Pronunciation & Voice Coach
mcpkey · packageio.github.JuhongPark/pronunciation · v0.3.0
Local MCP voice coach with English pronunciation, grammar, and fluency feedback.
run it
on your own machines, one way per deploy methodgenerated from the record, not tested yet
# once, as root:
# as_mcp DIR COMMAND...: runs COMMAND as the mcp user in DIR, its home, sandboxed as the
# units are: a package's install scripts can write to DIR only, as the server later can
as_mcp() {
local dir="$1"; shift
systemd-run --quiet --wait --pipe --collect --uid=mcp --gid=mcp \
-p WorkingDirectory="$dir" -p Environment=HOME="$dir" -p ReadWritePaths="$dir" \
-p NoNewPrivileges=true -p ProtectSystem=strict -p ProtectHome=true -p PrivateTmp=true \
-- "$@" </dev/null
}
install -d -m 0750 -o mcp -g mcp /var/lib/mcp/pronunciation
# pronunciation: its packages, installed whole before its unit starts (no session installs)
systemctl stop mcp-my-agent-pronunciation.service 2>/dev/null || true
as_mcp /var/lib/mcp/pronunciation uv tool install mcp-server-pronunciation==0.3.0
as_mcp /var/lib/mcp/pronunciation uv tool install mcp-proxy
#!/usr/bin/env bash
# pronunciation (io.github.JuhongPark/pronunciation), recipe baremetal (generated).
# Generated by Hub for toolset "my-agent"; started by mcp-my-agent-pronunciation.service.
set -euo pipefail
export HOST=127.0.0.1 PORT=8101
exec uvx mcp-proxy --host 127.0.0.1 --port 8101 --pass-environment -- uvx mcp-server-pronunciation==0.3.0
[Unit]
Description=MCP server pronunciation (toolset my-agent), generated by Hub
After=network-online.target
Wants=network-online.target
[Service]
Type=simple
User=mcp
Group=mcp
EnvironmentFile=/etc/mcp/my-agent.env
Environment=HOME=/var/lib/mcp/pronunciation
WorkingDirectory=/var/lib/mcp/pronunciation
ExecStart=/opt/mcp/my-agent/bin/pronunciation.sh
Restart=on-failure
RestartSec=5
NoNewPrivileges=true
ProtectSystem=strict
ProtectHome=true
PrivateTmp=true
ReadWritePaths=/var/lib/mcp/pronunciation
[Install]
WantedBy=multi-user.target
generated from the record, not tested yet
docker run --rm -p 127.0.0.1:8101:8000 -e MCP_PRONUNCIATION_MODEL -e HF_HUB_CACHE -e MCP_PRONUNCIATION_PRELOAD -e MCP_PRONUNCIATION_AUDIO_RETENTION -e TORCH_HOME ghcr.io/astral-sh/uv:python3.12-bookworm-slim sh -c 'uvx mcp-proxy --host 0.0.0.0 --port 8000 --pass-environment -- uvx mcp-server-pronunciation==0.3.0'
generated from the record, not tested yet
# Generated by Hub for toolset "my-agent" (2026-10-18T16:56:20+00:00).
# Each package server runs behind a stdio->HTTP bridge and listens on localhost only.
# cp .env.example .env # fill the ${VAR}s
# docker compose up -d && bash smoke.sh
# Remote servers are not here: clients reach them directly (see clients/).
name: mcp-my-agent
services:
pronunciation:
image: ghcr.io/astral-sh/uv:python3.12-bookworm-slim
command:
- sh
- -c
- uvx mcp-proxy --host 0.0.0.0 --port 8000 --pass-environment -- uvx mcp-server-pronunciation==0.3.0
ports:
- 127.0.0.1:8101:8000
volumes:
- uv-cache:/root/.cache/uv
healthcheck:
test:
- CMD
- python3
- -c
- import urllib.request; urllib.request.urlopen('http://127.0.0.1:8000/status')
interval: 30s
timeout: 5s
retries: 5
start_period: 2m
restart: unless-stopped
environment:
MCP_PRONUNCIATION_MODEL: ${MCP_PRONUNCIATION_MODEL}
HF_HUB_CACHE: ${HF_HUB_CACHE}
MCP_PRONUNCIATION_PRELOAD: ${MCP_PRONUNCIATION_PRELOAD}
MCP_PRONUNCIATION_AUDIO_RETENTION: ${MCP_PRONUNCIATION_AUDIO_RETENTION}
TORCH_HOME: ${TORCH_HOME}
volumes:
