Voice MCP
This MCP server provides voice interaction capabilities through multiple transport methods, enabling AI assistants to conduct two-way voice conversations using either local microphone recording or LiveKit room-based communication. Built by mbailey using Python with FastMCP, sounddevice, and OpenAI-compatible APIs, it features automatic transport selection that tries LiveKit first then falls back to local audio, configurable STT/TTS services with support for self-hosted alternatives, debug mode with audio file saving, and privacy-conscious design with clear user consent requirements. The implementation includes tools for asking voice questions with automatic response recording, standalone text-to-speech and speech-to-text functions, audio device detection, and LiveKit room status monitoring, making it valuable for creating voice-enabled AI assistants, accessibility applications requiring audio interaction, and development workflows that need flexible voice processing with both cloud and local deployment options.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately.
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- devops-ci
- Source
- PulseMCP
- Repository
- github.com/mbailey/voicemode
- Author type
- human
- Updated
- 2026-04-25
Use via MCP
Resolve Voice MCP from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.