Three Ws

three.ws

https://github.com/user-attachments/assets/d52515d1-cb04-4dd6-98bd-fef233312dc4

Give your AI a body. three.ws is an open-source, browser-native 3D AI agent platform. Drop a GLB file, add an LLM brain, register on-chain, and embed anywhere — no plugins, no server uploads, no installs required.

What is three.ws?
Vision
Roadmap
Key Features
Screenshots
Architecture
Tech Stack
Getting Started
Examples
Tutorials
Project Structure
The Agent System
- Event Bus (Agent Protocol)
- LLM Runtime
- Empathy Layer
- Skills
- Memory
Web Component & Embedding
Widget System
API Reference
Authentication & OAuth 2.1
MCP Server
On-Chain Identity (ERC-8004)
Database Schema
Build & Deployment
Environment Variables
Testing
Contributing
License

What is three.ws?

three.ws is a full-stack system for creating, deploying, and embedding 3D AI agents. It combines a WebGL model viewer, an LLM-driven agent runtime, on-chain identity contracts, and a distributable web component into one cohesive platform.

At its core, it does four things:

Render — loads and validates glTF 2.0 / GLB models in WebGL 2.0 with zero server-side processing. Drag a file onto the browser and it renders instantly with full Draco, KTX2, and Meshopt decompression.
Embody — wraps any avatar with an LLM brain. The agent listens to the user, thinks with Claude, executes tools (animations, gestures, memory operations, skill calls), and expresses emotion through morph-target blending on the 3D model in real time.
Register — optionally mints the agent as an ERC-8004 token on any EVM chain, giving it a stable on-chain identity, a wallet address, signed action history, and a reputation score that cannot be forged.
Embed — distributes the agent as an <agent-3d> web component that anyone can drop into a page, or as one of five purpose-built widget types (turntable, animation gallery, talking agent, passport card, hotspot tour) with Open Graph and oEmbed support built in.

The backend is a set of Vercel serverless functions backed by Neon Postgres for metadata, Cloudflare R2 for model storage, and Upstash Redis for rate limiting. It exposes a full OAuth 2.1 authorization server and an MCP (Model Context Protocol) endpoint so external AI systems can drive avatars programmatically.

three.ws is production-ready and serves three.ws live. The entire stack — viewer, agent runtime, contracts, backend, and web component — is open source under Apache 2.0.

Vision

One day, creating your agent should be as simple as taking a selfie.

Point your camera at yourself — or anyone — and watch a fully realized 3D avatar emerge: your face, your voice, your personality, alive in the browser. That avatar becomes an agent with memory and skills, registered onchain as an ERC-8004 token, permanent and verifiable by anyone forever. No 3D software. No wallet setup. No uploads. Just a photo and a name.

This is the direction three.ws is heading: photo → avatar → agent → onchain identity, in a single flow. The infrastructure is already here — the viewer, the runtime, the contracts, the embedding layer. What comes next is closing the gap between a picture of a person and a living, ownable, embeddable piece of them that exists on the internet permanently.

Roadmap

three.ws ships in four phases. Each phase closes a specific gap between the current platform and the end-state vision: anyone can mint a 3D agent of themselves, own it onchain, and embed it anywhere on the internet.

Phase	Theme	Status
0	Platform foundations (viewer, runtime, ERC-8004, embed layer)	✅ Shipped
1	Selfie → Avatar engine (3-photo capture, hosted inference)	🟡 In progress
2	Agent personalization + voice cloning	⏳ Next
3	Onchain economy (agent tokens, reputation markets, royalties)	⏳ Next
4	Open inference network (decentralized GPU layer)	🔮 Future

Phase 0 — Foundations (Shipped)

The full stack is live at three.ws: WebGL viewer, LLM agent runtime, ERC-8004 identity contracts, OAuth 2.1 server, MCP endpoint, and the <agent-3d> web component. Anyone can register an agent today — but the avatar still has to come from a 3D artist or a third-party tool.

What works: model upload, agent runtime, onchain registration, embedding, signed action history, reputation scores. What doesn't: there is no automated path from a real human face to a usable 3D avatar.

Phase 1 — Selfie → Avatar Engine

Goal: any user takes 3 selfies (left, center, right) and receives a rigged, animatable 3D avatar in under 60 seconds.

Deliverables

Mobile-first capture UX with realtime quality gates (lighting, framing, blur)
Multi-view face reconstruction pipeline (FLAME / 3DMM fitting on top of a base body mesh)
Hosted inference workers (GPU-backed) for sub-minute generation
Output written directly to R2 + minted as a draft ERC-8004 token

Compute requirements

A100/H100-class GPUs for inference, sized to ~10k avatars/day at launch
Training budget for fine-tuning a stylized face-fitter on a curated dataset
CDN egress scaling for high-res GLB delivery

Verification: 1,000 test users complete capture and mint an onchain agent of themselves end-to-end with ≥4/5 likeness score.

Phase 2 — Agent Personalization

Goal: the avatar isn't just you — the agent acts like you.

Deliverables

Voice cloning (3–10 seconds of speech → ElevenLabs custom voice bound to the agent)
Persona extraction from a short onboarding interview (tone, vocabulary, interests)
Memory seeding from connected accounts (X, GitHub, Farcaster) with explicit user consent
Per-agent fine-tuned system prompt stored in the manifest, signed and pinned to IPFS

Verification: users return to converse with their own agent; ≥30% week-2 retention on minted agents.

Phase 3 — Onchain Economy

Goal: agents are real economic objects on EVM and Solana, not just collectibles.

Deliverables

Agent tokens — ERC-8004 mints with bonding-curve pricing or fair launch options
Reputation markets — stake on agents, earn from their action history (extends ReputationRegistry.sol)
Skill royalties — skill authors earn per-call fees through EIP-7710 delegated permissions
Agent-to-agent payments — agents transact autonomously via their delegated signer wallets
Subscriptions & DCA — recurring onchain payments to creators (cron infra already in place)

Funding requirements

Smart contract audits (multi-firm) for the reputation, royalty, and delegation contracts
Liquidity for agent token launches
Indexer infrastructure across Base, Solana, and additional EVM chains

Verification: ≥1,000 agents minted with active onchain reputation; ≥$X in cumulative skill royalties paid out.

Phase 4 — Open Inference Network

Goal: decouple agent inference from any single provider. Anyone can run a node; agents pay nodes onchain for compute.

Deliverables

Open protocol for agent inference (model weights, GPU runtime, signed responses)
Node operator client (Docker + GPU drivers) with onchain registration
Onchain settlement for inference jobs — pay-per-token with cryptographic receipts
Federation with existing decentralized compute networks where appropriate

Compute requirements

Bootstrap GPU credits for early node operators
Cryptoeconomic security model (slashing, validator set) — research + audit budget

Verification: ≥50% of production agent traffic served by independent node operators; latency parity with centralized inference.

