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Gives your AI coding assistant the full SceneView SDK so it writes correct, compilable code.","maintainers":[{"name":"thomasgorisse","email":"thomas.gorisse@gmail.com"}],"readme":"# sceneview-mcp\n\n**Give any AI assistant expert-level knowledge of 3D and AR development.**\n\n[![npm version](https://img.shields.io/npm/v/sceneview-mcp?color=6c35aa)](https://www.npmjs.com/package/sceneview-mcp)\n[![npm downloads](https://img.shields.io/npm/dm/sceneview-mcp?color=blue)](https://www.npmjs.com/package/sceneview-mcp)\n[![Tests](https://img.shields.io/badge/tests-2015%20passing-brightgreen)](#quality)\n[![MCP SDK](https://img.shields.io/badge/MCP%20SDK-v1.29-blue)](https://modelcontextprotocol.io/)\n[![Registry](https://img.shields.io/badge/MCP%20Registry-listed-blueviolet)](https://registry.modelcontextprotocol.io)\n[![License](https://img.shields.io/badge/License-MIT-green)](./LICENSE)\n[![Node](https://img.shields.io/badge/Node-%3E%3D18-brightgreen)](https://nodejs.org/)\n\nThe official [Model Context Protocol](https://modelcontextprotocol.io/) server for **[SceneView](https://sceneview.github.io)** — the cross-platform 3D & AR SDK for Android (Jetpack Compose + Filament), iOS / macOS / visionOS (SwiftUI + RealityKit), and Web (Filament.js + WebXR).\n\nConnect it to Claude Code, Cline, Codex, Cursor, GitHub Copilot, JetBrains AI Assistant — or any other MCP client — locally over stdio, or remotely over Streamable HTTP at **`https://mcp.sceneview.dev/mcp`** (see [Remote server](#remote-server-streamable-http)). Your AI assistant gets specialized tools, compilable code samples, the full API reference, a code validator, and an inline 3D viewer widget — so it writes correct, working 3D/AR code on the first try.\n\n> **Disclaimer:** Generated code is provided \"as is\" without warranty. Always review before production use. See [TERMS.md](./TERMS.md) and [PRIVACY.md](./PRIVACY.md).\n\n---\n\n## Quick start\n\n**One command — no install required:**\n\n```bash\nnpx sceneview-mcp\n```\n\nEvery client below runs that same server. Three config shapes exist across the ecosystem —\n`mcpServers` (most clients), `servers` (VS Code) and `[mcp_servers.*]` (Codex TOML) — but the\ncommand and arguments are identical in all three.\n\n### Any MCP client\n\n```json\n{\n  \"mcpServers\": {\n    \"sceneview\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"sceneview-mcp\"]\n    }\n  }\n}\n```\n\n### Claude Code\n\n```bash\nclaude mcp add sceneview -- npx -y sceneview-mcp\n```\n\nOr commit `.mcp.json` at the repository root so the whole team gets it:\n\n```json\n{ \"mcpServers\": { \"sceneview\": { \"type\": \"stdio\", \"command\": \"npx\", \"args\": [\"-y\", \"sceneview-mcp\"] } } }\n```\n\nOptionally, the [SceneView Claude Code plugin](https://github.com/sceneview/claude-marketplace)\nbundles this server with the three SceneView skills (Compose, SwiftUI, web), the same ones the\nCodex plugin carries:\n\n```bash\n/plugin marketplace add sceneview/claude-marketplace\n/plugin install sceneview@sceneview\n```\n\n### Claude Desktop\n\nSettings → Developer → Edit Config, then add the standard `mcpServers` block above to\n`~/Library/Application Support/Claude/claude_desktop_config.json` (macOS) or\n`%APPDATA%\\Claude\\claude_desktop_config.json` (Windows). Restart after saving.\n\n### Cline\n\nMCP Servers icon → Configure → Configure MCP Servers, or `~/.cline/mcp.json`:\n\n```json\n{ \"mcpServers\": { \"sceneview\": { \"command\": \"npx\", \"args\": [\"-y\", \"sceneview-mcp\"], \"disabled\": false, \"autoApprove\": [] } } }\n```\n\n### Codex\n\n```bash\ncodex mcp add sceneview -- npx -y sceneview-mcp\n```\n\nOr `~/.codex/config.toml` — TOML, and the table is `mcp_servers`, not `mcpServers`:\n\n```toml\n[mcp_servers.sceneview]\ncommand = \"npx\"\nargs = [\"-y\", \"sceneview-mcp\"]\n```\n\nThe same config serves the Codex CLI, the IDE extension and the app.