Talkies

Name: Talkies
Author: psyb0t

by psyb0tversion 0.17.0i★ –iRuns on your computer

Registry nameio.github.psyb0t/talkies

Install

Overview

Description from the maker (original English)

Self-hosted MCP server for speech: ASR transcription, TTS synthesis, and file staging tools.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: Streamable HTTP
Category: Design, images & audio

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

DockerDocker installed

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "talkies": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "docker.io/psyb0t/talkies:v0.17.0"
      ]
    }
  }
}

Run this in your terminal

claude mcp add talkies -- docker run -i --rm docker.io/psyb0t/talkies:v0.17.0

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "talkies": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "docker.io/psyb0t/talkies:v0.17.0"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "talkies": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "docker.io/psyb0t/talkies:v0.17.0"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account psyb0t, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Design, images & audioi

More stars than 0% of the other 2192 servers in this category
Published to the registry more recently than 27% of the other 2192 servers in this category
Basic checks equal to or better than 100% of the other 2192 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Talkies safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.17.0) reached the registry 2 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker on your computer.

What can I use instead?

In the same category: Figma Context MCP, Claude Real Video, Figma MCP Server

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

talkies

Self-hosted speech services in one Docker image: OpenAI-compatible file transcription and text-to-speech, Talkies live ASR over WebSocket, file staging, model lifecycle controls, and an MCP endpoint for ASR workflows.

Start here
What it provides
Models at a glance
Reading phonemes
Prompting Chatterbox with emotion
Documentation
Agent integrations
Security in one minute
Development

Start here

Restrict the first boot to the models you need; otherwise the entrypoint downloads every model in the bundled registry.

docker run --rm -it --name talkies \

-p 127.0.0.1:8000:8000 \ -v "$PWD/talkies-data:/data" \ -e TALKIES_ENABLED_MODELS=whisper-large-v3-turbo,kokoro-82m \ psyb0t/talkies:latest

curl -s http://127.0.0.1:8000/healthz curl -s http://127.0.0.1:8000/v1/audio/transcriptions \ -F "file=@/path/to/clip.wav" \ -F "model=whisper-large-v3-turbo"

For CUDA-only models — Parakeet-TDT, the larger Canary models, Qwen3 TTS and Chatterbox Turbo — use psyb0t/talkies:latest-cuda with --gpus all. The loopback port mapping keeps the service local; see Getting started for first boot and authentication.

What it provides

Surface	Purpose	Reference
`POST /v1/audio/transcriptions`	File transcription and subtitles	HTTP API
`WS /v1/audio/transcriptions/stream`	Live 16 kHz PCM ASR	Streaming
`POST /v1/audio/speech`	Speech synthesis in six formats	HTTP API
`GET /v1/models`	Enabled slugs and their modality	HTTP API
`GET /v1/audio/voices`	Per-model voice catalog with origin tags	Models
`GET/PUT/DELETE /v1/files/*`	Server-side file staging	HTTP API
`/api/ps`, `/unload`	Model inspection and eviction	Operations
`/v1/mcp`	Streamable HTTP MCP with ASR/file tools	HTTP API
`GET /healthz`	Liveness probe; the only unauthenticated route	Operations

The HTTP transcription and speech routes use the corresponding OpenAI wire shapes where those contracts overlap. Streaming ASR, files, lifecycle controls, and MCP are Talkies extensions.

Models at a glance

CPU: two Whisper models, Canary-180M-Flash, Nemotron ASR via parakeet.cpp, four English Sherpa-ONNX Zipformer choices, Vosk small English, two phoneme recognizers, and two Kokoro TTS backends.
CUDA: the CPU set plus Parakeet-TDT, Canary 1B/Qwen ASR, five Qwen3 TTS variants, and Chatterbox Turbo.
Live ASR: bundled Nemotron, Sherpa-ONNX, and Vosk are native; bundled Whisper is a bounded rolling decoder. Sherpa and Vosk also work through the OpenAI-compatible file-transcription endpoint.
Phoneme recognition: wav2vec2-xlsr-53-espeak and zipa-ipa return the IPA phones that were spoken, not words, with no language model correcting them toward the nearest dictionary entry. Same transcription endpoint and timestamp options as the other ASR models; see Phoneme recognition.
Per-model concurrency limits cover WebSocket, HTTP, MCP, ASR, and TTS; the bundled Nemotron CPU and CUDA entries admit two requests.
Streaming TTS: Qwen3 returns incremental raw PCM for response_format="pcm"; other TTS formats and Kokoro are buffered.
Expressive TTS: Chatterbox Turbo (English) takes 19 inline tags such as [sigh], [whispering] and [laugh] directly in the input text. Its output carries a neural watermark by default; set TALKIES_CHATTERBOX_WATERMARK to false to emit unmarked audio.
Voice cloning: drop a .wav into /data/custom-voices and it appears on GET /v1/audio/voices. Qwen3 pairs it with an optional sibling .txt transcript; Chatterbox needs only the clip, longer than five seconds.