What we need

Resource	Used for	Phase
Inference GPUs	Avatar generation, agent conversations	1, 2
Training compute	Fine-tuned face-fitter, voice models	1, 2
Smart contract audits	Reputation, royalty, delegation contracts	3
Token launch liquidity	Agent token markets	3
Indexer infrastructure	Multi-chain crawl + reputation aggregation	3
Node operator credits	Bootstrap the open inference network	4
Engineering headcount	Capture pipeline, contracts, indexer, ops	1–4

Phases 1 and 2 unblock the consumer story — anyone gets an agent of themselves. Phases 3 and 4 unblock the onchain story — those agents are real economic actors that don't depend on any one company to keep running. Both are required for the vision; neither is funded yet.

If you want to support the project — compute credits, grants, partnerships, or contributions — open an issue or reach out via three.ws.

Key Features

3D Viewer

WebGL 2.0 rendering via three.js r176
glTF 2.0 and GLB with Draco geometry compression, KTX2 texture compression, and Meshopt mesh optimization
Khronos-spec glTF validation with line-level error reporting
HDR environment maps, PBR materials, skinned mesh animations, morph targets, and embedded cameras
OrbitControls (pan, zoom, rotate) with configurable auto-rotation
Real-time parameter tweaking (lights, exposure, morph weights) via dat.GUI

Agent Runtime

LLM brain powered by Claude (Anthropic API) with a structured tool-loop architecture
Up to 8 tool iterations per turn before returning final output
Built-in tools: wave, lookAt, play_clip, setExpression, speak, remember
Composable skill system — install skills from IPFS, Arweave, or HTTP; each skill is a self-contained bundle with a description, tool definitions, and async handlers
Weighted emotion blending (celebration, concern, curiosity, empathy, patience) driven by protocol events, not a finite-state machine
Web Speech API for STT/TTS out of the box; ElevenLabs integration for production-quality voice

Identity & On-Chain

ERC-8004 smart contracts (IdentityRegistry, ReputationRegistry, ValidationRegistry) deployable on any EVM chain
Each agent is an ERC-721 token with a stable agentId, owner wallet, delegated signer (EIP-712), and IPFS-pinned manifest
Signed action log — every speak, remember, skill-done, and validate event is recorded on-chain-optionally or in the database with a cryptographic signature
EIP-7710 delegated permissions for composable agent-to-agent authorization
Solana support (SIWS sign-in, Solana wallet linking, Metaplex NFT option)

Embedding & Distribution

<agent-3d> custom element — drop it anywhere with no framework dependency
Five widget variants: turntable, animation gallery, talking agent, ERC-8004 passport card, hotspot tour
Widget Studio — point-and-click embed code generator
Open Graph metadata and oEmbed support for rich social previews when links are shared
Versioned CDN bundles at /agent-3d/x.y.z/agent-3d.js

Backend & Integrations

OAuth 2.1 server (RFC 6749 + PKCE, RFC 7591 dynamic registration, RFC 7009 revocation, RFC 7662 introspection, RFC 8414 discovery)
Developer API keys with scope and expiry
MCP (Model Context Protocol) over HTTP with JSON-RPC 2.0 for tool-calling from external AI systems
Ready Player Me, Avaturn (photo-to-avatar), and Privy (embedded wallet) integrations
DCA strategy execution and on-chain subscription scheduling via cron jobs
OpenAPI 3.1 spec generated at /openapi.json

Screenshots

Viewer	Widget Studio

Agent Discovery	Avatar Creation

Architecture

The platform is organized into four layers. All layers communicate through a single event bus (agent-protocol) rather than direct calls.

┌────────────────────────────────────────────────────────────┐
│  Layer 4: Embed & Distribution                             │
│  <agent-3d> web component · CDN library · 5 widget types  │
│  Widget Studio · oEmbed · Open Graph cards                 │
└────────────────────────────────────────────────────────────┘
                            ↓ protocol events
┌────────────────────────────────────────────────────────────┐
│  Layer 3: Identity & Persistence                           │
│  Agent passport · ERC-8004 on-chain registry              │
│  Signed action log · Memory store · Wallet linking        │
└────────────────────────────────────────────────────────────┘
                            ↓ protocol events
┌────────────────────────────────────────────────────────────┐
│  Layer 2: Agent Runtime                                    │
│  LLM tool-loop · Built-in tools · Skill registry          │
│  Empathy Layer (emotion blending) · TTS/STT               │
└────────────────────────────────────────────────────────────┘
                            ↓ protocol events
┌────────────────────────────────────────────────────────────┐
│  Layer 1: Viewer                                           │
│  three.js r176 · glTF / GLB · Draco / KTX2 / Meshopt     │
│  Animations · Morph targets · HDR · Validation            │
└────────────────────────────────────────────────────────────┘

The event bus decouples every component. The avatar emotion system reacts to speak events without knowing the runtime exists. The identity module records actions without knowing the UI exists. This makes the system testable, embeddable in isolation, and composable across pages.

The backend is stateless serverless functions. All persistent state lives in Postgres (Neon), object storage (Cloudflare R2), or on-chain. Cron jobs handle scheduled blockchain operations (ERC-8004 crawl, DCA execution, subscription execution).

Tech Stack

Frontend

Technology	Version	Purpose
three.js	r176	WebGL 2.0 rendering
Vite	7.3.2	Build tooling + HMR
Vitest	4.1.4	Unit testing
viem	2.18.0	Ethereum wallet + SIWE
ethers	6.16.0	Contract interaction
@solana/web3.js	1.98.4	Solana RPC + signing
jose	5.9.6	JWT handling
zod	3.23.8	Schema validation
gltf-validator	2.0.0-dev.3.10	Khronos spec compliance
dat.gui	0.7.9	Real-time parameter UI
simple-dropzone	0.8.3	Drag-and-drop file handling
vhtml	2.2.0	JSX → HTML string rendering

Backend (Vercel serverless)

Technology	Purpose
Neon Postgres	Primary database
Cloudflare R2	Avatar / model object storage
Upstash Redis	Rate limiting
Anthropic SDK	Claude LLM (claude-sonnet-4-6 / claude-opus-4-7)
Resend	Transactional email
Sentry	Error monitoring
@aws-sdk/client-s3	R2 presigned upload URLs

Smart Contracts

Technology	Purpose
Solidity 0.8+	ERC-8004 contracts
Foundry	Compile, test, deploy
ERC-721	Agent token standard
EIP-712	Typed structured signing
EIP-7710	Delegated permissions

Getting Started

Use the embeddable web component (no setup)

Install from npm:

npm install three.ws

import 'three.ws';
// <agent-3d src="/path/to/avatar.glb"></agent-3d>

Or load via CDN:

<script type="module" src="https://unpkg.com/three.ws"></script>
<agent-3d src="/path/to/avatar.glb"></agent-3d>

Package: https://www.npmjs.com/package/three.ws

Run the full platform locally

Prerequisites

Node.js 20+
npm 10+
A Neon Postgres database (or any Postgres 15+)
A Cloudflare R2 bucket (or any S3-compatible store)
An Anthropic API key (for the LLM backend)

Installation

git clone https://github.com/nirholas/3D-Agent.git
cd 3D-Agent
npm install

Environment Setup

Copy the example env file and fill in required values:

cp .env.example .env.local

At minimum, set:

PUBLIC_APP_ORIGIN=http://localhost:3000
DATABASE_URL=postgres://user:pass@host/db
JWT_SECRET=<run: openssl rand -base64 64>
ANTHROPIC_API_KEY=sk-ant-...

