feat(mcp,editor): Option A+B storage + 10 agent deliverables (Phase 7)
Ships the combined filesystem/Supabase storage adapter + MCP scene lifecycle tools + Next.js API routes + editor /scene/[id] route, so an MCP save is directly openable at /scene/<id> without any injection hack. End-to-end verified: 10/10 e2e steps pass. Storage (A1/A2/A3): - SceneStore interface + error classes + slug helpers - FilesystemSceneStore at $PASCAL_DATA_DIR (defaults XDG/~/.pascal) with atomic writes, .index sidecar, optimistic locking - SupabaseSceneStore with scenes + scene_revisions tables, RLS migration SQL, mock-backed unit tests - createSceneStore(env) auto-selects based on SUPABASE_URL + SUPABASE_SERVICE_ROLE_KEY MCP tools (A4, A8, A9, A10): - save_scene / load_scene / list_scenes / delete_scene / rename_scene - list_templates / create_from_template (3 seed templates: empty-studio, two-bedroom, garden-house) - generate_variants (7 mutation kinds, seeded RNG, save=true|false) - photo_to_scene (vision sampling → scene graph → save) Editor (A5, A6): - /api/scenes + /api/scenes/[id] with RFC 7232 If-Match locking - /scene/[id] and /scenes route pages with save button, SceneLoader - Removed the window.__pascalScene dev injection hack Security + UX edges (A7, A8): - AssetUrl Zod validator: asset:// blob: data:image/ /path https: (http://localhost for dev) + PASCAL_ALLOWED_ASSET_ORIGINS env allowlist. Hardens scan.url, guide.url, item.asset.src, material.texture.url, MaterialMaps.*Map - Auto-frame camera on empty→non-empty scene transition (camera-controls:fit-scene emitter event) Shared utilities: - rehydrateSiteChildren() extracted to packages/mcp/src/lib/ and used by both create-from-template and generate-variants to work around the SiteNode.children-as-objects vs. ids inconsistency (CROSS_CUTTING §2) - Storage + MCP subpath exports added to packages/mcp/package.json (CROSS_CUTTING §4) Tests: 293 pass / 0 fail across 40 files (was 142 pre-Phase-7). Biome: clean. Phase-7 e2e script at packages/mcp/test-reports/phase7-e2e.ts: MCP HTTP + editor Next.js both point at $PASCAL_DATA_DIR = /tmp/pascal-e2e, save_scene from MCP, GET /api/scenes/<id> from editor server, /scenes list page renders all saved scenes, scene page renders SceneLoader, delete_scene works. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
Adrian Perez
co-authored by
Claude Opus 4.7
Claude Opus 4.7
parent
42bd05db9c
commit
e8d0b13ff5
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import type { McpServer } from '@modelcontextprotocol/sdk/server/mcp.js'
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import { ErrorCode, McpError } from '@modelcontextprotocol/sdk/types.js'
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import type { SceneGraph } from '@pascal-app/core/clone-scene-graph'
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import type { AnyNodeId, AnyNode as AnyNodeT } from '@pascal-app/core/schema'
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import {
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AnyNode,
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BuildingNode,
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LevelNode,
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SiteNode,
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WallNode,
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ZoneNode,
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} from '@pascal-app/core/schema'
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import { z } from 'zod'
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import type { SceneBridge } from '../../bridge/scene-bridge'
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import type { SceneStore } from '../../storage/types'
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/**
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* Input shape for the `photo_to_scene` orchestrator. `image` matches the
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* contract documented on `analyze_floorplan_image` — base64 or http(s) URL.
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*/
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export const photoToSceneInput = {
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image: z.string().describe('Base64 or https URL of the floor-plan photo'),
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scaleHint: z.string().optional().describe('e.g. "1 cm = 1 m" or "approx 80 m²"'),
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name: z.string().default('Scene from photo'),
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save: z.boolean().default(true),
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defaultWallThickness: z.number().default(0.2),
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defaultWallHeight: z.number().default(2.6),
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}
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export const photoToSceneOutput = {
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sceneId: z.string().optional(),
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url: z.string().optional(),
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walls: z.number(),
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rooms: z.number(),
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confidence: z.number(),
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notes: z.string().optional(),
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graph: z.any().optional(),
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}
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/**
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* Shape of the vision JSON we consume. Kept in-sync with
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* `analyze_floorplan_image`'s output schema (walls / rooms /
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* approximateDimensions / confidence).