\n\nOptionally, the SceneView repository is itself a Codex plugin that bundles this server with the\nthree SceneView skills. From a checkout (the path must be absolute):\n\n```bash\ncodex plugin marketplace add \"$PWD\"\ncodex plugin add sceneview@sceneview-local\n```\n\n### Cursor\n\nAdd to `.cursor/mcp.json` (project) or `~/.cursor/mcp.json` (global) — the standard\n`mcpServers` block above. Cursor also accepts an install link:\n\n```\ncursor://anysphere.cursor-deeplink/mcp/install?name=sceneview&config=eyJjb21tYW5kIjoibnB4IiwiYXJncyI6WyIteSIsInNjZW5ldmlldy1tY3AiXX0=\n```\n\n### Gemini CLI\n\nThe repository root carries a [`gemini-extension.json`](../gemini-extension.json), so the CLI\ninstalls the server straight from GitHub — no JSON to paste:\n\n```bash\ngemini extensions install https://github.com/sceneview/sceneview\n```\n\n**This clones the whole monorepo** — over 2 GB of history — because the CLI installs an\nextension by cloning the repository that declares it, and SceneView's manifest sits in a\nrepository that also carries the Android, Apple, Web, Flutter and React Native sources. If you\nwant the server and not the clone, paste the standard `mcpServers` block into\n`~/.gemini/settings.json` instead; it is the same command, `npx -y sceneview-mcp`, and it costs\na download of the npm package.\n\nEither way, `npx` resolves `sceneview-mcp` to the **latest version published on npm**, which is\nnot necessarily the version this manifest declares — the manifest's `version` describes the\nextension, and the server it launches updates on npm's cadence.\n\nThe extension declares nothing but the server: `npx -y sceneview-mcp` over stdio, no context\nfile and no tool exclusions, so it adds the SceneView tools to a session and changes nothing\nelse about it.\n\n### Gemini in Android Studio\n\nAndroid Studio's MCP integration **does not support stdio** — it connects over HTTP only, so\npoint it at the hosted endpoint. Settings → Tools → AI → MCP Servers:\n\n```json\n{ \"mcpServers\": { \"sceneview\": { \"httpUrl\": \"https://mcp.sceneview.dev/mcp\", \"enabled\": true } } }\n```\n\n### GitHub Copilot\n\nIn VS Code, `.vscode/mcp.json` — note the `servers` key, not `mcpServers`:\n\n```json\n{ \"servers\": { \"sceneview\": { \"type\": \"stdio\", \"command\": \"npx\", \"args\": [\"-y\", \"sceneview-mcp\"] } } }\n```\n\nVS Code also accepts an install link:\n\n```\nvscode:mcp/install?%7B%22name%22%3A%22sceneview%22%2C%22command%22%3A%22npx%22%2C%22args%22%3A%5B%22-y%22%2C%22sceneview-mcp%22%5D%7D\n```\n\nIn Copilot CLI:\n\n```bash\ncopilot mcp add sceneview -- npx -y sceneview-mcp\n```\n\n### JetBrains AI Assistant / Junie\n\nSettings → Tools → AI Assistant → Model Context Protocol (MCP) → Add, then paste the standard\n`mcpServers` block above.\n\n### MCP Bundle (`.mcpb`)\n\n[`mcp/manifest.json`](manifest.json) describes this server in the [MCP Bundle\nformat](https://github.com/modelcontextprotocol/mcpb) (spec 0.3), for desktop apps that install\na local server from a bundle rather than a command line. It runs the built `dist/index.js` with\nthe host's Node — the host provides the runtime and **nothing else**, so the bundle has to carry\nits own `node_modules`. Zipping this directory after `npm run build` alone produces a bundle\nthat fails at launch with `Cannot find package '@modelcontextprotocol/sdk'`:\n\n```bash\nnpm ci                                # dev dependencies — the build needs them\nnpm run build                         # writes dist/\nnpm ci --omit=dev --ignore-scripts    # drop the dev tree, keep dist/\nzip -r sceneview-mcp.mcpb manifest.json package.json dist node_modules\n```\n\n`--ignore-scripts` is not optional: this package's `prepare` script ends in `tsc`, and the same\ncommand that omits the dev dependencies omits TypeScript, so without it npm runs `prepare`,\nfails to find `tsc` and exits 127. Reinstall with a plain `npm ci` afterwards to get the dev\ntree back.