See Environment Variables for the full reference.

Initialize the Database

The schema is idempotent — run it against your Postgres instance to create all tables:

psql $DATABASE_URL < api/_lib/schema.sql

Start the Dev Server

npm run dev

Opens at http://localhost:3000. The landing page is at /, the viewer at /app, the user dashboard at /dashboard, and the agent creation flow at /create. For the full list of routes, see docs/internal/PAGES.md.

Quick Viewer Test

Navigate to http://localhost:3000/app and drag any GLB file onto the canvas. The model loads instantly with PBR materials, animations, and full glTF validation.

To try the agent, navigate to /create, upload a GLB, and configure a brain (requires ANTHROPIC_API_KEY in your env).

Examples

Copy-paste ready snippets for the most common use cases. Swap in your own GLB URL and go.

1. Minimal viewer (no AI)

The simplest possible setup — one script tag, one element, zero build step.

<!doctype html>
<html lang="en">
<head>
  <meta charset="utf-8">
  <title>3D Viewer</title>
  <style>
    body { margin: 0; background: #0a0a0a; display: flex; align-items: center; justify-content: center; height: 100vh; }
    agent-3d { width: 400px; height: 560px; display: block; }
  </style>
</head>
<body>
  <script type="module" src="https://three.ws/agent-3d/1.5.1/agent-3d.js"></script>
  <agent-3d body="https://cdn.three.ws/models/sample-avatar.glb"></agent-3d>
</body>
</html>

Drag-to-rotate, scroll-to-zoom, full PBR rendering — no API key, no account required. Swap body= for any publicly accessible .glb URL.

2. Talking agent with inline instructions

Add brain= and instructions= to turn the viewer into a conversational agent.

<script type="module" src="https://three.ws/agent-3d/1.5.1/agent-3d.js"></script>

<agent-3d
  body="https://cdn.three.ws/models/sample-avatar.glb"
  brain="claude-sonnet-4-6"
  name="Aria"
  instructions="You are Aria, a friendly AI guide. Be warm, concise, and occasionally playful.
                When someone greets you, wave at them. Keep replies to 2–3 sentences."
  mode="inline"
  width="400px"
  height="560px"
></agent-3d>

The chat input and mic button appear automatically when brain is set. No UI to build.

Pin the agent to a corner of the page so it persists as users scroll.

<script type="module" src="https://three.ws/agent-3d/1.5.1/agent-3d.js"></script>

<agent-3d
  body="https://cdn.three.ws/models/sample-avatar.glb"
  brain="claude-sonnet-4-6"
  instructions="You are a helpful product assistant. Answer questions about our features."
  mode="floating"
  position="bottom-right"
  width="320px"
  height="420px"
></agent-3d>

position accepts bottom-right, bottom-left, top-right, or top-left.

4. Load a registered agent by ID

If you've registered an agent on the platform, load it entirely from its manifest — no inline attributes needed.

<!-- By platform agent ID -->
<agent-3d agent-id="a_abc123def456"></agent-3d>

<!-- By on-chain ERC-8004 ID -->
<agent-3d agent-id="42" chain-id="8453"></agent-3d>

The element fetches the manifest (model URL, instructions, skills, memory config) automatically.

5. Custom chat UI with JavaScript API

Hide the built-in chrome and wire in your own input using the element's JS API.

<script type="module" src="https://three.ws/agent-3d/1.5.1/agent-3d.js"></script>

<agent-3d id="agent" body="./avatar.glb" brain="claude-sonnet-4-6" kiosk
  style="width:400px;height:560px;display:block"></agent-3d>

<input id="msg" type="text" placeholder="Ask something…">
<button onclick="send()">Send</button>

<script>
  const agent = document.getElementById('agent');
  const input = document.getElementById('msg');

  async function send() {
    const text = input.value.trim();
    if (!text) return;
    input.value = '';
    await agent.say(text);
  }

  input.addEventListener('keydown', e => { if (e.key === 'Enter') send(); });

  // Auto-greet on load
  agent.addEventListener('agent:ready', () => {
    setTimeout(() => agent.say('Hello! How can I help you today?'), 1200);
  });

  // Listen to replies
  agent.addEventListener('brain:message', e => {
    if (e.detail.role === 'assistant') console.log('Agent:', e.detail.content);
  });
</script>

Full JS API:

Method	Description
`agent.say(text)`	Send a message; agent speaks and animates the reply
`agent.ask(text)`	Same as `say()`, returns reply text as a string
`agent.wave()`	Trigger the wave gesture directly
`agent.lookAt(target)`	`'camera'`, `'model'`, or `'user'`
`agent.play(clipName)`	Play a named animation clip
`agent.clearConversation()`	Reset conversation history
`agent.expressEmotion(trigger, weight)`	Manually inject an emotion blend

Key events: agent:ready, brain:message, brain:thinking, skill:tool-called, voice:transcript

Use a widget URL directly — no script tag needed.

<iframe
  src="https://three.ws/a/8453/42/embed"
  width="400"
  height="560"
  frameborder="0"
  allow="microphone"
  style="border-radius:16px;"
></iframe>

Generate the src URL from Widget Studio — pick an avatar, choose a widget type, and copy the snippet.

7. Agent manifest JSON

For anything beyond a quick one-liner, define the agent in a manifest file and reference it with manifest=.

agent.json:

{
  "spec": "agent-manifest/0.2",
  "name": "Aria",
  "description": "A friendly AI guide",
  "body": {
    "uri": "./avatar.glb",
    "format": "gltf-binary"
  },
  "brain": {
    "provider": "anthropic",
    "model": "claude-sonnet-4-6",
    "instructions": "You are Aria, a warm and curious AI guide. Wave when greeted.",
    "temperature": 0.8,
    "maxTokens": 1024
  },
  "voice": {
    "tts": { "provider": "browser", "rate": 1.05 },
    "stt": { "provider": "browser", "language": "en-US" }
  },
  "memory": { "mode": "local" },
  "skills": [
    { "uri": "https://cdn.three.ws/skills/wave/" }
  ]
}

<agent-3d manifest="./agent.json" width="400px" height="560px"></agent-3d>

Tutorials

Step-by-step guides in docs/tutorials/:

Tutorial	What you'll build	Time
Build Your First Agent	A talking 3D character on a shareable page, from zero	~20 min
Embed on Your Website	Add an agent to any page — plain HTML, React, Webflow, WordPress	~15 min
Write a Custom Skill	A new tool the agent can call (e.g., fetch live weather data)	~30 min
Register On-Chain	Mint your agent as an ERC-8004 token with permanent identity	~20 min
Build a Personal AI Site	A full personal site with an embedded AI version of yourself	~45 min

Common gotchas

CORS — if your GLB is hosted on a different domain, the server must send Access-Control-Allow-Origin: *. Without it the fetch is blocked and the canvas stays blank. Uploading via the platform's storage sets this automatically.

