Voice MCP▌
by mbailey
Voice MCP powers two-way voice apps with Google Cloud Speech to Text, Speech Recognition, and Text to Speech API for acc
Enables two-way voice conversations through multiple transport methods including local microphone recording and LiveKit room-based communication, with configurable STT/TTS services and automatic transport fallback for creating voice-enabled applications.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Developers who need hands-free coding assistance
- / Working while multitasking or away from keyboard
- / Accessibility for users who prefer voice interaction
capabilities
- / Record voice through local microphone
- / Convert speech to text with multiple STT services
- / Convert text to speech with configurable TTS services
- / Connect through LiveKit rooms for remote voice chat
- / Handle automatic transport fallback
- / Maintain continuous voice conversations
what it does
Enables voice conversations with Claude by converting speech to text and text back to speech. Works through local microphone or remote room connections with automatic fallback options.
about
Voice MCP is a community-built MCP server published by mbailey that provides AI assistants with tools and capabilities via the Model Context Protocol. Voice MCP powers two-way voice apps with Google Cloud Speech to Text, Speech Recognition, and Text to Speech API for acc It is categorized under productivity, communication.
how to install
You can install Voice MCP in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Voice MCP is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
VoiceMode
Natural voice conversations with Claude Code (and other MCP capable agents)
VoiceMode enables natural voice conversations with Claude Code. Voice isn't about replacing typing - it's about being available when typing isn't.
Perfect for:
- Walking to your next meeting
- Cooking while debugging
- Giving your eyes a break after hours of screen time
- Holding a coffee (or a dog)
- Any moment when your hands or eyes are busy
See It In Action
Quick Start
Requirements: Computer with microphone and speakers
Option 1: Claude Code Plugin (Recommended)
The fastest way for Claude Code users to get started:
# Add the VoiceMode marketplace
claude plugin marketplace add mbailey/voicemode
# Install VoiceMode plugin
claude plugin install voicemode@voicemode
## Install dependencies (CLI, Local Voice Services)
/voicemode:install
# Start talking!
/voicemode:converse
Option 2: Python installer package
Installs dependencies and the VoiceMode Python package.
# Install UV package manager (if needed)
curl -LsSf https://astral.sh/uv/install.sh | sh
# Run the installer (sets up dependencies and local voice services)
uvx voice-mode-install
# Add to Claude Code
claude mcp add --scope user voicemode -- uvx --refresh voice-mode
# Optional: Add OpenAI API key as fallback for local services
export OPENAI_API_KEY=your-openai-key
# Start a conversation
claude converse
For manual setup, see the Getting Started Guide.
Features
- Natural conversations - speak naturally, hear responses immediately
- Works offline - optional local voice services (Whisper STT, Kokoro TTS)
- Low latency - fast enough to feel like a real conversation
- Smart silence detection - stops recording when you stop speaking
- Privacy options - run entirely locally or use cloud services
Compatibility
Platforms: Linux, macOS, Windows (WSL), NixOS Python: 3.10-3.14
Configuration
VoiceMode works out of the box. For customization:
# Set OpenAI API key (if using cloud services)
export OPENAI_API_KEY="your-key"
# Or configure via file
voicemode config edit
See the Configuration Guide for all options.
Permissions Setup (Optional)
To use VoiceMode without permission prompts, add to ~/.claude/settings.json:
{
"permissions": {
"allow": [
"mcp__voicemode__converse",
"mcp__voicemode__service"
]
}
}
See the Permissions Guide for more options.
Local Voice Services
For privacy or offline use, install local speech services:
- Whisper.cpp - Local speech-to-text
- Kokoro - Local text-to-speech with multiple voices
These provide the same API as OpenAI, so VoiceMode switches seamlessly between them.
Installation Details
<details> <summary><strong>System Dependencies by Platform</strong></summary>Ubuntu/Debian
sudo apt update
sudo apt install -y ffmpeg gcc libasound2-dev libasound2-plugins libportaudio2 portaudio19-dev pulseaudio pulseaudio-utils python3-dev
WSL2 users: The pulseaudio packages above are required for microphone access.
Fedora/RHEL
sudo dnf install alsa-lib-devel ffmpeg gcc portaudio portaudio-devel python3-devel
macOS
brew install ffmpeg node portaudio
NixOS
# Use development shell
nix develop github:mbailey/voicemode
# Or install system-wide
nix profile install github:mbailey/voicemode
</details>
<details>
<summary><strong>Alternative Installation Methods</strong></summary>
From source
git clone https://github.com/mbailey/voicemode.git
cd voicemode
uv tool install -e .
NixOS system-wide
# In /etc/nixos/configuration.nix
environment.systemPackages = [
(builtins.getFlake "github:mbailey/voicemode").packages.${pkgs.system}.default
];
</details>
Troubleshooting
| Problem | Solution |
|---|---|
| No microphone access | Check terminal/app permissions. WSL2 needs pulseaudio packages. |
| UV not found | Run curl -LsSf https://astral.sh/uv/install.sh | sh |
| OpenAI API error | Verify OPENAI_API_KEY is set correctly |
| No audio output | Check system audio settings and available devices |
Save Audio for Debugging
export VOICEMODE_SAVE_AUDIO=true
# Files saved to ~/.voicemode/audio/YYYY/MM/
Documentation
- Getting Started - Full setup guide
- Configuration - All environment variables
- Whisper Setup - Local speech-to-text
- Kokoro Setup - Local text-to-speech
- Development Setup - Contributing guide
Full documentation: voice-mode.readthedocs.io
Links
- Website: getvoicemode.com
- GitHub: github.com/mbailey/voicemode
- PyPI: pypi.org/project/voice-mode
- YouTube: @getvoicemode
- Twitter/X: @getvoicemode
- Newsletter:
License
MIT - A Failmode Project
mcp-name: com.failmode/voicemode
FAQ
- What is the Voice MCP MCP server?
- Voice MCP is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Voice MCP?
- This profile displays 60 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.7★★★★★60 reviews- ★★★★★Kwame Diallo· Dec 28, 2024
Voice MCP is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Ama Singh· Dec 28, 2024
According to our notes, Voice MCP benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★William Bansal· Dec 20, 2024
Voice MCP is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Ganesh Mohane· Dec 16, 2024
Voice MCP reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Hiroshi Rao· Dec 16, 2024
Voice MCP is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Carlos Garcia· Dec 4, 2024
I recommend Voice MCP for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Carlos Dixit· Nov 27, 2024
We evaluated Voice MCP against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Ama Verma· Nov 23, 2024
Voice MCP reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Sakura Jain· Nov 19, 2024
We wired Voice MCP into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Sakshi Patil· Nov 7, 2024
I recommend Voice MCP for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
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