Voice Bridge
Add multi-engine text-to-speech to your coding assistant so summaries and alerts are spoken aloud, including a free engine option.
Overview
Voice Bridge is an MCP server for the Build phase that provides multi-engine text-to-speech—including a free engine—for AI coding assistants.
What is this MCP server?
- Multi-engine TTS MCP server aimed at AI coding assistants
- 5 TTS engines with a free engine included
- npm: ai-voice-bridge (npx) and PyPI uvx path with edge-tts + MCP extras
- stdio transport; version 0.1.5
- Console entry voice-bridge-mcp for MCP mode
- 5 TTS engines documented
- 1 free engine included
- Server version 0.1.5
What problem does it solve?
Builders staring at the IDE miss urgent agent updates because long responses stay silent and single-vendor TTS setups are fiddly to wire into MCP.
Who is it for?
Solo developers who want audible agent feedback in Claude Code or Cursor with engine choice and a no-cost path to try TTS.
Skip if: Teams shipping production voice products that need hosted telephony, SSML studio workflows, or compliance-heavy call center features.
What do I get? / Deliverables
After you register Voice Bridge, your assistant can speak responses through selectable TTS engines so you hear completions and summaries without extra glue code.
- MCP tools that synthesize speech from agent text across up to 5 engines
- Local voice readout workflow without custom TTS glue in the repo
Recommended MCP Servers
Journey fit
Voice output is agent tooling you add while building and tuning how your assistant behaves in the IDE, not a launch or growth distribution task. Agent-tooling is the shelf because Voice Bridge exists specifically to extend Claude Code–class assistants with TTS MCP tools.
How it compares
MCP TTS integration with 5 engines, not a markdown-only ‘read aloud’ skill or a single-vendor cloud widget.
Common Questions / FAQ
Who is Voice Bridge for?
Voice Bridge is for indie builders using MCP-enabled coding assistants who want spoken output from agent messages with multiple TTS backends.
When should I use Voice Bridge?
Use it while building or daily-driving agent workflows when audible readouts, accessibility, or hands-free monitoring of long agent runs would help.
How do I add Voice Bridge to my agent?
Add the MCP server via npx ai-voice-bridge or uvx with ai-voice-bridge[edge,mcp] and the voice-bridge-mcp entry point, stdio transport, then restart your client.