Example

mcp-event added into calender

mcp-labrat

Voice + MCP calendar demo.

This project is a small Express app that:

• Hosts an MCP server (Streamable HTTP transport) that exposes calendar tools backed by a CalDAV server
• Hosts an HTTP “MCP client” endpoint that sends a prompt to an OpenAI-compatible Chat Completions API and lets the model call those MCP tools
• Serves a simple browser UI (in public/) that records audio, transcribes it (Whisper API), and sends the resulting prompt to the MCP client endpoint

Requirements

• Node.js 18+ (Node 20+ recommended)
• A CalDAV server + credentials (or accept the defaults, but tools won’t be useful)
• An OpenAI-compatible API endpoint for:
  • Chat Completions (/v1/chat/completions)
  • Audio Transcriptions (/v1/audio/transcriptions)

In this lab, OPENAI_PROXY_URL typically points to a proxy service (not OpenAI directly). The proxy is responsible for adding any required authentication (e.g. API keys) to outgoing requests.

Because auth is handled by the proxy, the server uses direct HTTP requests (via fetchData) instead of the official OpenAI SDK.

Quick start

1. Install

   npm install
   

2. Create .env

   cp .env-sample .env
   

   Then edit .env and set OPENAI_PROXY_URL to your proxy/base URL (e.g. http://localhost:1234 or your deployed proxy).

3. Run the dev server

   npm run dev
   

4. Open the demo UI

   • Visit http://localhost:3000/
   • Click “Start Recording”, speak a command, then click “Stop Recording”
   • Click “Send”

Environment variables

Create a .env file in the project root.

Server

• PORT (optional, default: 3000)
• NODE_ENV (optional, e.g. development)

MCP client + OpenAI-compatible API

• MCP_SERVER_URL (required)
  • Example: http://localhost:3000/api/v1/mcp
  • This can point back to the same server instance.
• OPENAI_PROXY_URL (required)
  • Base URL of your OpenAI-compatible proxy (the app calls /v1/chat/completions and /v1/audio/transcriptions under it)
  • Example: http://localhost:1234
• OPENAI_MODEL (optional, default: gpt-4o)

Audio transcription (Whisper)

• OPENAI_TRANSCRIPTION_MODEL (optional, default: whisper-1)

CalDAV (calendar backing store)

• CALDAV_SERVER_URL (optional, default: http://localhost:5232/)
• CALDAV_USERNAME (optional, default: username)
• CALDAV_PASSWORD (optional, default: password)

Radicale (dev CalDAV server)

For local development you can run a minimal Radicale CalDAV server with no authentication.

macOS / Linux

1. Install Radicale

python3 -m pip install --user radicale

1. Create a local config + data folder

mkdir -p radicale-data/collections
cat > radicale.config <<'EOF'
[server]
hosts = 127.0.0.1:5232

[auth]
type = none

[storage]
filesystem_folder = ./radicale-data/collections
EOF

1. Run Radicale

radicale --config ./radicale.config

Windows (PowerShell)

1. Install Radicale

py -m pip install --user radicale

1. Create a local config + data folder

New-Item -ItemType Directory -Force -Path .\radicale-data\collections | Out-Null
@'
[server]
hosts = 127.0.0.1:5232

[auth]
type = none

[storage]
filesystem_folder = ./radicale-data/collections
'@ | Set-Content -Encoding UTF8 .\radicale.config

1. Run Radicale

py -m radicale --config .\radicale.config

1. Point this app to Radicale

In .env:

• CALDAV_SERVER_URL=http://localhost:5232/
• CALDAV_USERNAME=anything (ignored when auth=none)
• CALDAV_PASSWORD=anything (ignored when auth=none)

Scripts

• npm run dev – run server with nodemon + ts-node
• npm run build – compile TypeScript to dist/
• npm start – run the compiled server (dist/index.js)

API

Base path is /api/v1.

Health

GET /api/v1/

Returns a simple JSON message.

MCP server

POST /api/v1/mcp

Implements the MCP Streamable HTTP transport.

MCP client

POST /api/v1/client

Accepts either:

1. JSON (text prompt)

curl -sS \
 -H 'Content-Type: application/json' \
 -d '{"prompt":"List my events","timezone":"Europe/Helsinki"}' \
 http://localhost:3000/api/v1/client

1. multipart/form-data (audio upload)

The field name must be audio.

curl -sS \
 -F '[email protected]' \
 -F 'timezone=Europe/Helsinki' \
 http://localhost:3000/api/v1/client

Response:

{
  "answer": "...",
  "toolCalls": 2
}

MCP tools

The MCP server currently exposes:

• listEvents – list events in the primary CalDAV calendar
• getEventsInTimeSlot – check availability for a time slot (relative date inputs)
• createEvent – create an event (relative date inputs + title + optional description/location)

The MCP client instructs the model to use tools for all user requests and applies some workflow rules (e.g., check availability before creating events when the user asks “if the time is free”).

Troubleshooting

• Mic permission: The browser will prompt for microphone access the first time. If recording fails, check site permissions.
• CalDAV auth: If the calendar tools always return empty results, verify CALDAV_* values and that your user has at least one calendar.
• Proxy URL: OPENAI_PROXY_URL must be the base URL; the app calls /v1/chat/completions and /v1/audio/transcriptions under it.
• Uploads cleanup: Uploaded audio is deleted best-effort after transcription; check filesystem permissions if uploads/ grows unexpectedly.

---

API doc: POST /api/v1/client

Runs a user prompt through the MCP client. The server will call an OpenAI-compatible Chat Completions API, and the model can invoke MCP calendar tools (via the MCP server URL).

Request

Supported content types:

1. application/json (text prompt)

• prompt (string, required) – the user command/question
• timezone (string, optional) – IANA timezone name (defaults to the server’s default timezone). See: List of tz database time zones

JSON request body example:

{
  "prompt": "List my events",
  "timezone": "Europe/Helsinki"
}

Example:

curl -sS \
  -H 'Content-Type: application/json' \
  -d '{"prompt":"List my events","timezone":"Europe/Helsinki"}' \
  http://localhost:3000/api/v1/client

Option 2: multipart/form-data (audio)

• audio (file, required) – audio file to transcribe (browser demo sends audio/webm)
• timezone (string, optional) – IANA timezone name

In this mode the server transcribes the audio first and uses the transcription text as the prompt.

Example:

curl -sS \
  -F '[email protected]' \
  -F 'timezone=Europe/Helsinki' \
  http://localhost:3000/api/v1/client

Response

On success (HTTP 200):

{
  "answer": "...",
  "toolCalls": 2
}

• answer (string) – final assistant output
• toolCalls (number) – total number of tool calls made during the run

Errors

• 400 – invalid request body (e.g., missing prompt in JSON, invalid timezone)
• 500 – transcription failures, OpenAI/MCP errors, or unexpected server errors

Errors are returned as JSON:

{
  "message": "..."
}

mc