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*/
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const VisionResponseSchema = z.object({
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walls: z.array(
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z.object({
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start: z.tuple([z.number(), z.number()]),
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end: z.tuple([z.number(), z.number()]),
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thickness: z.number().optional(),
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}),
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),
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rooms: z.array(
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z.object({
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name: z.string(),
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polygon: z.array(z.tuple([z.number(), z.number()])),
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approximateAreaSqM: z.number().optional(),
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}),
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),
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approximateDimensions: z.object({
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widthM: z.number(),
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depthM: z.number(),
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}),
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confidence: z.number().min(0).max(1),
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})
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type VisionResponse = z.infer<typeof VisionResponseSchema>
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/**
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* System prompt mirrors `analyze_floorplan_image` — the contract between
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* orchestrator and host is identical, so we keep the prompt verbatim to
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* guarantee wire-compatible responses.
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*/
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const SYSTEM_PROMPT = `You are a vision assistant that extracts structured floor-plan data from an image.
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Your ONLY job: return a JSON object that exactly matches this schema — no prose, no markdown fences.
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{
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"walls": [{ "start": [x, z], "end": [x, z], "thickness": number? }, ...],
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"rooms": [{ "name": string, "polygon": [[x,z], ...], "approximateAreaSqM": number? }, ...],
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"approximateDimensions": { "widthM": number, "depthM": number },
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"confidence": number 0..1
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}
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Coordinates are in metres. Origin can be the floor plan's centre or bottom-left — be consistent.
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If the image is unclear, lower the confidence score but still produce your best attempt.
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DO NOT wrap the JSON in markdown. DO NOT explain. Just output the raw JSON.`
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const DATA_URI_RE = /^data:(image\/[a-z0-9.+-]+);base64,(.+)$/i
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type ImageBlock = {
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type: 'image'
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data: string
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mimeType: string
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}
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/**
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* Resolve the `image` input into a sampling-ready image block. Follows the
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* same fetch/data-uri/raw-base64 rules as the vision tool so the user gets
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* consistent behaviour whether they call `photo_to_scene` or
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* `analyze_floorplan_image` directly.
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*/
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async function resolveImageBlock(image: string): Promise<ImageBlock> {
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if (/^https?:\/\//i.test(image)) {
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const res = await fetch(image)
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if (!res.ok) {
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throw new McpError(
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ErrorCode.InvalidParams,
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`failed to fetch image: ${res.status} ${res.statusText}`,
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{ url: image, status: res.status },
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)
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}
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const buf = Buffer.from(await res.arrayBuffer())
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const data = buf.toString('base64')
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const mimeType = res.headers.get('content-type') ?? 'image/jpeg'
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return { type: 'image', data, mimeType }
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}
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const dataUriMatch = image.match(DATA_URI_RE)
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if (dataUriMatch) {
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return {
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type: 'image',
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mimeType: dataUriMatch[1]!,
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data: dataUriMatch[2]!,
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}
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}
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return { type: 'image', mimeType: 'image/jpeg', data: image }
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}
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/** Collect all text content blocks returned by the sampling host into one string. */
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function extractText(
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content:
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| { type: 'text'; text: string }
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| { type: 'image' | 'audio'; data: string; mimeType: string }
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| Array<
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| { type: 'text'; text: string }
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| { type: 'image' | 'audio'; data: string; mimeType: string }
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| { type: string; [k: string]: unknown }
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>,
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): string {
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const blocks = Array.isArray(content) ? content : [content]
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const texts: string[] = []
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for (const block of blocks) {
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if (block && typeof block === 'object' && (block as { type?: string }).type === 'text') {
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const t = (block as { text?: unknown }).text
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if (typeof t === 'string') texts.push(t)
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}
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}
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return texts.join('\n').trim()
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}
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/**
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* Call the host's sampling capability to analyse a floor-plan photo. Throws
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* `sampling_unavailable` when the host has not advertised the capability and
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* `sampling_response_unparseable` / `sampling_response_invalid` when the
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* reply cannot be mapped onto `VisionResponseSchema`.
