<h2 align="center">built with</h2> <picture> <source media="(prefers-color-scheme: dark)" srcset="static/logo_white.svg"> <source
built with . The mcp use voice assistant mcp server wraps that behind the Model Context Protocol, so an assistant can use it through 5 defined tools rather than through you.
Everything the assistant can do here goes through one of these:
macOS — brew install portaudioWindows — PyAudio wheel includes PortAudioplaywright — Web automation and browser controllinear — Task and project managementPrerequisites — 1. Python 3.11+ 2. uv (Python package manager): pip install uv or pipx install uv 3. Node.js (for MCP servers) 4. **SystemYou will need 8 environment variables: YOUR_API_KEY, OPENAI_API_KEY, ELEVENLABS_API_KEY, ANTHROPIC_API_KEY, GROQ_API_KEY, ELEVENLABS_VOICE_ID, LINEAR_API_KEY, GITHUB_PERSONAL_ACCESS_TOKEN. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
pip install uv or pipx install uv 3. Node.js (for MCP servers) 4. System dependencies: - macOS: brew install portaudio - Ubuntu/Debian: sudo apt-get install portaudio19-dev - Windows: PyAudio wheel includes PortAudioThe server ships on npm as downloads, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.
Among the AI and media services options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. MCP Use Voice Assistant's toolset — macOS, Windows, playwright and 2 more — is a fair guide to whether it matches your workflow. It is maintained by mcp-use; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against MCP Use Voice Assistant's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| macOS | brew install portaudio |
| Windows | PyAudio wheel includes PortAudio |
| playwright | Web automation and browser control |
| linear | Task and project management |
| Prerequisites | 1. **Python 3.11+** 2. **uv** (Python package manager): pip install uv or pipx install uv 3. **Node.js** (for MCP servers) 4. **System dependencies**: - macOS: brew install portaudio - Ubuntu/Debian: sudo apt-get install |
{
"mcpServers": {
"use-voice-assistant": {
"command": "npx",
"args": ["-y", "downloads"],
"env": {
"YOUR_API_KEY": "your-value",
"OPENAI_API_KEY": "your-value",
"ELEVENLABS_API_KEY": "your-value",
"ANTHROPIC_API_KEY": "your-value",
"GROQ_API_KEY": "your-value",
"ELEVENLABS_VOICE_ID": "your-value",
"LINEAR_API_KEY": "your-value",
"GITHUB_PERSONAL_ACCESS_TOKEN": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
pip install uv or pipx install uv 3. Node.js (for MCP servers) 4. System dependencies: - macOS: brew install portaudio - Ubuntu/Debian: sudo apt-get install portaudio19-dev - Windows: PyAudio wheel includes PortAudio| Variable | Description | Required |
|---|---|---|
| YOUR_API_KEY | Credential the server authenticates with. | Yes |
| OPENAI_API_KEY | Credential the server authenticates with. | Yes |
| ELEVENLABS_API_KEY | Credential the server authenticates with. | Yes |
| ANTHROPIC_API_KEY | Credential the server authenticates with. | Yes |
| GROQ_API_KEY | Credential the server authenticates with. | Yes |
| ELEVENLABS_VOICE_ID | Configuration value read at startup. | Optional |
| LINEAR_API_KEY | Credential the server authenticates with. | Yes |
| GITHUB_PERSONAL_ACCESS_TOKEN | Credential the server authenticates with. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.