Exact slugs, executors, tag list, and registry format: Models and registries.

Reading phonemes

wav2vec2-xlsr-53-espeak and zipa-ipa use the same transcription call as every other ASR slug; only the model changes. text comes back as a space-separated IPA phone stream rather than words, and no language model corrects a mispronunciation toward a real word.

curl -s http://127.0.0.1:8000/v1/audio/transcriptions \

-F "file=@/path/to/clip.wav" \ -F "model=zipa-ipa"

{"text": "a ɪ m k ə n f j u z ...", ...}

Add -F "response_format=verbose_json" (or timestamp_granularities[]=word) to get each phone as a words entry with start and end in seconds.

Prompting Chatterbox with emotion

Tags go inline in input, in square brackets, lowercase. They are real tokens in the model's tokenizer, so only these 19 do anything — any other bracketed word is spoken as literal text:

[angry] [fear] [surprised] [whispering] [advertisement] [dramatic] [narration]

[crying] [happy] [sarcastic] [clear throat] [sigh] [shush] [cough] [groan] [sniff] [gasp] [chuckle] [laugh]

curl -s http://127.0.0.1:8000/v1/audio/speech \

-H 'Content-Type: application/json' \ -d '{ "model": "chatterbox-turbo", "voice": "builtin", "input": "Oh, that is hilarious. [chuckle] Anyway [sigh] back to work.", "response_format": "mp3" }' --output out.mp3

Swap "voice" for the name of any .wav you dropped in /data/custom-voices (extension stripped) to speak the same line in a cloned voice.

Documentation

Guide	Contents
Getting started	Run CPU/CUDA, persist data, authenticate, verify
Models and registries	Bundled slugs, image availability, custom registries
Architecture	Request flow, backend selection, on-disk layout
HTTP API	Requests, responses, files, lifecycle, MCP
Streaming	Live ASR protocol, streaming backends, PCM TTS
Configuration	Supported environment variables and limits
Operations and security	Exposure, model memory, data retention, logs
Development	Make targets, test suites, image builds

Agent integrations

The Talkies skill teaches agents to use the HTTP, WebSocket, and MCP surfaces. Install it through the shared psyb0t marketplace or let Codex discover it directly from this checkout.

Claude Code

claude plugin marketplace add psyb0t/agents

claude plugin install talkies@psyb0t

Claude Code prompts for the Talkies URL and, when enabled, the bearer token; the sensitive token is stored through the client's protected configuration.

Codex

codex plugin marketplace add psyb0t/agents

codex plugin add talkies@psyb0t

A marketplace install invokes the skill as $talkies:talkies. Codex also discovers .agents/skills/talkies directly in this repository, where it is invoked as $talkies without installation.

OpenClaw

The skill and MCP bridge are published through ClawHub:

openclaw skills install @psyb0t/talkies

openclaw plugins install clawhub:@psyb0t/talkies

The bridge connects local stdio MCP clients to a running Talkies /v1/mcp endpoint. Set TALKIES_URL and, when authentication is enabled, TALKIES_AUTH_TOKEN.

Security in one minute

TALKIES_AUTH_TOKEN enables a shared bearer token for every HTTP and WebSocket route except /healthz. It is unset by default. Keep the port loopback-only or put Talkies behind TLS, authentication, and rate limiting. If untrusted callers can supply remote file_path URLs, set TALKIES_BLOCK_PRIVATE_DOWNLOADS=true. See Operations and security for the complete posture.

Development

make check                 # lint + unit tests in the dev image

make lint # flake8 + mypy only make test-unit # fast offline unit tests make run # run the CPU image locally make test-streaming # real CPU native WebSocket ASR test make test-streaming-custom # real CPU Sherpa/Vosk WebSocket + HTTP tests make test-streaming-custom-cuda # real CUDA Sherpa WebSocket + HTTP test make compile-heavy # regenerate the hash-locked ML requirements make build-all # CPU and CUDA production images

make help lists every target.

Talkies is released under the WTFPL. Model weights are downloaded at runtime and have their own terms; image component notices are in THIRD_PARTY.md. Release notes are in CHANGELOG.md.

Talkies

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Design, images & audioi

Common questions

Alternatives

Figma Context MCP

Claude Real Video

Figma MCP Server

README from the maker

talkies

Contents

Start here

What it provides

Models at a glance

Reading phonemes

{"text": "a ɪ m k ə n f j u z ...", ...}

Prompting Chatterbox with emotion

Documentation

Agent integrations

Claude Code

Codex

OpenClaw

Security in one minute

Development