npm-cache: {}
uv-cache: {}
generated from the record, not tested yet
# Generated by Hub for toolset "my-agent" (2026-10-18T16:56:20+00:00).
# kubectl create namespace mcp
# kubectl -n mcp create secret generic mcp-credentials --from-env-file=.env
# kubectl apply -f kubernetes.yaml
# Services are cluster-internal: <name>.mcp.svc.cluster.local:8000/mcp. Put an ingress
# with auth in front before exposing any of them.
apiVersion: v1
kind: Namespace
metadata:
name: mcp
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: pronunciation
namespace: mcp
labels: &id001
app: pronunciation
spec:
replicas: 1
selector:
matchLabels: *id001
template:
metadata:
labels: *id001
spec:
containers:
- name: pronunciation
image: ghcr.io/astral-sh/uv:python3.12-bookworm-slim
ports:
- containerPort: 8000
name: http
env:
- name: MCP_PRONUNCIATION_MODEL
valueFrom:
secretKeyRef:
name: mcp-credentials
key: MCP_PRONUNCIATION_MODEL
- name: HF_HUB_CACHE
valueFrom:
secretKeyRef:
name: mcp-credentials
key: HF_HUB_CACHE
- name: MCP_PRONUNCIATION_PRELOAD
valueFrom:
secretKeyRef:
name: mcp-credentials
key: MCP_PRONUNCIATION_PRELOAD
- name: MCP_PRONUNCIATION_AUDIO_RETENTION
valueFrom:
secretKeyRef:
name: mcp-credentials
key: MCP_PRONUNCIATION_AUDIO_RETENTION
- name: TORCH_HOME
valueFrom:
secretKeyRef:
name: mcp-credentials
key: TORCH_HOME
args:
- sh
- -c
- uvx mcp-proxy --host 0.0.0.0 --port 8000 --pass-environment -- uvx mcp-server-pronunciation==0.3.0
readinessProbe:
httpGet:
path: /status
port: http
initialDelaySeconds: 10
---
apiVersion: v1
kind: Service
metadata:
name: pronunciation
namespace: mcp
spec:
selector:
app: pronunciation
ports:
- port: 8000
targetPort: http
name: http
generated from the record, not tested yet
# Generated by Hub for toolset "my-agent" (2026-10-18T16:56:20+00:00).
# Credentials come from the Secret 'mcp-credentials' (kubectl create secret generic ... --from-env-file=.env).
# Each server under `servers` is one Deployment + Service; the keys after it configure
# upstream charts a worker verified.
servers:
pronunciation:
enabled: true
replicas: 1
port: 8000
path: /mcp
container:
name: pronunciation
image: ghcr.io/astral-sh/uv:python3.12-bookworm-slim
ports:
- containerPort: 8000
name: http
env:
- name: MCP_PRONUNCIATION_MODEL
valueFrom:
secretKeyRef:
name: mcp-credentials
key: MCP_PRONUNCIATION_MODEL
- name: HF_HUB_CACHE
valueFrom:
secretKeyRef:
name: mcp-credentials
key: HF_HUB_CACHE
- name: MCP_PRONUNCIATION_PRELOAD
valueFrom:
secretKeyRef:
name: mcp-credentials
key: MCP_PRONUNCIATION_PRELOAD
- name: MCP_PRONUNCIATION_AUDIO_RETENTION
valueFrom:
secretKeyRef:
name: mcp-credentials
key: MCP_PRONUNCIATION_AUDIO_RETENTION
- name: TORCH_HOME
valueFrom:
secretKeyRef:
name: mcp-credentials
key: TORCH_HOME
args:
- sh
- -c
- uvx mcp-proxy --host 0.0.0.0 --port 8000 --pass-environment -- uvx mcp-server-pronunciation==0.3.0
readinessProbe:
httpGet:
path: /status
port: http
initialDelaySeconds: 10
# helm install my-agent helm/my-agent -n mcp
in the cloud
one click: the provider's deploy form opens filled in, in your own account- koyeb
-
The form opens with CHANGE_ME for each value you supply: MCP_PRONUNCIATION_MODEL, HF_HUB_CACHE, MCP_PRONUNCIATION_PRELOAD, MCP_PRONUNCIATION_AUDIO_RETENTION, TORCH_HOME. Fill them in before you deploy.
