docs(mcp): add README, examples, and changelog

- README.md: install/quick start; configs for Claude Desktop, Claude
  Code, and Cursor; programmatic usage; tables covering all 21 tools,
  4 resources, and 3 prompts; limitations; development commands.
- CHANGELOG.md: 0.1.0 entry in Keep a Changelog format.
- examples/generate-apartment.md: prose transcript using from_brief
  to build an 80 m² 2-bed apartment, showing apply_patch, set_zone,
  cut_opening, validate_scene.
- examples/renovate-from-photos.md: prose transcript using the vision
  tools + renovation_from_photos prompt.
- examples/embed-in-agent.ts: compilable TypeScript showing
  programmatic usage via InMemoryTransport.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

packages/mcp/examples/embed-in-agent.ts

@@ -0,0 +1,82 @@
+/**
+ * Programmatic `@pascal-app/mcp` usage.
+ *
+ * Runs a full MCP client/server pair over the in-memory transport inside a
+ * single Node process. Useful for agent frameworks and tests that want to
+ * drive Pascal without spawning a subprocess.
+ *
+ * Compile with the package's `tsc --build`, or run directly with Bun:
+ *
+ *   bun run packages/mcp/examples/embed-in-agent.ts
+ */
+
+import { Client } from '@modelcontextprotocol/sdk/client/index.js'
+import { InMemoryTransport } from '@modelcontextprotocol/sdk/inMemory.js'
+import { createPascalMcpServer, SceneBridge } from '@pascal-app/mcp'
+
+async function main(): Promise<void> {
+  // 1. Spin up the headless bridge. `loadDefault()` seeds a Site → Building →
+  //    Level stack so the client has something to query immediately.
+  const bridge = new SceneBridge()
+  bridge.loadDefault()
+  const server = createPascalMcpServer({ bridge })
+
+  // 2. Link the server to an in-memory client. Exactly the same API surface
+  //    as the stdio / HTTP transports, but without any process boundary.
+  const [srvT, cliT] = InMemoryTransport.createLinkedPair()
+  const client = new Client({ name: 'my-agent', version: '0.1.0' })
+  await Promise.all([server.connect(srvT), client.connect(cliT)])
+
+  // 3. Discover available capabilities.
+  const tools = await client.listTools()
+  console.log(
+    'available tools:',
+    tools.tools.map((t) => t.name),
+  )
+
+  // 4. Inspect the current scene.
+  const scene = await client.callTool({ name: 'get_scene', arguments: {} })
+  console.log('scene snapshot:', JSON.stringify(scene, null, 2))
+
+  // 5. Find the default level, create a 5 m wall, and undo it.
+  const levels = await client.callTool({
+    name: 'find_nodes',
+    arguments: { type: 'level' },
+  })
+  const levelId = (levels.structuredContent as { nodes: Array<{ id: string }> }).nodes[0]?.id
+
+  if (levelId) {
+    const created = await client.callTool({
+      name: 'create_wall',
+      arguments: {
+        levelId,
+        start: [0, 0],
+        end: [5, 0],
+        thickness: 0.2,
+        height: 2.5,
+      },
+    })
+    console.log('created wall:', created.structuredContent)
+
+    const undone = await client.callTool({ name: 'undo', arguments: { steps: 1 } })
+    console.log('undone:', undone.structuredContent)
+  }
+
+  // 6. Validate and export.
+  const validation = await client.callTool({ name: 'validate_scene', arguments: {} })
+  console.log('validation:', validation.structuredContent)
+
+  const exported = await client.callTool({
+    name: 'export_json',
+    arguments: { pretty: true },
+  })
+  console.log('export size:', (exported.structuredContent as { json: string }).json.length)
+
+  await client.close()
+  await server.close()
+}
+
+main().catch((err) => {
+  console.error(err)
+  process.exit(1)
+})