\n\nThe manifest is not published as a `.mcpb` artefact by CI: it is the descriptor, and packing it\nstays a manual step for whoever needs a bundle. `mcp/src/packaging.test.ts` keeps its name,\nversion, licence, entry point and Node range equal to `package.json`'s — and does the same for\n[`server.json`](server.json) and the root `gemini-extension.json` — because nothing else would\nnotice them drifting.\n\n### Use as a remote connector\n\nNo install, nothing to run: SceneView is hosted as a remote MCP server at\n\n```\nhttps://mcp.sceneview.dev/mcp\n```\n\nAny client that accepts a Streamable HTTP MCP URL can use it. In claude.ai, that is\n**Settings → Connectors → Add custom connector**.\n\n**Authless and read-only.** There is no sign-in, no API key and no account: every tool is a pure\nfunction of the SDK's own documentation, samples and API surface, so there is nothing to\nauthenticate and nothing of yours stored. All tools are annotated `readOnlyHint` except\n`generate_3d_model`, which calls an external generation service and is therefore marked\nopen-world rather than read-only.\n\n**Prefer it local?** `npx -y sceneview-mcp` runs the exact same server over stdio. The local\nroute is the one that reads your project from disk (`analyze_project`) and the one that accepts\nyour own `SKETCHFAB_API_KEY` / `TRIPO_API_KEY` / `RUNWARE_API_KEY`; the hosted connector, being shared and anonymous,\ncannot.\n\n### Remote server (Streamable HTTP)\n\nSome hosts cannot spawn a local process: they need MCP's **Streamable HTTP** transport at a public URL. The same package serves it:\n\n```bash\nnpx sceneview-mcp --http\n# [sceneview-mcp] v4.x — HTTP (remote tool surface)\n# [sceneview-mcp] MCP endpoint: http://127.0.0.1:3333/mcp\n```\n\n| Route | What it does |\n|---|---|\n| `POST /mcp` | MCP JSON-RPC (Streamable HTTP, stateless — no sessions, safe behind any load balancer) |\n| `GET` / `DELETE /mcp` | `405` (no standalone SSE stream, no session to delete) |\n| `GET /health` | `{\"status\":\"ok\",\"version\":\"4.x.y\"}` |\n| `GET /.well-known/openai-apps-challenge` | OpenAI domain verification — returns `OPENAI_APPS_CHALLENGE_TOKEN` as `text/plain`, `404` when unset |\n| anything else | `404` |\n\nConfiguration: `PORT` (default `3333`), `HOST` (default `127.0.0.1` — set `HOST=0.0.0.0` to expose it, and put HTTPS in front), `OPENAI_APPS_CHALLENGE_TOKEN` (the value OpenAI gives you when you submit the domain). CORS allows any origin. The usual `SKETCHFAB_API_KEY` / `TRIPO_API_KEY` / `RUNWARE_API_KEY` / `SCENEVIEW_TELEMETRY=0` knobs apply.\n\n**Everything is free, but not everything is remote.** Three generation tools (`render_3d_preview`, `create_3d_artifact`, `generate_scene`) need your own third-party credentials, which a shared anonymous endpoint cannot hold, so the remote surface omits them and refuses those names at call time with a clear `isError` message pointing at the local `npx sceneview-mcp` path. stdio lists and runs all 32.\n\n**Inline 3D viewer.** `view_3d_model` returns `structuredContent` plus `_meta.ui.resourceUri = ui://widget/3d-viewer.html`; the widget (SceneView.js + Filament.js, served by `resources/read` with the `text/html;profile=mcp-app` mime type and its `_meta.ui.csp`) renders the model inline in ChatGPT and any MCP Apps host.