File size — models over ~50 MB load slowly. Compress with Draco:

npx gltf-transform draco input.glb output.glb

Voice on HTTPS — getUserMedia (microphone) requires HTTPS. Localhost is exempt; any remote deployment needs TLS. Vercel and Netlify both provide it automatically.

CSP — if your page has a strict Content Security Policy, add:

script-src 'self' https://three.ws;

For sandboxed iframes use the widget embed path instead — it runs in its own browsing context.

Project Structure

3D-Agent/
├── home.html                   # Landing page (served at /)
├── index.html                  # Legacy marketing page
├── app.html                    # Main viewer (drag-and-drop + /deploy alias)
├── create.html                 # Avatar + agent creation wizard
├── profile.html                # User profile (/profile, /u/[username])
├── avatar-page.html            # Public avatar detail (/avatars/[id])
├── agent-home.html             # Agent detail & action timeline
├── agent-edit.html             # Agent editing UI
├── agent-embed.html            # Chromeless embed variant
├── a-edit.html                 # On-chain agent edit
├── a-embed.html                # On-chain agent embed
│
├── src/                        # Frontend JavaScript (~80 modules, ~15k lines)
│   ├── viewer.js               # three.js renderer core (1,534 lines)
│   ├── app.js                  # SPA entry + URL routing (460 lines)
│   ├── agent-protocol.js       # Event bus (200-action ring buffer)
│   ├── agent-avatar.js         # Empathy Layer (morph targets, emotion) (694 lines)
│   ├── agent-identity.js       # Passport, diary, signed action history
│   ├── element.js              # <agent-3d> custom element
│   ├── runtime/
│   │   ├── index.js            # LLM tool-loop engine
│   │   ├── providers.js        # AnthropicProvider, NullProvider
│   │   ├── scene.js            # SceneController bridge to three.js
│   │   ├── tools.js            # Built-in tools (wave, speak, remember...)
│   │   └── speech.js          # TTS + STT
│   ├── memory/
│   │   └── index.js            # File-based memory (local/ipfs/encrypted-ipfs/none)
│   ├── skills/
│   │   ├── index.js            # SkillRegistry
│   │   └── <name>/             # Bundled skills (SKILL.md, tools.json, handlers.js)
│   ├── erc8004/
│   │   ├── abi.js              # Contract ABIs + deployment addresses
│   │   ├── agent-registry.js   # connectWallet, registerAgent, pinToIPFS
│   │   └── reputation.js       # submitFeedback, getReputation
│   └── widgets/                # Five widget type implementations
│
├── api/                        # Vercel serverless functions (~153 endpoints, ~3.6k lines)
│   ├── agents.js               # Agent CRUD (321 lines)
│   ├── chat.js                 # LLM chat endpoint (298 lines)
│   ├── mcp.js                  # MCP server over HTTP (759 lines)
│   ├── agent-actions.js        # Record signed actions (122 lines)
│   ├── agent-memory.js         # Memory CRUD + recall (188 lines)
│   ├── auth/                   # Login, register, SIWE, Privy, sessions
│   ├── oauth/                  # OAuth 2.1 server (authorize, token, register...)
│   ├── avatars/                # Avatar CRUD + presigned upload
│   ├── widgets/                # Widget CRUD + OG + oEmbed
│   ├── erc8004/                # Blockchain hydrate, import, pin
│   ├── cron/                   # Scheduled jobs (crawl, DCA, subscriptions)
│   └── _lib/                   # Shared helpers (db, auth, r2, validate, email...)
│       └── schema.sql          # Idempotent Postgres migrations
│
├── public/                     # Static subapps + assets
│   ├── studio/                 # Widget Studio SPA
│   ├── dashboard/              # User dashboard SPA (actions, sessions, storage, usage, wallets, embed-policy, agent-pumpfun)
│   ├── settings/               # Account settings
│   ├── admin/                  # Staff admin surface
│   ├── validation/             # glTF validator tool
│   ├── discover/               # Agent discovery SPA
│   ├── my-agents/              # Owner agent list
│   ├── reputation/             # Reputation registry browser
│   ├── widgets-gallery/        # Public widget gallery
│   ├── hydrate/                # Import on-chain agent
│   ├── features/               # Features marketing page
│   ├── first-meet/             # First-time-user onboarding
│   ├── artifact/               # Claude Artifact viewer bundle
│   ├── cz/                     # CZ demo experience
│   ├── lobehub/iframe/         # LobeHub plugin surface
│   ├── pumpfun.html            # pump.fun token launcher
│   ├── vanity-wallet.html      # Solana vanity-address grinder
│   ├── strategy-lab.html       # DCA strategy designer
│   ├── agent-passport.html     # Solana agent passport
│   ├── login.html, register.html, forgot-password.html, reset-password.html
│   └── animations/             # Animation clip library
│
├── contracts/                  # Foundry + Solidity (ERC-8004)
│   ├── src/
│   │   ├── IdentityRegistry.sol    # ERC-721 agent tokens (EIP-712)
│   │   ├── ReputationRegistry.sol  # Signed reviewer feedback
│   │   └── ValidationRegistry.sol  # Validator attestations
│   ├── script/Deploy.s.sol
│   ├── test/IdentityRegistry.test.sol
│   └── DEPLOYMENTS.md          # Chain deployment addresses
│
├── docs/                       # Architecture, API, deployment guides (see internal/PAGES.md for full route audit)
├── specs/                      # Formal specs (manifest, embed, skill, memory...)
├── tests/                      # Vitest test suite (~30 files)
├── scripts/                    # Build tools (publish, icon gen, animations)
│
├── vite.config.js              # App build config
├── vite.config.artifact.js     # Standalone artifact bundle
├── vercel.json                 # Routes, rewrites, crons, headers
└── package.json                # Scripts + dependencies

The Agent System

Event Bus (Agent Protocol)

src/agent-protocol.js implements a lightweight EventTarget subclass that is the nervous system of the platform. Every component — avatar, runtime, identity, UI — communicates exclusively through this bus. There are no direct method calls between layers.

The bus maintains a 200-action ring buffer for debugging and replay. Embed variants expose a filtered subset of events through postMessage to the host page.