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*/
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async function callVisionSampling(
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server: McpServer,
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image: string,
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scaleHint: string | undefined,
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): Promise<VisionResponse> {
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const caps = server.server.getClientCapabilities()
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if (!caps?.sampling) {
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throw new McpError(ErrorCode.InvalidRequest, 'sampling_unavailable')
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}
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const imageBlock = await resolveImageBlock(image)
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const instruction = scaleHint
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? `Analyze this floor plan. Scale hint: ${scaleHint}. Return ONLY the JSON described by the system prompt.`
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: 'Analyze this floor plan. Return ONLY the JSON described by the system prompt.'
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const response = await server.server.createMessage({
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systemPrompt: SYSTEM_PROMPT,
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temperature: 0,
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maxTokens: 2000,
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messages: [
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{
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role: 'user',
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content: [imageBlock, { type: 'text', text: instruction }],
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},
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],
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})
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const text = extractText(response.content as Parameters<typeof extractText>[0])
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if (!text) {
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throw new McpError(ErrorCode.InternalError, 'sampling_response_unparseable', {
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reason: 'no text content returned by host',
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})
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}
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let parsed: unknown
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try {
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parsed = JSON.parse(text)
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} catch (err) {
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throw new McpError(ErrorCode.InternalError, 'sampling_response_unparseable', {
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raw: text,
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reason: err instanceof Error ? err.message : String(err),
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})
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}
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const validation = VisionResponseSchema.safeParse(parsed)
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if (!validation.success) {
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throw new McpError(ErrorCode.InternalError, 'sampling_response_invalid', {
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raw: text,
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errors: validation.error.issues,
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})
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}
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return validation.data
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}
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type BuildResult = {
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nodes: Record<AnyNodeId, AnyNodeT>
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rootNodeIds: AnyNodeId[]
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walls: number
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rooms: number
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warnings: string[]
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levelId: AnyNodeId
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}
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/**
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* Build a SceneGraph (flat `nodes` dict + `rootNodeIds`) from the vision
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* response. Uses the schema factories for every node so IDs, defaults, and
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* parent linkage match what the core store would produce. Each node is
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* revalidated via `AnyNode.safeParse`; failures are dropped with a warning.
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*/
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function buildSceneGraphFromVision(
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vision: VisionResponse,
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defaultWallThickness: number,
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defaultWallHeight: number,
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): BuildResult {
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const warnings: string[] = []
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// Build the skeleton: site → building → level.
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const building = BuildingNode.parse({})
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const level = LevelNode.parse({ level: 0 })
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const site = SiteNode.parse({ children: [building] })
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// Link parent ids so downstream traversal works.
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const siteId = site.id as AnyNodeId
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const buildingId = building.id as AnyNodeId
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const levelId = level.id as AnyNodeId
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const linkedBuilding: AnyNodeT = {
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...(building as AnyNodeT),
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parentId: siteId,
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}
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const linkedLevel: AnyNodeT = {
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...(level as AnyNodeT),
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parentId: buildingId,
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}
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// BuildingNode children stores level ids (string[]).
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;(linkedBuilding as BuildingNode).children = [levelId as BuildingNode['children'][number]]
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// Collect level children (ids of walls/zones we create below).
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const levelChildren: string[] = []
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const nodes: Record<AnyNodeId, AnyNodeT> = {}
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// Validate + add site, building, level in that order.
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const siteValidated = AnyNode.safeParse(site)
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if (!siteValidated.success) {
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warnings.push(`site node failed schema validation: ${siteValidated.error.message}`)
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}
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nodes[siteId] = (siteValidated.success ? siteValidated.data : site) as AnyNodeT
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const buildingValidated = AnyNode.safeParse(linkedBuilding)
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if (!buildingValidated.success) {
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warnings.push(`building node failed schema validation: ${buildingValidated.error.message}`)
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}
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nodes[buildingId] = (
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buildingValidated.success ? buildingValidated.data : linkedBuilding
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) as AnyNodeT
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// Walls.
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let wallsAdded = 0
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for (let i = 0; i < vision.walls.length; i++) {
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const w = vision.walls[i]!
