/AgentsKit-io/projects/1) before depending on a pre-1.0 package contract.

---

## Contributing

AgentsKit is built in the open and ships because contributors show up. Every package, every doc, every example is fair game.

- **[How to contribute →](https://www.agentskit.io/docs/contribute)** — start here
- **[Public roadmap board](https://github.com/orgs/AgentsKit-io/projects/1)** — what's planned, in flight, and shipped
- **[Good-first-issues](https://github.com/AgentsKit-io/agentskit/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22)** — curated, tractable tickets
- **[Help-wanted](https://github.com/AgentsKit-io/agentskit/issues?q=is%3Aissue+is%3Aopen+label%3A%22help+wanted%22)** — larger scoped work
- **[Discussions](https://github.com/AgentsKit-io/agentskit/discussions)** — ask, propose, share
- **[RFC template](https://github.com/AgentsKit-io/agentskit/issues/new?template=rfc.yml)** — open before touching a contract
- **[`CONTRIBUTING.md`](./CONTRIBUTING.md)** — dev setup + PR checklist
- **[README Standard v1](./docs/README-STANDARD-V1.md)** — executable quality profiles for repositories, apps, and packages

### Contributors

Thanks to everyone who's shipped a line of code, docs, or feedback.

---

## License

MIT — see [`LICENSE`](./LICENSE).

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