Core event types:

Event	Payload	Who emits	Who listens
`speak`	`{ text, sentiment: -1..1 }`	runtime, skills	avatar (emotion), identity (log), chat UI
`think`	`{ thought }`	runtime	home (timeline), avatar
`gesture`	`{ name, duration }`	avatar, skills	avatar (one-shot clip)
`emote`	`{ trigger, weight: 0..1 }`	avatar	avatar (emotion inject)
`look-at`	`{ target: 'user'\|'camera'\|'center' }`	skills	scene controller
`perform-skill`	`{ skill, args, animationHint }`	runtime	skill registry
`skill-done`	`{ skill, result }`	skills	avatar, identity
`skill-error`	`{ skill, error }`	skills	avatar, identity
`remember`	`{ type, content, ... }`	skills, runtime	memory, identity
`load-start` / `load-end`	`{ uri, error? }`	viewer	avatar (emotion)
`validate`	`{ errors, warnings }`	validator	avatar, identity
`presence`	`{ state }`	element	home UI

Identity-relevant events (speak, remember, sign, skill-done, validate, load-end) are fire-and-forwarded to POST /api/agent-actions for durable logging.

LLM Runtime

src/runtime/index.js implements the Runtime class, which drives the agent's LLM-powered brain.

Tool-loop flow:

User message (text or STT transcript) arrives
System prompt is assembled: manifest instructions + recalled memory + skill descriptions
Claude is called with the conversation history and all available tools

Tool calls are dispatched in order — each built-in tool or skill handler receives a rich context object:

{ viewer, memory, llm, speak, listen, fetch, loadGLB, loadClip, loadJSON, call, stage, agentId }

Tool results are appended to conversation history as tool_result messages
Steps 3–5 repeat until Claude returns with no tool calls, or the iteration limit (8) is hit
Final text response is optionally spoken via TTS

Providers (src/runtime/providers.js):

AnthropicProvider — connects to the Anthropic API, supports streaming
NullProvider — no-op for testing and offline mode

Built-in tools (src/runtime/tools.js):

Tool	Description
`wave`	Play a wave gesture animation
`lookAt`	Direct the agent's gaze (user, camera, or scene center)
`play_clip`	Play a named animation clip from the model or animation library
`setExpression`	Set a named morph target weight directly
`speak`	Emit text through TTS and the protocol bus
`remember`	Write a memory entry (user, feedback, project, or reference type)

Skills can define additional tools that override or augment the built-ins. The skill registry is loaded from the agent manifest before each conversation turn.

Empathy Layer

src/agent-avatar.js implements the Empathy Layer — a continuous weighted emotion blend that drives the avatar's facial morph targets and head orientation in real time.

Emotions are not a finite-state machine. Each emotion is a float (0..1) that decays linearly per frame at a different rate. Protocol events inject spikes:

Trigger	Emotion	Spike
`speak` (positive sentiment)	celebration	+0.7
`speak` (negative sentiment)	concern	+0.5
`skill-error`	concern + empathy	+0.6 / +0.5
`load-start`	patience + curiosity	+0.4 / +0.3
`validate` (clean)	celebration	+0.5
`validate` (errors)	concern	+0.6

Decay half-lives (approximate):

Patience: ~20s — persists during long operations
Empathy: ~13s — lingers after emotional events
Concern: ~12s — sustained worry
Curiosity: ~8s — alert, fades moderately
Celebration: ~6s — brief, upbeat

The blended emotion mix drives morph target values each frame. For example:

Celebration → mouthSmile 0.85, mouthOpen 0.2
Concern → mouthFrown 0.55, browInnerUp 0.6
Empathy → eyeSquint 0.4, browInnerUp 0.5

Head tilt and lean are also driven by the blend — curiosity tilts the head, patience leans slightly back.

This architecture means the avatar feels responsive and emotionally coherent without any hand-authored animation triggers.

Skills

Skills are self-contained capability bundles that extend the agent's tool set. Each skill lives in its own directory:

skills/wave/
├── SKILL.md        # Human-readable description and usage instructions
├── tools.json      # Tool definitions (name, description, input JSON schema)
└── handlers.js     # Async handler functions (default export)

tools.json example:

[
  {
    "name": "wave",
    "description": "Plays a waving gesture on the avatar for the specified duration.",
    "inputSchema": {
      "type": "object",
      "properties": {
        "duration_ms": { "type": "integer", "minimum": 500, "maximum": 5000 }
      }
    }
  }
]

handlers.js example:

export default {
  async wave(args, ctx) {
    const { viewer, speak } = ctx;
    await viewer.playClipByName('wave');
    return { ok: true, output: 'Waved!' };
  }
};

Skills are loaded from the agent manifest at runtime. The SkillRegistry supports three trust modes:

any — install skills from any source (development only)
owned-only — only skills the agent owner has registered
whitelist — only approved skill URIs

Skills are distributed over IPFS, Arweave, or HTTP. The public skills registry is at /public/skills-index.json.

Memory

src/memory/index.js implements a file-based memory system (mirroring this project's own Claude memory system). Memories are Markdown files with YAML frontmatter, organized by type:

---
type: user
key: user_role
name: User's Role
created: 2024-01-15T10:30:00Z
salience: 0.95
---

User is a game developer interested in character animation.

A MEMORY.md index file is auto-maintained. At the start of each conversation turn, the memory store is scanned and high-salience entries are injected into the system prompt.

Storage modes:

local — stored in the browser's local storage (default for development)
ipfs — pinned to IPFS via Pinata or Web3.Storage
encrypted-ipfs — encrypted before pinning (user holds the key)
none — stateless, no memory between sessions

Memory types (user, feedback, project, reference) follow the same taxonomy used by this codebase's own Claude guidelines.

Web Component & Embedding

The <agent-3d> custom element (src/element.js) is the primary distribution mechanism. It lazy-boots on intersection (IntersectionObserver), so off-screen agents don't load until visible.

Basic usage:

<script src="https://three.ws/agent-3d/latest/agent-3d.js"></script>

<agent-3d
  body="https://example.com/my-avatar.glb"
  brain="https://example.com/manifest.json"
  mode="chat"
></agent-3d>

Key attributes:

Attribute	Type	Description
`body`	URL	GLB model URL
`brain`	URL	Agent manifest JSON URL
`agent-id`	string	Registered agent ID (resolves manifest automatically)
`mode`	`view` \| `chat` \| `embed`	Interaction mode
`eager`	boolean	Load immediately without intersection check
`sandbox`	boolean	Disable network calls (offline mode)
`width` / `height`	number	iframe dimensions when generating embed code

The element fires a postMessage API for host-page communication (documented in specs/EMBED_HOST_PROTOCOL.md). Hosts can send events to the agent and receive speak, think, and skill-done events back.

