OpenAI Realtime API Voice Agent

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MODEL = \"gpt-realtime\";\nconst INSTRUCTIONS = `\n Tell me which person's favorite food is the most expensive?\n`;\n\n//const VOICE = \"cedar\"; //male tenor\n//const VOICE = \"marin\"; //female alto\n//const VOICE = \"alloy\"; //female contralto\nconst VOICE = \"ash\"; //male\tbaritone\n//const VOICE = \"ballad\";// male\ttenor\n//const VOICE = \"coral\";//female soprano\n//const VOICE = \"echo\"; //male tenor\n//const VOICE = \"fable\"; //female alto\n//const VOICE = \"onyx\";//male base\n//const VOICE = \"nova\";//female alto\n//const VOICE = \"sage\";//female soprano\n//const VOICE = \"shimmer\";//female contralto\n//const VOICE = \"verse\"; //male tenor\n\nconst OPENAI_API_KEY = Deno.env.get(\"OPENAI_API_KEY\");\nif (!OPENAI_API_KEY) {\n throw new Error(\"🔴 OpenAI API key not configured\");\n}\n\nexport function makeHeaders(contentType?: string) {\n const obj: Record = {\n Authorization: `Bearer ${OPENAI_API_KEY}`,\n };\n if (contentType) obj[\"Content-Type\"] = contentType;\n return obj;\n}\n\nexport function makeSession(mcpUrl?: string) {\n const session: any = {\n type: \"realtime\",\n model: MODEL,\n instructions: INSTRUCTIONS,\n audio: {\n input: { noise_reduction: { type: \"near_field\" } },\n output: { voice: VOICE },\n },\n };\n\n // Add MCP configuration if requested\n if (mcpUrl) {\n session.tools = [{\n type: \"mcp\",\n server_label: \"hello-mcp-demo\",\n server_url: mcpUrl,\n authorization: \"demo-token-12345\", // In production, use a secure token\n require_approval: \"never\",\n }];\n }\n\n return session;\n}","const MODEL = \"gpt-realtime\";\nconst INSTRUCTIONS = `\n Tell me which person's favorite food is the most expensive using the getFavoriteFood function\n`;\n\n//const VOICE = \"cedar\"; //male tenor\n//const VOICE = \"marin\"; //female alto\n//const VOICE = \"alloy\"; //female contralto\nconst VOICE = \"ash\"; //male\tbaritone\n//const VOICE = \"ballad\";// male\ttenor\n//const VOICE = \"coral\";//female soprano\n//const VOICE = \"echo\"; //male tenor\n//const VOICE = \"fable\"; //female alto\n//const VOICE = \"onyx\";//male base\n//const VOICE = \"nova\";//female alto\n//const VOICE = \"sage\";//female soprano\n//const VOICE = \"shimmer\";//female contralto\n//const VOICE = \"verse\"; //male tenor\n\nconst OPENAI_API_KEY = Deno.env.get(\"OPENAI_API_KEY\");\nif (!OPENAI_API_KEY) {\n throw new Error(\"🔴 OpenAI API key not configured\");\n}\n\nexport function makeHeaders(contentType?: string) {\n const obj: Record = {\n Authorization: `Bearer ${OPENAI_API_KEY}`,\n };\n if (contentType) obj[\"Content-Type\"] = contentType;\n return obj;\n}\n\nexport function makeSession(mcpUrl?: string) {\n const session: any = {\n type: \"realtime\",\n model: MODEL,\n instructions: INSTRUCTIONS,\n audio: {\n input: { noise_reduction: { type: \"near_field\" } },\n output: { voice: VOICE },\n },\n };\n\n // Add MCP configuration if requested\n if (mcpUrl) {\n session.tools = [{\n type: \"mcp\",\n server_label: 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{ Hono } from \"npm:hono\";\nimport { parseVal, serveFile } from \"https://esm.town/v/std/utils/index.ts\";\nimport mcp from \"./routes/mcp.ts\";\nimport rtc from \"./routes/rtc.ts\";\nimport sip from \"./routes/sip.ts\";\nimport observer from \"./routes/observer.ts\";\n\nconst SOURCE_URL = parseVal(Deno.env.get(\"VALTOWN_ENTRYPOINT\")).links.self.val;\n\nconst app = new