Deployment¶
Deployment Options¶
audio-transcriber exposes its MCP server (console script audio-transcriber-mcp) four ways. Pick the row that
matches where the server runs relative to your MCP client, then copy the matching
mcp_config.json below. Replace the <your-…> placeholders with the values from the Configuration / Environment Variables section.
| # | Option | Transport | Where it runs | mcp_config.json key |
|---|---|---|---|---|
| 1 | stdio | stdio |
client launches a subprocess | command |
| 2 | Streamable-HTTP (local) | streamable-http |
a local network port | command or url |
| 3 | Local container / uv | stdio or streamable-http |
Docker / Podman / uv on this host | command or url |
| 4 | Remote URL | streamable-http |
a remote host behind Caddy | url |
1. stdio (local subprocess)¶
The client launches the server over stdio via uvx — best for local IDEs
(Cursor, Claude Desktop, VS Code):
{
"mcpServers": {
"audio-transcriber-mcp": {
"command": "uvx",
"args": ["--from", "audio-transcriber", "audio-transcriber-mcp"],
"env": {
"AUDIO_TRANSCRIPTOR_API_KEY": "<your-audio_transcriptor_api_key>"
}
}
}
}
2. Streamable-HTTP (local process)¶
Run the server as a long-lived HTTP process:
uvx --from audio-transcriber audio-transcriber-mcp --transport streamable-http --host 0.0.0.0 --port 8000
curl -s http://localhost:8000/health # {"status":"OK"}
Then either let the client launch it:
{
"mcpServers": {
"audio-transcriber-mcp": {
"command": "uvx",
"args": ["--from", "audio-transcriber", "audio-transcriber-mcp", "--transport", "streamable-http", "--port", "8000"],
"env": {
"TRANSPORT": "streamable-http",
"HOST": "0.0.0.0",
"PORT": "8000",
"AUDIO_TRANSCRIPTOR_API_KEY": "<your-audio_transcriptor_api_key>"
}
}
}
}
…or connect to the already-running process by URL:
3. Local container / uv¶
(a) Launch a container directly from mcp_config.json (stdio over the container —
no ports to manage). Swap docker for podman for a daemonless runtime:
{
"mcpServers": {
"audio-transcriber-mcp": {
"command": "docker",
"args": [
"run", "-i", "--rm",
"-e", "TRANSPORT=stdio",
"-e", "AUDIO_TRANSCRIPTOR_API_KEY=<your-audio_transcriptor_api_key>",
"knucklessg1/audio-transcriber:latest"
]
}
}
}
(b) Run a local streamable-http container, then connect by URL:
docker run -d --name audio-transcriber-mcp -p 8000:8000 \
-e TRANSPORT=streamable-http \
-e PORT=8000 \
-e AUDIO_TRANSCRIPTOR_API_KEY="<your-audio_transcriptor_api_key>" \
knucklessg1/audio-transcriber:latest
# or, from a clone of this repo:
docker compose -f docker/mcp.compose.yml up -d
(c) From a local checkout with uv:
4. Remote URL (deployed behind Caddy)¶
When the server is deployed remotely (e.g. as a Docker service) and published through
Caddy on the internal *.arpa zone, connect with the "url" key — no local process or
image required:
Caddy reverse-proxies http://audio-transcriber-mcp.arpa to the container's :8000
streamable-http listener; http://audio-transcriber-mcp.arpa/health returns
{"status":"OK"} when the service is live.
This page covers running audio-transcriber as a long-lived server: the transports,
the optional A2A agent, a Docker Compose stack, putting it behind a Caddy reverse
proxy, and giving it a DNS name with Technitium.
audio-transcriberships an MCP server (console scriptaudio-transcriber-mcp) and an A2A agent server (console scriptaudio-transcriber-agent). The MCP server is the typed, deterministic tool surface; the agent drives those tools over the Agent Control Protocol.