\n\nSmoke test with curl (the `Accept` header is required by the spec):\n\n```bash\ncurl -s http://127.0.0.1:3333/mcp \\\n  -H 'Content-Type: application/json' \\\n  -H 'Accept: application/json, text/event-stream' \\\n  -d '{\"jsonrpc\":\"2.0\",\"id\":1,\"method\":\"initialize\",\"params\":{\"protocolVersion\":\"2025-11-25\",\"capabilities\":{},\"clientInfo\":{\"name\":\"curl\",\"version\":\"0\"}}}'\n# {\"jsonrpc\":\"2.0\",\"id\":1,\"result\":{\"protocolVersion\":\"2025-11-25\",\"capabilities\":{\"resources\":{},\"tools\":{}},\"serverInfo\":{\"name\":\"sceneview-mcp\",\"version\":\"4.x.y\"}}}\n```\n\nPoint the ChatGPT connector / OpenAI `mcp` tool at `https://<your-host>/mcp`.\n\n**Already hosted.** You do not have to run it yourself to get a public URL: the same code is\ndeployed at `https://mcp.sceneview.dev/mcp` (`GET /health` answers `{\"status\":\"ok\"}`), which is\nwhat the [remote connector](#use-as-a-remote-connector) above points at. Self-host when you want\nyour own keys, your own rate limits, or `analyze_project` against a local checkout.\n\n---\n\n## What you get\n\nEvery tool is free and there is no API key. The three generation tools that talk to a\nthird-party service use *your* credentials; everything else works the moment the server starts.\n\n### Start here\n\nSix tools carry most of what assistants actually do with SceneView. If you read nothing else:\n\n| Tool | What it does | Ask your assistant |\n|---|---|---|\n| `validate_code` | Compile-checks generated Kotlin or Swift against the real public API — symbol existence, 30+ rules, did-you-mean suggestions — before it reaches you | *\"Check that this SceneView code actually compiles\"* |\n| `get_node_reference` | The exact signature, defaults and example for any of 48+ node types, instead of an invented one | *\"What are the parameters of ModelNode?\"* |\n| `list_samples` | Browse 38 scenarios by tag (`ar`, `3d`, `ios`, `animation`, `geometry`, …) | *\"What SceneView samples involve AR planes?\"* |\n| `get_sample` | Returns one of them complete and compilable, in Kotlin or Swift | *\"Give me the AR plane-placement sample in Kotlin\"* |\n| `get_setup` | Gradle and manifest setup for Android 3D or AR | *\"Set up SceneView in my Android app\"* |\n| `get_ar_setup` | Permissions, session options, plane detection, image tracking | *\"Add ARCore plane detection to this screen\"* |\n\n### Full tool reference\n\n#### Setup & integration\n\n| Tool | What it does |\n|---|---|\n| `get_setup` | Gradle + manifest setup for Android 3D or AR |\n| `get_ios_setup` | SPM dependency, Info.plist, SwiftUI for iOS / macOS / visionOS |\n| `get_web_setup` | Kotlin/JS + Filament.js (WASM) for browser-based 3D |\n| `get_ar_setup` | Permissions, session options, plane detection, image tracking |\n| `get_platform_setup` | Unified setup guide for any platform (Android, iOS, Web, Flutter, RN, Desktop, TV) |\n\n#### Code generation & migration\n\n| Tool | What it does |\n|---|---|\n| `get_sample` | Returns a complete, compilable code sample for any of 38 scenarios (Kotlin or Swift) |\n| `list_samples` | Browse all samples, filter by tag (`ar`, `3d`, `ios`, `animation`, `geometry`, ...) |\n| `validate_code` | Checks generated code against 30+ rules — including symbol existence against the real public API, with did-you-mean suggestions — before presenting it to the user |\n| `migrate_code` | Automatically migrates SceneView 2.x / 3.x code with detailed changelog |\n| `get_migration_guide` | Every breaking change with before/after code |\n\n#### API reference\n\n| Tool | What it does |\n|---|---|\n| `get_node_reference` | Full API reference for any of 48+ node types — exact signatures, defaults, examples |\n| `list_platforms` | Supported platforms with their status, renderer, and framework |\n| `get_platform_roadmap` | Multi-platform status and timeline |\n\n#### Guides\n\n`get_best_practices` · `get_animation_guide` · `get_gesture_guide` · `get_performance_tips` · `get_material_guide` · `get_collision_guide` · `get_model_optimization_guide` · `get_web_rendering_guide` · `get_troubleshooting` · `debug_issue`\n\n#### Discovery & analysis\n\n| Tool | What it does |\n|---|---|\n| `search_models` | Searches Sketchfab for free 3D models (BYOK — set `SKETCHFAB_API_KEY`) |\n| `generate_3d_model` | Generates a brand-new GLB from a text prompt or image via TRELLIS.2 on Runware or Tripo AI (BYOK — set `RUNWARE_API_KEY` or `TRIPO_API_KEY`) |\n| `analyze_project` | Scans a local SceneView project on disk — detects platform, extracts version, flags outdated deps and known anti-patterns |\n| `search_android_docs` | Searches Google's stock Android docs knowledge base (needs the `android` CLI on PATH) |\n| `fetch_android_doc` | Fetches a full Android docs entry by its `kb://...` URI (needs the `android` CLI on PATH) |\n\n#### Inline 3D viewer (MCP Apps widget)\n\n| Tool | What it does |\n|---|---|\n| `view_3d_model` | Renders a public GLB / glTF URL in an interactive SceneView.js + Filament.js viewer inline in ChatGPT and any MCP Apps host (orbit, auto-rotate). For an https model it adds an \"Open in AR on your phone\" action (an `ar.sceneview.dev/open` link to the 3D AR Model Viewer app, with a QR code on desktop). Returns `structuredContent` + `_meta.ui.resourceUri` |\n\n### 5 resources\n\n| Resource URI | What it provides |\n|---|---|\n| `sceneview://api` | Complete SceneView 4.x API reference (the full `llms.txt`) |\n| `sceneview://known-issues` | Live open issues from GitHub (cached 10 min) |\n| `examples://demo-with-settings` | DemoScaffold v2 pattern — full-screen scene + Material 3 bottom sheet |\n| `examples://sketchfab-streaming` | Streaming Sketchfab CC-BY models into a demo instead of bundling GLBs |\n| `ui://widget/3d-viewer.html` | The 3D viewer widget (`text/html;profile=mcp-app`) that `view_3d_model` renders into |\n\n---\n\n## `search_models` — find real 3D assets from the AI\n\nGenerated SceneView code is only useful if it points at an asset that actually exists. `search_models` queries Sketchfab's public search API and returns a shortlist with names, authors, licenses, thumbnails, triangle counts, and viewer/embed URLs that the assistant can drop straight into `rememberModelInstance(modelLoader, ...)` or embed as a live preview.\n\n**Bring your own key (BYOK).** SceneView never proxies the request — you keep the rate limit and the cost stays at zero. To set it up:\n\n1. Create a free account at [sketchfab.com/register](https://sketchfab.com/register)\n2. Copy your API token from [sketchfab.com/settings/password](https://sketchfab.com/settings/password)\n3. Set `SKETCHFAB_API_KEY` in your MCP client config:\n\n```json\n{\n  \"mcpServers\": {\n    \"sceneview\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"sceneview-mcp\"],\n      \"env\": { \"SKETCHFAB_API_KEY\": \"YOUR_TOKEN_HERE\" }\n    }\n  }\n}\n```\n\nCall it like `search_models({ query: \"red sports car\", category: \"cars-vehicles\", maxResults: 6 })`. If the key is missing, the tool returns a clear message explaining how to get one instead of failing silently.\n\n## `generate_3d_model` — create brand-new 3D assets from the AI\n\nWhen no existing model fits, `generate_3d_model` closes the other half of the asset loop: it generates a fresh GLB from a **text prompt** (text→3D) or a **source image** (image→3D), then returns a direct GLB download URL plus license/attribution metadata — ready for `rememberModelInstance(modelLoader, ...)