Hono();\napp.route(\"/rtc\", rtc);\napp.route(\"/sip\", sip);\napp.route(\"/observer\", observer);\napp.route(\"/mcp\", mcp);\napp.get(\"/source\", (c) => c.redirect(SOURCE_URL));\n\napp.get(\"/\", () => serveFile(\"/frontend/index.html\"));\n\nexport default app.fetch;","label",[150],"2fe1a250-a230-11f0-bdde-0224a6c84d84","deno.json","0199b639-4047-7707-90b5-1856875494de",["D",1759698829309],"{\n \"$schema\": \"https://raw.githubusercontent.com/denoland/deno/348900b8b79f4a434cab4c74b3bc8d4d2fa8ee74/cli/schemas/config-file.v1.json\",\n \"lock\": false,\n \"compilerOptions\": {\n \"noImplicitAny\": false,\n \"strict\": false,\n \"types\": [\n \"https://www.val.town/types/valtown.d.ts\"\n ],\n \"lib\": [\n \"dom\",\n \"dom.iterable\",\n \"dom.asynciterable\",\n \"deno.ns\",\n \"deno.unstable\"\n ]\n },\n \"lint\": {\n \"files\": {\n \"include\": [\n \"deno:/https/esm.town/**/*\"\n ]\n },\n \"rules\": {\n \"exclude\": [\n \"no-explicit-any\"\n ]\n }\n },\n \"node_modules_dir\": false,\n \"experimental\": {\n \"unstable-node-globals\": true,\n \"unstable-temporal\": true,\n \"unstable-worker-options\": true,\n \"unstable-sloppy-imports\": true\n }\n}",[160],"2fe19ecc-a230-11f0-bdde-0224a6c84d84","README.md","0199b639-4047-7707-90b5-14c5c901dd1c",["D",1759698829309],"# hello-mcp\n\n**Hello MCP** is a remix of OpenAI's hello-realtime demo that adds Model Context Protocol (MCP) support for server-side tool execution.\n\nThis demo showcases:\n- WebRTC-based voice conversations with OpenAI's Realtime API\n- **MCP (Model Context Protocol)** for secure server-side tool execution\n- A demo `getFavoriteFood` tool to demonstrate MCP functionality\n- Toggle between standard and MCP-enabled modes\n\nIf you remix the app, you'll just need to pop in your own `OPENAI_API_KEY` (from\n[platform.openai.com](https://platform.openai.com)).\n\n## What's New: MCP Support\n\n### Model Context Protocol (MCP)\nMCP enables server-side tool execution, keeping your business logic and API keys secure on the server rather than exposing them to the client.\n\n### Demo Tool: getFavoriteFood\nTry asking questions like:\n- \"What's Thomas's favorite food?\"\n- \"What does Brian like to eat?\"\n- \"Tell me about Yana's favorite food\"\n\nThe tool knows about: Thomas, Brian, Emil, Yana, Alex, Max, Justin, and Sam.\n\n## Architecture\n\n1. **Standard WebRTC Flow**:\n - Browser connects to frontend\n - Creates WebRTC offer\n - `/rtc` endpoint handles SDP negotiation with OpenAI\n - Observer established to monitor session\n\n2. **MCP-Enhanced Flow** (when enabled):\n - Same WebRTC setup as above\n - OpenAI discovers tools via MCP protocol (`/mcp`)\n - Tools execute server-side when invoked\n - Results returned through MCP protocol\n - Client triggers response generation after tool completion\n\n## API Endpoints\n- `GET /` - serves the WebRTC-based app with MCP toggle\n- `POST /rtc` - creates a new WebRTC-based Realtime API session (with optional `?mcp=true`)\n- `POST /sip` - handles an incoming Realtime API SIP call\n- `POST /observer` - internal endpoint to establish a Realtime API websocket for session control\n- `POST /mcp` - MCP protocol endpoint for tool discovery and execution\n- `GET /mcp/tools` - Debug endpoint to list available tools\n\n## Project Structure\n```\n├── frontend/ \n│ └── index.html # HTML/JS application for WebRTC with MCP support\n├── main.tsx # Main entrypoint for the val.town app\n└── routes/\n |── mcp.ts # MCP protocol handler with getFavoriteFood tool\n |── observer.ts # Server-side session control for SIP & WebRTC\n |── rtc.ts # WebRTC session setup with MCP configuration\n |── sip.ts # SIP webhook handling and session setup\n └── utils.ts # Realtime API session configuration with MCP support\n```\n\n## How to Test MCP\n\n1. **Start the app** - Click \"Start\" and allow microphone access\n2. **Check MCP is enabled** - Ensure \"Use MCP Tools\" checkbox is checked\n3. **Ask about favorite foods** - Try \"What's Thomas's favorite food?