Run the MCP server¶
The transport is selected with --transport (or the TRANSPORT env var):
Health check (HTTP transports):
Configuration (environment)¶
audio-transcriber is configured from the environment. The commonly used set:
| Var | Default | Meaning |
|---|---|---|
HOST |
0.0.0.0 |
Bind address for HTTP transports |
PORT |
8000 |
Bind port for HTTP transports |
TRANSPORT |
stdio |
stdio, streamable-http, or sse |
WHISPER_MODEL |
base |
Whisper model: tiny, base, small, medium, large |
TRANSCRIBE_DIRECTORY |
data dir | Default directory for recordings and exports |
AUDIO_PROCESSINGTOOL |
True |
Register the audio-processing tool set |
MISC_TOOL |
True |
Register the miscellaneous (health) tool set |
ENABLE_OTEL |
True |
Export OpenTelemetry traces |
EUNOMIA_TYPE |
none |
Authorization mode: none, embedded, remote |
Every variable, grouped by concern, is documented in
.env.example.
Copy it to .env and populate only what you use.
Docker Compose¶
The repo ships docker/mcp.compose.yml.
It reads a sibling .env and publishes the HTTP server on :8000:
services:
audio-transcriber-mcp:
image: knucklessg1/audio-transcriber:latest
container_name: audio-transcriber-mcp
hostname: audio-transcriber-mcp
restart: always
env_file:
- ../.env
environment:
- PYTHONUNBUFFERED=1
- HOST=0.0.0.0
- PORT=8000
- TRANSPORT=streamable-http
ports:
- "8000:8000"
healthcheck:
test: ["CMD", "python3", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')"]
interval: 30s
timeout: 10s
retries: 3
cp .env.example .env # then edit WHISPER_MODEL and any other values
docker compose -f docker/mcp.compose.yml up -d
docker compose -f docker/mcp.compose.yml logs -f
Run the A2A agent¶
The agent connects to the MCP server and exposes an Agent Control Protocol endpoint
(and an optional web interface). The console script is audio-transcriber-agent:
export MCP_URL=http://localhost:8000/mcp
audio-transcriber-agent --provider openai --model-id gpt-4o
The repo ships docker/agent.compose.yml,
which deploys the MCP server and the agent together. The agent listens on :9014
and is wired to the MCP server by container name through MCP_URL:
services:
audio-transcriber-mcp:
image: knucklessg1/audio-transcriber:latest
hostname: audio-transcriber-mcp
environment:
- TRANSPORT=streamable-http
- HOST=0.0.0.0
- PORT=8000
ports:
- "8000:8000"
audio-transcriber-agent:
image: knucklessg1/audio-transcriber:latest
depends_on:
- audio-transcriber-mcp
command: ["audio-transcriber-agent"]
environment:
- HOST=0.0.0.0
- PORT=9014
- MCP_URL=http://audio-transcriber-mcp:8000/mcp
- PROVIDER=${PROVIDER:-openai}
- MODEL_ID=${MODEL_ID:-gpt-4o}
- ENABLE_WEB_UI=True
ports:
- "9014:9014"
The agent endpoints are then available at http://localhost:9014/a2a (discovery at
/a2a/.well-known/agent.json) and, when enabled, the web interface at
http://localhost:9014/.
Behind a Caddy reverse proxy¶
Expose the HTTP server on a hostname with automatic TLS. Add to your Caddyfile:
# Internal (self-signed) — homelab .arpa zone
audio-transcriber.arpa {
tls internal
reverse_proxy audio-transcriber-mcp:8000
}
# Public — automatic Let's Encrypt
audio-transcriber.example.com {
reverse_proxy audio-transcriber-mcp:8000
}
Reload Caddy:
DNS with Technitium¶
Point the hostname at the host running Caddy. Via the Technitium API:
curl -s "http://technitium.arpa:5380/api/zones/records/add" \
--data-urlencode "token=$TECHNITIUM_DNS_TOKEN" \
--data-urlencode "domain=audio-transcriber.arpa" \
--data-urlencode "zone=arpa" \
--data-urlencode "type=A" \
--data-urlencode "ipAddress=10.0.0.10" \
--data-urlencode "ttl=3600"
…or add an A record audio-transcriber.arpa → <caddy-host-ip> in the Technitium
web console (http://technitium.arpa:5380). The ecosystem
technitium-dns-mcp automates
this as a tool.
Register with an MCP client¶
Add to your client's mcp_config.json:
{
"mcpServers": {
"audio-transcriber": {
"command": "uv",
"args": ["run", "audio-transcriber-mcp"],
"env": {
"WHISPER_MODEL": "base",
"TRANSCRIBE_DIRECTORY": "~/Downloads"
}
}
}
}
For a remote HTTP server, point the client at
http://audio-transcriber.arpa/mcp instead.