` and AR placement.\n\nTwo providers, both bring-your-own-key:\n\n| `provider` | Key | Model | Approx. cost per model |\n|---|---|---|---|\n| `\"trellis\"` | `RUNWARE_API_KEY` ([my.runware.ai/keys](https://my.runware.ai/keys)) | Microsoft [TRELLIS.2](https://github.com/microsoft/TRELLIS.2) (MIT weights) on [Runware](https://runware.ai) — `fast` = 1024³, `hd` = 1536³ | ~$0.01–0.03, billed by compute time (November 2026) |\n| `\"tripo\"` | `TRIPO_API_KEY` ([platform.tripo3d.ai/api-keys](https://platform.tripo3d.ai/api-keys)) | [Tripo AI](https://www.tripo3d.ai) P1 / H3.1 | ~$0.10–0.41 (July 2026) |\n\nWithout `provider`, the tool uses Tripo when `TRIPO_API_KEY` is set, otherwise TRELLIS.2 when `RUNWARE_API_KEY` is set. TRELLIS.2 is image→3D only, so a text prompt first renders a single-object concept image with FLUX.1 [schnell] on the same Runware key (the result links it, and reports the total cost).\n\nTripo's two quality tiers:\n\n| `quality` | Tripo model | Topology | Latency | Approx. cost (July 2026) |\n|---|---|---|---|---|\n| `\"fast\"` (default) | P1 (`P1-20260311`) | low-poly, AR-ready | ~25–30 s | ~$0.10–0.25 of your credits |\n| `\"hd\"` | H3.1 (`v3.1-20260211`) | quad mesh, detailed geometry + textures | up to ~100 s | ~$0.41 of your credits |\n\n**Bring your own key (BYOK).** Exactly like `search_models`: SceneView never proxies the request or holds your key — generations are billed to **your** Runware or Tripo account. To set it up:\n\n1. Create an API key at [my.runware.ai/keys](https://my.runware.ai/keys) (TRELLIS.2) or [platform.tripo3d.ai/api-keys](https://platform.tripo3d.ai/api-keys) (Tripo, new accounts get free trial credits)\n2. Set `RUNWARE_API_KEY` or `TRIPO_API_KEY` in your MCP client config:\n\n```json\n{\n  \"mcpServers\": {\n    \"sceneview\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"sceneview-mcp\"],\n      \"env\": { \"RUNWARE_API_KEY\": \"YOUR_KEY_HERE\" }\n    }\n  }\n}\n```\n\nCall it like `generate_3d_model({ prompt: \"a low-poly cactus in a striped pot\" })` or `generate_3d_model({ imageUrl: \"https://example.com/chair.jpg\", quality: \"hd\", provider: \"trellis\" })`. Provide exactly one of `prompt` / `imageUrl`.\n\n**⚠️ The GLB download URL is temporary (Tripo: ~5 minutes)** — download the file immediately and self-host it (e.g. copy it into your app's `assets/models/`). The tool result repeats this warning. Missing key, task failures, rate limits, and poll timeouts (2 min fast / 4 min hd cap) all return clear, actionable messages instead of hanging or crashing.\n\n## `analyze_project` — local project scan\n\nBecause the MCP server runs on the user's machine, `analyze_project` can read their project files directly. Given a `path` (default: `process.cwd()`), it:\n\n- Detects the project type by looking for `build.gradle(.kts)` with `io.github.sceneview:sceneview` (Android), `Package.swift` with `SceneViewSwift` (iOS), or `package.json` with `sceneview-web` (Web).\n- Extracts the SceneView dependency version and compares it against the latest release known to this MCP build, flagging outdated projects.\n- Walks up to **30** source files (`.kt`, `.kts`, `.swift`, `.js`, `.ts`) and up to **500 KB** total, scanning for well-known anti-patterns: Filament/ModelLoader calls inside background coroutines, the `LightNode(...) { ... }` trailing-lambda bug, deprecated 2.x APIs (`ArSceneView`, `TransformableNode`, `PlacementNode`, `ViewRenderable`, `loadModelAsync`), and `com.google.ar.sceneform.*` imports.