Versioned CDN bundles are published at /agent-3d/x.y.z/agent-3d.js. Use latest for auto-updates or pin to a version for stability:

<script src="https://three.ws/agent-3d/1.5.1/agent-3d.js"></script>

The Widget Studio (/studio) lets anyone build a shareable, embeddable 3D experience without writing code. Pick an avatar, pick a widget type, configure it, and get an iframe snippet.

Five widget types:

Widget	Description
Turntable	Auto-rotating model showcase with configurable background, lighting, and camera
Animation Gallery	Paginated grid of named clips; click any to play it on the model
Talking Agent	Full chat interface with the LLM brain; embed a conversational agent anywhere
ERC-8004 Passport	On-chain identity card — shows agent name, owner, reputation score, and verification badge
Hotspot Tour	3D hotspots pinned to world-space coordinates; click to reveal text annotations

Each widget has:

A public URL at /w/<id> with server-rendered Open Graph metadata for rich link previews
An oEmbed endpoint at /api/widgets/oembed for WordPress, Ghost, Notion embedding
An iframe embed URL at /api/widgets/<id>/view
A view counter tracked at /api/widgets/<id>/stats
A duplicate API at /api/widgets/<id>/duplicate

Widgets are stored as JSON config in Postgres, pointing at an avatar in R2.

API Reference

The full OpenAPI 3.1 spec is available at /openapi.json. The key API surface is organized below.

Agent API

Method	Route	Auth	Description
GET	`/api/agents`	session	List your agents
POST	`/api/agents`	session	Create an agent
GET	`/api/agents/:id`	—	Get agent detail
PATCH	`/api/agents/:id`	session	Update agent
DELETE	`/api/agents/:id`	session	Delete agent
GET	`/api/agents/:id/manifest`	—	Download manifest JSON
POST	`/api/agents/:id/sign`	session	Sign a message with agent wallet
GET/POST	`/api/agents/:id/embed-policy`	session	Manage iframe origin allowlist
POST	`/api/agents/register-prep`	session	Prep EVM on-chain registration
POST	`/api/agents/register-confirm`	session	Confirm EVM registration
POST	`/api/agent-actions`	session	Record signed agent action

Avatar API

Method	Route	Auth	Description
GET	`/api/avatars`	—	List public avatars
POST	`/api/avatars`	session	Create avatar record
GET	`/api/avatars/:id`	—	Get avatar detail
PATCH	`/api/avatars/:id`	session	Update metadata
DELETE	`/api/avatars/:id`	session	Soft-delete avatar
POST	`/api/avatars/:id/presign`	session	Get presigned R2 upload URL
POST	`/api/avatars/:id/pin-ipfs`	session	Pin to IPFS

Three-step upload flow:

1. POST /api/avatars/:id/presign  →  { url, storage_key }
2. PUT <presigned_url>            ←  raw GLB bytes
3. POST /api/avatars              →  register metadata with storage_key

Method	Route	Auth	Description
GET	`/api/widgets`	session	List your widgets
POST	`/api/widgets`	session	Create widget
PATCH	`/api/widgets/:id`	session	Update widget
DELETE	`/api/widgets/:id`	session	Delete widget
POST	`/api/widgets/:id/duplicate`	session	Clone widget
GET	`/api/widgets/:id/stats`	—	View stats
GET	`/api/widgets/oembed`	—	oEmbed card

Memory API

Method	Route	Auth	Description
GET	`/api/agent-memory/:id`	session	Fetch agent memory store
POST	`/api/agent-memory/:id`	session	Append memory entries
PUT	`/api/agent-memory/:id`	session	Replace memory store

Chat & LLM

Method	Route	Auth	Description
POST	`/api/chat`	session \| api-key	Chat with agent (Claude backend)
POST	`/api/llm/anthropic`	session	Anthropic API proxy

Cron Jobs

Scheduled via vercel.json, these run automatically in production:

Schedule	Endpoint	Purpose
Every 15 min	`/api/cron/erc8004-crawl`	Index new agents from blockchain
Every 5 min	`/api/cron/index-delegations`	Index EIP-7710 delegations
Hourly	`/api/cron/run-dca`	Execute DCA strategy orders
Hourly	`/api/cron/run-subscriptions`	Execute recurring subscriptions

Authentication & OAuth 2.1

three.ws supports three authentication methods:

1. Email + Password (Session cookie)

POST /api/auth/register   →  create account
POST /api/auth/login      →  JWT session cookie
GET  /api/auth/me         →  current user
POST /api/auth/logout     →  revoke session

2. Wallet (SIWE / SIWS)

POST /api/auth/siwe        →  get nonce challenge
POST /api/auth/siwe/verify →  verify EIP-4361 signed message → session
POST /api/auth/siws        →  Solana equivalent

3. Developer API Keys

POST /api/api-keys          →  create key (set scope + expiry)
DELETE /api/api-keys/:id    →  revoke key
Authorization: Bearer sk-...  →  authenticate requests

OAuth 2.1 Server (RFC 6749 + PKCE)

For third-party apps and MCP integrations:

GET  /oauth/authorize                       →  consent screen
POST /oauth/authorize                       →  submit consent → auth code
POST /oauth/token                           →  exchange code for tokens
POST /oauth/register                        →  RFC 7591 dynamic client reg
POST /oauth/revoke                          →  RFC 7009 token revocation
POST /oauth/introspect                      →  RFC 7662 token check
GET  /.well-known/oauth-authorization-server →  RFC 8414 discovery
GET  /.well-known/oauth-protected-resource  →  RFC 9728 resource discovery

Token scopes: avatars:read, avatars:write, agents:read, agents:write, mcp.

Access tokens are short-lived JWTs (1 hour). Refresh tokens are opaque strings stored hashed in Postgres.

MCP Server

api/mcp.js (759 lines) implements the Model Context Protocol 2025-06-18 specification over HTTP with JSON-RPC 2.0. It enables external AI systems (including Claude Desktop, other agents, or custom integrations) to drive avatars programmatically.

Endpoint: POST /api/mcp Auth: OAuth 2.1 Bearer token with mcp scope Registry: Listed on the official MCP Registry as io.github.nirholas/three.ws x402scan: view on x402scan — paid MCP tool calls and revenue

Available tools:

Tool	Description
`list_my_avatars`	List all avatars owned by the authenticated user
`get_avatar`	Fetch metadata and download URL for a specific avatar
`search_public_avatars`	Search the public avatar library by name, tag, or description
`render_avatar`	Generate a preview render of an avatar (returns image URL)
`delete_avatar`	Permanently delete an avatar
`validate_model`	Run Khronos glTF validation and return error report
`inspect_model`	Inspect model internals (mesh count, material list, animation names, texture sizes)
`optimize_model`	Optimize a model (Draco compression, texture downscale, mesh simplification)

MCP discovery: configured in .mcp.json at the repo root for Claude Desktop integration.

SSE stream: GET /api/mcp returns a Server-Sent Events stream for real-time notifications from long-running operations (validation, optimization).