\"\n4. **Watch the logs** - You'll see MCP events including tool discovery and execution\n5. **Try without MCP** - Uncheck the box and restart to see the difference\n\n## MCP Protocol Details\n\nThe MCP implementation follows the JSON-RPC 2.0 specification:\n\n### Initialize\n```json\n{\n \"method\": \"initialize\",\n \"params\": { \"protocolVersion\": \"2025-06-18\" }\n}\n```\n\n### Tools List\n```json\n{\n \"method\": \"tools/list\",\n \"result\": { \"tools\": [...] }\n}\n```\n\n### Tool Call\n```json\n{\n \"method\": \"tools/call\",\n \"params\": {\n \"name\": \"getFavoriteFood\",\n \"arguments\": { \"name\": \"Thomas\" }\n 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type: \"response.create\" })), 250);\n });\n ws.on(\"message\", (data /*, isBinary */) => {\n const message = JSON.parse(data);\n if (message.type !== \"response.output_audio_transcript.delta\") {\n console.log(message);\n }\n });\n ws.on(\"error\", (err: Error) => {\n console.error(`🔴 websocket failed: ${err.message}`);\n });\n\n // Respond immediately; WS continues in background\n return c.newResponse(null);\n});\n\nexport default observer;",[],[178,243],"2fe1904e-a230-11f0-bdde-0224a6c84d84","mcp.ts","0199b639-4047-7707-90b4-facc63a14594",["D",1759698829309],"import { Hono } from \"npm:hono\";\nimport { StreamableHTTPTransport } from \"npm:@hono/mcp\";\nimport { McpServer } from \"npm:@modelcontextprotocol/sdk/server/mcp.js\";\nimport { z } from \"npm:zod\";\n\nconst mcp = new Hono();\nconst server = new McpServer({ name: \"hello-mcp\", version: \"1.0.0\" });\n\n// MCP entrypoint over HTTP.\nmcp.all(\"/\", async (c) => {\n const transport = new StreamableHTTPTransport();\n await server.connect(transport);\n return transport.handleRequest(c);\n});\n\nfunction makeJsonResponse(data: any) {\n return { content: [{ type: \"json\", data }] };\n}\n\nfunction makeErrorResponse(message: string) {\n return { content: [{ type: \"text\", text: message }], isError: true };\n}\n\nfunction wrap(fn: Function, args: any) {\n try {\n return makeJsonResponse(fn(args));\n } catch (e) {\n return makeErrorResponse(e.message);\n }\n}\n\n// ----- Demo tool -----\nserver.tool(\n \"getFavoriteFood\",\n \"Returns the favorite food for specific people\",\n z.object({\n name: z.string().describe(\"The person's name to look up\"),\n }),\n (x) => wrap(getFavoriteFood, x),\n);\n\nconst favoriteFoods: Record = {\n thomas: \"alsacian choucroute\",\n brian: \"trail mix\",\n emil: \"nutella\",\n yana: \"french macarons\",\n alex: \"brownies\",\n max: \"feta cheese\",\n justin: \"sushi\",\n sam: \"pizza\",\n};\n\nfunction getFavoriteFood({ name }: { name: string }) {\n const favoriteFood = 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I know about: ${knownFoods}.`;\n throw new Error(message);\n }\n\n return { favoriteFood };\n}\n\nexport default mcp;",[],[178,250],["D",1759698829309],[201,202,203,204,205],[178],"2fe172da-a230-11f0-bdde-0224a6c84d84","index.html","0199b639-4046-74cd-b93b-9bddbcd462b3",["D",1759698829309],"\n\n \n \n \n OpenAI Realtime API Voice Agent\n \n \n \n \n\n

\n\n

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Realtime Agent with MCP

Diff · v3