\n- Returns a structured `{ projectType, sceneViewVersion, latestVersion, isOutdated, warnings, suggestions }` report, plus a Markdown summary.\n\nThe tool is read-only, never writes to disk, and gracefully handles missing directories. Use it when the user asks \"is my project up to date?\" or as a quick sanity check before generating new code for an existing codebase.\n\n---\n\n## Examples\n\n### \"Build me an AR app\"\n\nThe assistant calls `get_ar_setup` + `get_sample(\"ar-model-viewer\")` and returns a complete, compilable Kotlin composable with all imports, Gradle dependencies, and manifest entries. Ready to paste into Android Studio.\n\n### \"Create a 3D model viewer for iOS\"\n\nThe assistant calls `get_ios_setup(\"3d\")` + `get_sample(\"ios-model-viewer\")` and returns Swift code with the SPM dependency, Info.plist entries, and a working SwiftUI view.\n\n### \"What parameters does LightNode accept?\"\n\nThe assistant calls `get_node_reference(\"LightNode\")` and returns the exact function signature, parameter types, defaults, and a usage example — including the critical detail that `apply` is a named parameter, not a trailing lambda.\n\n### \"Validate this code before I use it\"\n\nThe assistant calls `validate_code` with the generated snippet and checks it against 30+ rules: symbol existence against the real public API (unknown imports, made-up node types, nonexistent loader methods — each with did-you-mean suggestions), threading violations, null safety, API correctness, lifecycle issues, deprecated APIs. Problems are flagged with explanations before the code reaches the user.\n\n---\n\n## Why this exists\n\n**Without** this MCP server, AI assistants regularly:\n- Recommend deprecated **Sceneform** (abandoned 2021) instead of SceneView\n- Generate imperative **View-based** code instead of Jetpack Compose\n- Use **wrong API signatures** or outdated parameter names\n- Miss the `LightNode` named-parameter gotcha (`apply =` not trailing lambda)\n- Forget null-checks on `rememberModelInstance` (it returns `null` while loading)\n- Have no knowledge of SceneView's iOS/Swift API at all\n\n**With** this MCP server, AI assistants:\n- Always use the current SceneView 4.x API surface\n- Generate correct **Compose-native** 3D/AR code for Android\n- Generate correct **SwiftUI-native** code for iOS/macOS/visionOS\n- Know about all 48+ node types and their exact parameters\n- Validate code against 30+ rules before presenting it\n- Provide working, tested sample code for 38 scenarios\n\n---\n\n## Quality\n\nThe MCP server is tested with **2,015 unit tests** across 91 test files covering:\n\n- Every tool response (correct output, error handling, edge cases)\n- All 38 code samples (compilable structure, correct imports, no deprecated APIs)\n- Code validator rules (true positives and false-positive resistance)\n- Node reference parsing (all node types extracted correctly from `llms.txt`)\n- Resource responses (API reference, GitHub issues integration, the 3D viewer widget)\n- The Streamable HTTP surface end to end (initialize, the remote tools/list, widget resource, health, OpenAI challenge)\n\n```\n Test Files  91 passed (91)\n      Tests  2015 passed (2015)\n```\n\nAll tools work **fully offline** except `sceneview://known-issues` (GitHub API, cached 10 min), `search_models` (Sketchfab, BYOK), and `generate_3d_model` (Tripo AI, BYOK). Anonymous telemetry also makes a network call unless `SCENEVIEW_TELEMETRY=0` (see [below](#anonymous-telemetry)).\n\n---\n\n## Troubleshooting\n\n### \"MCP server not found\" or connection errors\n\n1. Ensure Node.js 18+ is installed: `node --version`\n2. Test manually: `npx sceneview-mcp` — should start without errors\n3. Restart your AI client after changing the MCP configuration\n\n### \"npx command not found\"\n\nInstall Node.js from [nodejs.org](https://nodejs.org/) (LTS recommended). npm and npx are included.