On-Chain Identity (ERC-8004)

ERC-8004 is a draft standard for verifiable 3D agent identity. The contracts/ directory contains a full Foundry implementation.

Contracts

IdentityRegistry.sol — the primary contract. Each agent is an ERC-721 token with:

agentId — stable numeric ID (the token ID)
owner — EVM address of the agent's owner
delegatedSigner — optional secondary address for runtime signing (EIP-712 typed signature)
tokenURI — IPFS URL of the agent manifest JSON
metadata — on-chain name, description, image pointer

ReputationRegistry.sol — stores signed feedback scores. Each reviewer can submit one score per agent. Scores are averaged for an on-chain reputation metric.

ValidationRegistry.sol — records validator attestations for off-chain proofs (glTF validation reports, skill audits, security reviews).

Deployment Addresses

See contracts/DEPLOYMENTS.md for current mainnet and testnet addresses.

Registration Flow (EVM)

1. POST /api/agents/register-prep   →  { manifest, typedData }
   (uploads manifest to IPFS, builds EIP-712 typed data for signing)

2. User signs typedData with their wallet

3. POST /api/agents/register-confirm  →  { txHash, agentId }
   (submits transaction, waits for confirmation, updates agent record)

The agent is now an ERC-721 token. Its manifest lives on IPFS. Its action history is anchored to its agentId. Any third party can verify the agent's identity, owner, and reputation without trusting three.ws.

On-Chain Indexing

api/cron/erc8004-crawl.js runs every 15 minutes to index new IdentityRegistry mint events. Indexed agents appear in /discover and can be imported via /hydrate.

Solana variant — same shape, no deployed program

Solana ships an ERC-8004 analog without any custom on-chain program:

Identity — Metaplex Core NFT minted via registerSolanaAgent() (the asset pubkey is the agent ID).
Reputation + Validation — signed SPL Memo transactions referencing the agent asset pubkey, with a JSON envelope (threews.feedback.v1 / threews.validation.v1). Anyone can read every attestation about an agent via getSignaturesForAddress(assetPubkey).

SDK:

import { attestFeedback, attestValidation, listAttestations } from '@nirholas/agent-kit';

await attestFeedback({ agentAsset, score: 5, network: 'devnet' });
await attestValidation({ agentAsset, taskHash: '0x…', passed: true, network: 'devnet' });
const rows = await listAttestations({ agentAsset, kind: 'all', network: 'devnet' });

Server read endpoint: GET /api/agents/solana-attestations?asset=<pubkey>&kind=feedback|validation|all&network=devnet|mainnet.

Demo page: sdk/example/solana-attest.html.

Pump.fun signals (Solana off-chain reputation)

Solana agents can ingest live pump.fun activity (GitHub social-fee claims, token graduations) as off-chain trust signals that feed into the agent's Solana reputation score and surface through the Empathy Layer in real time.

Surface	Path	Purpose
MCP client	api/_lib/pumpfun-mcp.js	Cached JSON-RPC client to upstream `pumpfun-claims-bot`
Read API	api/agents/pumpfun.js	`?op=claims\|graduations\|token\|creator`
SSE feed	api/agents/pumpfun-feed.js	Live event stream, 90s window, auto-reconnects
Cron crawler	api/cron/pumpfun-signals.js	15-min sweep → `pumpfun_signals` table
Skills	src/agent-skills-pumpfun-watch.js	`recent-claims`, `token-intel`, `watch-start`, `watch-stop`
Widget	src/widgets/pumpfun-feed.js	Live cards overlay
Reputation	api/agents/solana-reputation.js	`pumpfun_signals` block in response
Passport	api/agents/solana-card.js	`pumpfun` block on the agent card

The crawler runs on a */15 * * * * schedule (see vercel.json) and writes into the pumpfun_signals table. Agents subscribed via watch-start react to incoming events through the existing protocol bus — no new event types required.

Full design and configuration in docs/solana-pumpfun.md.

Database Schema

The Postgres schema (api/_lib/schema.sql) is fully idempotent — all migrations use CREATE TABLE IF NOT EXISTS patterns. Safe to re-run on any environment.

Core tables:

-- Users
users (id, email, password_hash, display_name, avatar_url, plan, wallet_address, deleted_at)

-- 3D model files
avatars (id, owner_id, slug, name, description, storage_key, visibility,
         tags, checksum_sha256, version, deleted_at)

-- Sessions
sessions (id, user_id, token_hash, user_agent, ip, expires_at, revoked_at)

-- Developer API keys
api_keys (id, user_id, prefix, token_hash, scope, expires_at, revoked_at)

-- Agent identities
agent_identities (id, user_id, name, description, avatar_id, skills,
                  meta, wallet_address, erc8004_agent_id, deleted_at)

-- Signed action log
agent_actions (id, agent_id, type, payload, source_skill,
               signature, signer_address, created_at)

-- Memory store
agent_memories (id, agent_id, type, content, tags, context,
                salience, expires_at, created_at)

OAuth tables:

oauth_clients       (client_id, client_secret_hash, redirect_uris, grant_types, scope, ...)
oauth_auth_codes    (code, client_id, user_id, code_challenge, expires_at, consumed_at)
oauth_refresh_tokens(token_hash, client_id, user_id, scope, expires_at, revoked_at, ...)

Wallet & signing:

user_wallets  (user_id, address, chain_type, chain_id, is_primary)
siwe_nonces   (nonce, address, issued_at, expires_at, consumed_at)
siws_nonces   (same shape for Solana)

Usage & quotas:

usage_events (user_id, api_key_id, client_id, avatar_id, kind, tool, status, bytes, latency_ms)
plan_quotas  (plan, max_avatars, max_bytes_per_avatar, max_total_bytes)

Build & Deployment

npm Scripts

Command	Description
`npm run dev`	Vite dev server on port 3000 with HMR
`npm run build`	Production build to `dist/`
`npm run build:lib`	Build `<agent-3d>` web component library to `dist-lib/`
`npm run build:artifact`	Build standalone Claude artifact viewer bundle
`npm run build:all`	build + build:lib + publish:lib
`npm run publish:lib`	Publish versioned CDN bundles to `/agent-3d/`
`npm run test`	Run Vitest suite
`npm run verify`	Prettier check + Vite build (pre-deploy gate)
`npm run format`	Prettier write (entire repo)
`npm run deploy`	build:all + vercel --prod
`npm run clean`	Remove dist/ and dist-lib/
`npm run fetch-animations`	Download animation clip assets
`npm run generate-icons`	Generate PWA icon set

Vercel Deployment

The project is built for Vercel. Deployment is one command:

npm run deploy

This runs build:all then vercel --prod. Routing, rewrites, cache headers, and cron schedules are defined in vercel.json.

For preview deployments, push a branch — Vercel auto-deploys it with a preview URL.