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try {
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const wall = WallNode.parse({
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start: w.start,
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end: w.end,
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thickness: w.thickness ?? defaultWallThickness,
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height: defaultWallHeight,
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})
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const linkedWall: AnyNodeT = {
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...(wall as AnyNodeT),
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parentId: levelId,
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}
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const validated = AnyNode.safeParse(linkedWall)
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if (!validated.success) {
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warnings.push(`wall[${i}] dropped: ${validated.error.message}`)
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continue
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}
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nodes[wall.id as AnyNodeId] = validated.data as AnyNodeT
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levelChildren.push(wall.id)
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wallsAdded++
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} catch (err) {
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const msg = err instanceof Error ? err.message : String(err)
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warnings.push(`wall[${i}] dropped: ${msg}`)
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}
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}
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// Rooms → zones.
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let roomsAdded = 0
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for (let i = 0; i < vision.rooms.length; i++) {
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const r = vision.rooms[i]!
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try {
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const zone = ZoneNode.parse({
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name: r.name,
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polygon: r.polygon,
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})
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const linkedZone: AnyNodeT = {
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...(zone as AnyNodeT),
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parentId: levelId,
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}
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const validated = AnyNode.safeParse(linkedZone)
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if (!validated.success) {
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warnings.push(`room[${i}] dropped: ${validated.error.message}`)
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continue
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}
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nodes[zone.id as AnyNodeId] = validated.data as AnyNodeT
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levelChildren.push(zone.id)
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roomsAdded++
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} catch (err) {
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const msg = err instanceof Error ? err.message : String(err)
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warnings.push(`room[${i}] dropped: ${msg}`)
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}
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}
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// Finalise the level's children array now that walls/zones are in the dict.
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;(linkedLevel as LevelNode).children = levelChildren as LevelNode['children']
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const levelValidated = AnyNode.safeParse(linkedLevel)
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if (!levelValidated.success) {
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warnings.push(`level node failed schema validation: ${levelValidated.error.message}`)
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}
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nodes[levelId] = (levelValidated.success ? levelValidated.data : linkedLevel) as AnyNodeT
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return {
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nodes,
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rootNodeIds: [siteId],
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walls: wallsAdded,
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rooms: roomsAdded,
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warnings,
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levelId,
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}
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}
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export function registerPhotoToScene(
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server: McpServer,
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bridge: SceneBridge,
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store: SceneStore,
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): void {
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server.registerTool(
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'photo_to_scene',
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{
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title: 'Photo to Pascal scene',
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description:
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'Orchestrator: analyse a floor-plan photo via MCP sampling, translate the structured vision result into a Pascal SceneGraph (site → building → level with walls and zones), optionally save it, and swap the bridge to the new scene. Requires host support for sampling.',
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inputSchema: photoToSceneInput,
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outputSchema: photoToSceneOutput,
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},
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async ({ image, scaleHint, name, save, defaultWallThickness, defaultWallHeight }) => {
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// 1. Vision.
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const vision = await callVisionSampling(server, image, scaleHint)
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// 2. Build scene graph.
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const built = buildSceneGraphFromVision(vision, defaultWallThickness, defaultWallHeight)
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const graph: SceneGraph = {
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nodes: built.nodes as SceneGraph['nodes'],
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rootNodeIds: built.rootNodeIds as SceneGraph['rootNodeIds'],
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collections: {} as SceneGraph['collections'],
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}
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// 5. Swap the bridge to the new scene so follow-up MCP calls operate on it.
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bridge.setScene(graph.nodes, graph.rootNodeIds)
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const notes = built.warnings.length > 0 ? built.warnings.join('; ') : undefined
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// 4. Save or return inline.
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if (save) {
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const meta = await store.save({
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name,
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graph,
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})
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const payload: {
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sceneId: string
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url: string
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walls: number
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rooms: number
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confidence: number
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notes?: string
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} = {
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sceneId: meta.id,
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url: `/scene/${meta.id}`,
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walls: built.walls,
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rooms: built.rooms,
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confidence: vision.confidence,
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}
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if (notes) payload.notes = notes
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return {
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content: [{ type: 'text' as const, text: JSON.stringify(payload) }],
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structuredContent: payload,
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}
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}
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const payload: {
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walls: number
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rooms: number
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confidence: number
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notes?: string
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graph: SceneGraph
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} = {
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walls: built.walls,
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rooms: built.rooms,
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confidence: vision.confidence,
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graph,
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}
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if (notes) payload.notes = notes
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return {
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content: [{ type: 'text' as const, text: JSON.stringify(payload) }],
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structuredContent: payload,
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}
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},
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)
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}
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Reference in New Issue
Block a user