\n\n### Server starts but tools are not available\n\n- **Claude Desktop:** check the MCP icon in the input bar — it should show \"sceneview\" as connected\n- **Cursor:** check **Settings > MCP** for green status\n- Restart the AI client to force a reconnect\n\n### Firewall or proxy issues\n\nThe only network calls are to the GitHub API (for known issues), Sketchfab (when `SKETCHFAB_API_KEY` is set), Tripo AI or Runware (when `TRIPO_API_KEY` / `RUNWARE_API_KEY` is set and `generate_3d_model` is called), and the anonymous telemetry endpoint (off with `SCENEVIEW_TELEMETRY=0`). Everything else works offline.\n\n```json\n{\n  \"mcpServers\": {\n    \"sceneview\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"sceneview-mcp\"],\n      \"env\": {\n        \"HTTPS_PROXY\": \"http://proxy.example.com:8080\"\n      }\n    }\n  }\n}\n```\n\n---\n\n## Sponsor\n\nIf sceneview-mcp saves you time, you can [sponsor SceneView on Open Collective](https://opencollective.com/sceneview), or through [GitHub Sponsors](https://github.com/sponsors/sceneview). Every tool is free with or without a contribution, and a sponsorship changes nothing in what the server returns. [How sponsorship works](https://sceneview.github.io/sponsors.html).\n\n---\n\n## Anonymous telemetry\n\nEnabled by default (MCP client name/version and tool names — no personal data, no prompt content). Opt out with `SCENEVIEW_TELEMETRY=0`. See [PRIVACY.md](./PRIVACY.md#telemetry) for the full payload shape.\n\n---\n\n## Development\n\n```bash\ncd mcp\nnpm install\nnpm run prepare  # Copy llms.txt + build TypeScript\nnpm test         # vitest suite\nnpm run lint     # Biome (repo-root biome.json) — lint + format + import assists\nnpm run lint:fix # same, applying the safe fixes\nnpm run dev      # Start with tsx (hot reload)\n```\n\n### Project structure\n\n```\nmcp/\n  src/\n    index.ts             # CLI entry point — stdio, or Streamable HTTP with --http\n    server.ts            # The MCP Server (resources + tools), shared by both transports\n    http.ts              # Streamable HTTP entrypoint (/mcp, /health, OpenAI challenge)\n    widgets.ts           # MCP Apps widget: ui://widget/3d-viewer.html (SceneView.js + Filament.js)\n    tools/handler.ts     # Tool dispatcher\n    surfaces.ts          # Which tools the anonymous remote surface serves\n    samples.ts           # 38 compilable code samples (Kotlin + Swift)\n    validator.ts         # Code validator (30+ rules)\n    node-reference.ts    # Node type parser\n    guides.ts            # Best practices, AR setup, roadmap, troubleshooting\n    migration.ts         # v2 -> v3 -> v4 migration guide\n    preview.ts           # 3D preview URL generator\n    artifact.ts          # HTML artifact generator (model-viewer, charts, product 360)\n    issues.ts            # GitHub issues fetcher (cached)\n    search-models.ts     # Sketchfab BYOK search\n    generate-model.ts    # Tripo BYOK text/image -> GLB generation\n    analyze-project.ts   # Local project scanner\n  llms.txt               # Bundled API reference (copied from repo root)\n```\n\n## Contributing\n\n1. Fork the repository\n2. Create a feature branch\n3. Add tests for new tools or rules\n4. Run `npm test` — all tests must pass\n5. Submit a pull request\n\nSee [CONTRIBUTING.md](../CONTRIBUTING.md) for the full guide.\n\n## Legal\n\n- [LICENSE](./LICENSE) — MIT License\n- [TERMS.md](./TERMS.md) — Terms of Service\n- [PRIVACY.md](./PRIVACY.md) — Privacy Policy\n","readmeFilename":"README.md"}