Environment variables must be set in the Vercel dashboard (not in .env files). See Environment Variables for the full list.

Self-Hosting

For a traditional server deployment:

Build: npm run build → dist/
Serve dist/ as static files (nginx, Caddy, Express)
Run api/ endpoints via Node.js (wrap with Express or use the Vercel dev adapter)
Connect to Postgres (Neon or self-hosted)
Connect to S3-compatible storage (R2, MinIO, AWS S3)
Schedule cron jobs with node-cron or systemd timers

Minimal nginx config:

server {
    listen 80;
    root /var/www/3d-agent/dist;
    index index.html;

    location /api {
        proxy_pass http://localhost:3001;
    }

    location / {
        try_files $uri $uri/ /index.html;
    }
}

Environment Variables

Required (Backend)

# App
PUBLIC_APP_ORIGIN=https://three.ws           # No trailing slash

# Database
DATABASE_URL=postgres://user:pass@host/db    # Neon or any Postgres 15+

# Object storage (Cloudflare R2 or S3-compatible)
S3_ENDPOINT=https://...
S3_ACCESS_KEY_ID=...
S3_SECRET_ACCESS_KEY=...
S3_BUCKET=3d-agent-avatars
S3_PUBLIC_DOMAIN=https://cdn.three.ws        # CDN base URL for public model URLs

# Redis (rate limiting)
UPSTASH_REDIS_REST_URL=...
UPSTASH_REDIS_REST_TOKEN=...

# Auth
JWT_SECRET=<base64>                          # openssl rand -base64 64
JWT_KID=k1                                   # Key ID (rotate by incrementing)
PASSWORD_ROUNDS=11                           # bcrypt cost factor

# LLM
ANTHROPIC_API_KEY=sk-ant-...
CHAT_MODEL=claude-sonnet-4-6
CHAT_MAX_TOKENS=1024

Optional (Backend)

# Email (required for registration flow)
RESEND_API_KEY=...

# Error monitoring
SENTRY_DSN=...

# Privy (social/embedded wallets)
PRIVY_APP_ID=...
PRIVY_APP_SECRET=...

# Avatar regeneration
AVATURN_API_KEY=...
AVATAR_REGEN_PROVIDER=none                   # none | avaturn

# EIP-7710 permissions relayer
PERMISSIONS_RELAYER_ENABLED=false
AGENT_RELAYER_KEY=0x...
AGENT_RELAYER_ADDRESS=0x...

# Per-chain RPC URLs (add chains as needed)
RPC_URL_84532=https://sepolia.base.org
RPC_URL_8453=https://mainnet.base.org

# IPFS pinning
PINATA_JWT=...
WEB3_STORAGE_TOKEN=...                       # Fallback

Optional (Frontend, prefixed `VITE_`)

VITE_RPM_SUBDOMAIN=demo                      # Ready Player Me subdomain
VITE_PRIVY_APP_ID=...
VITE_AVATURN_EDITOR_URL=https://editor.avaturn.me/
VITE_AVATURN_DEVELOPER_ID=...

Testing

The test suite uses Vitest. API tests mock the database and auth layer; frontend tests mock the viewer.

npm run test                           # All tests
npm run test -- tests/api/agents       # Specific file
npm run verify                         # prettier check + vite build

Test coverage:

Area	Files
Agent CRUD	`tests/api/agents.test.js`
Widget CRUD	`tests/api/widgets.test.js`
OAuth flow	`tests/api/oauth-authorize.test.js`, `oauth-token.test.js`
SIWE wallet auth	`tests/api/siwe.test.js`
LLM proxy	`tests/api/llm-anthropic.test.js`
Schema validation	`tests/api/validate.test.js`
API keys	`tests/api/api-keys.test.js`
Crypto utilities	`tests/api/crypto.test.js`
Embed CORS policy	`tests/api/embed-policy.test.js`
Animation slots	`tests/src/animation-slots.test.js`
Widget types	`tests/src/widget-types.test.js`

Smart contract tests are in contracts/test/ and run via Foundry:

cd contracts && forge test

Contributing

See CONTRIBUTING.md for the full contributor guide.

Quick rules:

Match existing style — no reformatting adjacent code
Every changed line should trace to the task
Add tests for new API endpoints
Run npm run verify before opening a PR (Prettier + build check)
Keep PRs focused — one concern per PR

Branch conventions:

feat/... — new features
fix/... — bug fixes
refactor/... — structural changes without behavior changes
docs/... — documentation only

Development tips:

The viewer runs standalone at /app — no auth, no backend required
Use mode=view in the <agent-3d> element to test rendering without a brain
Set CHAT_MODEL=claude-haiku-4-5-20251001 locally to keep API costs low during development
The MCP server can be tested with curl — it's plain JSON-RPC over HTTP

License

Apache 2.0 — see LICENSE.

The three.js library (node_modules/three) is MIT licensed. The gltf-validator (node_modules/gltf-validator) is Apache 2.0. See each dependency's license for details.

Built with three.js, Claude, and a belief that AI deserves a body.

Three Ws Overview

What is Three Ws about?

How to use Three Ws?

Key Features of Three Ws

Use Cases of Three Ws

FAQ from the Three Ws

Three Ws's README

three.ws

Table of Contents

What is three.ws?

Vision

Roadmap

Phase 0 — Foundations (Shipped)

Phase 1 — Selfie → Avatar Engine

Phase 2 — Agent Personalization

Phase 3 — Onchain Economy

Phase 4 — Open Inference Network

What we need

Key Features

Screenshots

Architecture

Tech Stack

Getting Started

Use the embeddable web component (no setup)

Run the full platform locally

Prerequisites

Installation

Environment Setup

Initialize the Database

Start the Dev Server

Quick Viewer Test

Examples

1. Minimal viewer (no AI)

2. Talking agent with inline instructions

3. Floating bubble (support widget style)

4. Load a registered agent by ID

5. Custom chat UI with JavaScript API

6. iframe widget (works in Notion, Substack, Webflow)

7. Agent manifest JSON

Tutorials

Common gotchas

Project Structure

The Agent System

Event Bus (Agent Protocol)

LLM Runtime

Empathy Layer

Skills

Memory

Web Component & Embedding

Widget System

API Reference

Agent API

Avatar API

Widget API

Memory API

Chat & LLM

Cron Jobs

Authentication & OAuth 2.1

MCP Server

On-Chain Identity (ERC-8004)

Contracts

Deployment Addresses

Registration Flow (EVM)

On-Chain Indexing

Solana variant — same shape, no deployed program

Pump.fun signals (Solana off-chain reputation)

Database Schema

Build & Deployment

npm Scripts

Vercel Deployment

Self-Hosting

Environment Variables

Required (Backend)

Optional (Backend)

Optional (Frontend, prefixed VITE_)

Testing

Contributing

License

Three Ws Reviews

Optional (Frontend, prefixed `VITE_`)