transcript-tts
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@transcript-tts Convert 'Thank you for calling' to an MP3 with a natural voice."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
transcript-tts
A minimal MCP server that converts text/transcripts into
MP3 audio using Microsoft Edge's free neural text-to-speech voices (edge-tts).
No API key, no account, no usage cap — it's an unofficial use of the same TTS service behind
Edge's "Read Aloud" feature.
Tools
text_to_speech(text, voice="en-US-AriaNeural", rate="+0%", volume="+0%", pitch="+0Hz", filename=None)Synthesizestextto an MP3 file. Returns{"audio_path": ..., "voice": ...}. Files are saved to~/tts-output/by default (override withTRANSCRIPT_TTS_OUTPUT_DIR).list_voices(locale_prefix=None)Lists available voices, optionally filtered by locale (e.g."en-US","ja","en-GB").
Related MCP server: Edge TTS MCP
Setup
Requires uv.
git clone https://github.com/ShevinuM/transcript-tts.git
cd transcript-tts
uv syncRegister with Claude Code:
claude mcp add --scope user transcript-tts -- \
/path/to/transcript-tts/.venv/bin/python /path/to/transcript-tts/server.pyOr add it manually to your MCP client config (e.g. claude_desktop_config.json):
{
"mcpServers": {
"transcript-tts": {
"command": "/path/to/transcript-tts/.venv/bin/python",
"args": ["/path/to/transcript-tts/server.py"]
}
}
}Environment variables
TRANSCRIPT_TTS_OUTPUT_DIR— where MP3s are saved (default:~/tts-output)TRANSCRIPT_TTS_VOICE— default voice short name (default:en-US-AriaNeural)
Notes
Requires mcp[cli]>=2.0.0 — the MCP Python SDK renamed FastMCP to MCPServer in its 2.0
release, so this won't work against older mcp SDK versions without adjusting the import in
server.py.
Available Tools
2 toolslist_voicesA
List available Edge TTS voices, optionally filtered by locale prefix (e.g. 'en-US', 'ja').
Inputs: locale_prefix. Returns: result
text_to_speechA
Convert a transcript/text into an MP3 audio recording using Microsoft Edge's free neural TTS voices, saved to disk. Call list_voices first if you want a specific voice/language/accent.
Inputs: text (required), rate, pitch, voice, +2 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: one lists available voices, the other converts text to speech. There is no overlap or ambiguity between them.
Both tool names follow a consistent verb_noun pattern: 'list_voices' and 'text_to_speech'. The naming is predictable and uniform.
With only two tools, the server feels minimal but appropriately scoped for a simple TTS purpose. It is on the lower end of the acceptable range as noted in the calibration guide.
The core workflow is covered: list voices to select one, then synthesize text. Minor gaps like streamed audio or additional output formats could be added, but the essential lifecycle is complete.
Related MCP Connectors
Text to speech and transcription for any AI model: MP3 voiceovers, audio and YouTube to text.
Turn text into natural-sounding MP3 voice-overs in 6 languages. Free plan included.
Text to speech in 149 languages: MP3 links from any assistant. Free without an account.
Hosted pay-per-use TTS: 54 neural voices, 9 languages incl. Brazilian Portuguese. $10 free credits.
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- AlicenseNot gradedqualityDmaintenanceAn MCP server that converts text into lifelike speech using Microsoft Edge's Text-to-Speech service, supporting customizable voice, rate, volume, and pitch.4MIT
- AlicenseAqualityCmaintenanceProvides text-to-speech synthesis using Microsoft Edge's free TTS engine, supporting multiple voices, languages, and audio output options (base64 or file).3MIT
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