> ## Documentation Index
> Fetch the complete documentation index at: https://docs.komaa.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Installation
> Run deepgram-msteams-bridge and put a Deepgram Voice Agent (Nova STT + LLM + Aura TTS) on Microsoft Teams calls through StandIn.
[`@komaa/deepgram-msteams-bridge`](https://www.npmjs.com/package/@komaa/deepgram-msteams-bridge)
brings a **Deepgram Voice Agent** (Nova STT + your chosen LLM + Aura TTS, with turn-taking, all run
by Deepgram) onto a Microsoft Teams call. It is the Deepgram analogue of the
[ElevenLabs](/elevenlabs/installation), [LiveKit](/livekit/installation) and
[OpenAI](/openai/installation) bridges: it hosts the HMAC WebSocket that StandIn connects to, then
relays audio to and from a Deepgram Voice Agent session.
Like the other bridges, this is a **standalone Node service**, not a framework plugin. There is
also **no agent to configure in a dashboard**: the bridge configures each Voice Agent session
itself (STT model, LLM, voice, prompt, greeting, tools) from environment variables. Two variables
and it runs.
**Prefer Python?** The same bridge exists as a Python package:
[`deepgram-msteams-bridge` on PyPI](https://pypi.org/project/deepgram-msteams-bridge/)
(`pip install deepgram-msteams-bridge`), with its own
[docs site](https://komaa-com.github.io/deepgram-msteams-bridge-py/) and
[repo](https://github.com/komaa-com/deepgram-msteams-bridge-py). Same wire protocol, same
environment variables, same hardening - pick the runtime that fits your stack. This page follows
the Node package.
## How it works
The bridge opens **one Voice Agent WebSocket per call**
(`wss://agent.deepgram.com/v1/agent/converse`), waits for the server's `Welcome`, sends a `Settings`
message configuring the agent, and relays audio both ways. Audio is **copy-only**: the StandIn wire
is base64 PCM 16 kHz and the Voice Agent session is pinned to `linear16` at 16 kHz, so nothing is
resampled or re-encoded. Caller barge-in (`UserStartedSpeaking`) maps to a Teams-side flush, and
stale "ghost" audio is dropped so nothing plays after the caller cuts in.
The agent gets four built-in tools automatically (`end_call`, `look` for vision, `show_image`,
`express` for avatar emotion), and you can register **your own function tools** the bridge executes
in-process. See [Extending the agent's tools](https://komaa-com.github.io/deepgram-msteams-bridge/extending-tools/).
## Requirements
* **Node.js `>= 20`**.
* A **Deepgram API key** with Voice Agent access ([console.deepgram.com](https://console.deepgram.com/)).
* A **StandIn** subscription ([standin.komaa.com](https://standin.komaa.com), free package works) -
the hosted media bridge that joins the Teams call and connects to this service. See
[Architecture](/concepts/architecture).
* Your own **Microsoft Teams bot** connected to StandIn - the [Teams setup](/teams/overview) walks
through the Azure bot, the app package, and the upload. To try it without one, use the
[sandbox](/community).
## Run
Env-configured, no install step needed:
```bash theme={null}
DEEPGRAM_API_KEY=dg_... \
WORKER_SHARED_SECRET=... \
npx @komaa/deepgram-msteams-bridge
```
Optionally shape the agent (all have defaults):
```bash theme={null}
DEEPGRAM_PROMPT="You are Komaa's friendly receptionist. Keep replies short."
DEEPGRAM_GREETING="Hello! You've reached Komaa. How can I help?"
DEEPGRAM_SPEAK_MODEL=aura-2-thalia-en # Aura voice
DEEPGRAM_THINK_MODEL=gpt-4o-mini # LLM
```
Or add it to a project (`npm i @komaa/deepgram-msteams-bridge`) and embed it - see the
[library API](https://komaa-com.github.io/deepgram-msteams-bridge/library-api/) for the programmatic
surface, custom tools, and a custom vision hook.
The bridge binds its media WebSocket (default `ws://:8080/voice/msteams/stream`; StandIn
appends `/{callId}` per call).
**Third-party LLMs need an endpoint.** Deepgram-managed `open_ai` and `anthropic` work with just a
model name. Providers like `google`, `groq` or `aws_bedrock` additionally require
`DEEPGRAM_THINK_ENDPOINT_URL` (Deepgram dials it) - see the
[configuration reference](/deepgram/configuration).
## Expose the WebSocket (Agent voice URL)
StandIn connects to the bridge **from the internet**, so the port must be reachable - a public host
or a tunnel. With Tailscale Funnel:
```bash theme={null}
tailscale funnel --bg --https=8080 8080
```
Your **Agent voice URL** is then:
```
wss://..ts.net:8080/voice/msteams/stream
```
## Connect it to StandIn
Register that URL (with a **matching shared secret**) on your identity in the
[dashboard](https://standin.komaa.com/dashboard), or use the
[sandbox](https://standin.komaa.com/sandbox) to try it without your own Teams bot:
1. Set the identity's **Agent voice URL** to where the bridge listens.
2. Set `WORKER_SHARED_SECRET` to the **shared secret from pairing** - both sides must match exactly,
or the WebSocket handshake is rejected with `401`.
3. Place a Teams call (or join the sandbox meeting). StandIn joins, connects to the bridge, and your
Deepgram agent answers.
## Try the runnable example
The fastest way to understand the bridge is to run its example project - a minimal, working
embedding you can copy straight into your own repo.
Clone `examples/basic-bridge`, fill in two environment variables, expose the port, connect it to
StandIn, and place a call - with the vision hook and a custom `lookup_order` tool explained along
the way.
Next: the full [configuration reference](/deepgram/configuration) - every environment variable, the
call governor, vision, and BYO-LLM endpoints. Deep protocol and library docs live on the
[project site](https://komaa-com.github.io/deepgram-msteams-bridge/).
## Links