Clients connect to the service's https://…koyeb.app address plus /mcp.
- azure
-
A Container Apps environment with one app per server, each with HTTPS ingress and one replica. The portal asks for each value you supply as a secure parameter; the deployment's outputs list the endpoints.
connect to it
copy what your client needsuvx mcp-server-pronunciation==0.3.0 # env: MCP_PRONUNCIATION_MODEL, HF_HUB_CACHE, MCP_PRONUNCIATION_PRELOAD, MCP_PRONUNCIATION_AUDIO_RETENTION, TORCH_HOME
{
"mcpServers": {
"pronunciation": {
"command": "uvx",
"args": [
"mcp-server-pronunciation==0.3.0"
],
"env": {
"MCP_PRONUNCIATION_MODEL": "${MCP_PRONUNCIATION_MODEL}",
"HF_HUB_CACHE": "${HF_HUB_CACHE}",
"MCP_PRONUNCIATION_PRELOAD": "${MCP_PRONUNCIATION_PRELOAD}",
"MCP_PRONUNCIATION_AUDIO_RETENTION": "${MCP_PRONUNCIATION_AUDIO_RETENTION}",
"TORCH_HOME": "${TORCH_HOME}"
}
}
}
}
#!/usr/bin/env bash
# Registers every server with Claude Code (run once; `claude mcp list` to check).
set -euo pipefail
set -a; [ -f .env ] && source .env; set +a
claude mcp add pronunciation -e "MCP_PRONUNCIATION_MODEL=${MCP_PRONUNCIATION_MODEL}" -e "HF_HUB_CACHE=${HF_HUB_CACHE}" -e "MCP_PRONUNCIATION_PRELOAD=${MCP_PRONUNCIATION_PRELOAD}" -e "MCP_PRONUNCIATION_AUDIO_RETENTION=${MCP_PRONUNCIATION_AUDIO_RETENTION}" -e "TORCH_HOME=${TORCH_HOME}" -- uvx mcp-server-pronunciation==0.3.0
{
"mcpServers": {
"pronunciation": {
"command": "uvx",
"args": [
"mcp-server-pronunciation==0.3.0"
],
"env": {
"MCP_PRONUNCIATION_MODEL": "${MCP_PRONUNCIATION_MODEL}",
"HF_HUB_CACHE": "${HF_HUB_CACHE}",
"MCP_PRONUNCIATION_PRELOAD": "${MCP_PRONUNCIATION_PRELOAD}",
"MCP_PRONUNCIATION_AUDIO_RETENTION": "${MCP_PRONUNCIATION_AUDIO_RETENTION}",
"TORCH_HOME": "${TORCH_HOME}"
}
}
}
}
{
"servers": {
"pronunciation": {
"type": "stdio",
"command": "uvx",
"args": [
"mcp-server-pronunciation==0.3.0"
],
"env": {
"MCP_PRONUNCIATION_MODEL": "${MCP_PRONUNCIATION_MODEL}",
"HF_HUB_CACHE": "${HF_HUB_CACHE}",
"MCP_PRONUNCIATION_PRELOAD": "${MCP_PRONUNCIATION_PRELOAD}",
"MCP_PRONUNCIATION_AUDIO_RETENTION": "${MCP_PRONUNCIATION_AUDIO_RETENTION}",
"TORCH_HOME": "${TORCH_HOME}"
}
}
}
}
name: my-agent target: local servers: - hub: io.github.JuhongPark/pronunciation
- not probed yet: tools unpinned, ingest lists them
tools
Not probed yetThe tools appear once the hub or its worker has listed this entry. Running it still works: your client lists them on first start.