Text To Speech Mcp — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Text To Speech Mcp (Agent Skill) and scored it 96/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 1 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 1 flagged
The text {match} tells the agent to skip the normal "ask the user first" gate. Used adversarially it removes the human-in-the-loop check before destructive or sensitive actions, turning a normally-gated agent into a fire-and-forget executor.
Every scanned point with the score it earned and what moved between them.
Aggregate score unchanged between these scans.
The primary manifest — the file an agent reads to learn what this artifact does.
<!-- mcp-name: io.github.Engr-FaizanAli/text-to-speech -->
Text to Speech is an open-source Model Context Protocol (MCP) server that lets AI assistants read text aloud on the user's computer. On Windows it uses the built-in Speech API (SAPI) by default, so no API key, account, subscription, or cloud text-to-speech service is required.
The server exposes one model-controlled tool:
speak_text(text: string)Use it for user-provided text, assistant answers, accessibility workflows, or spoken progress updates while an agent works.
stdio transport through the official Python SDK.The MCP server source is open source under the MIT License. Windows SAPI is a proprietary component included with Windows; it is not an open-source speech engine.
uv/uvx is recommended for package-based MCP installation.After the package is published to PyPI, configure an MCP client to run:
uvx text-to-speech-mcpFor Codex, add this to ~/.codex/config.toml:
[mcp_servers.text_to_speech]
command = "uvx"
args = ["text-to-speech-mcp"]
startup_timeout_sec = 30
tool_timeout_sec = 300
enabled = trueRestart the MCP client after changing its configuration.
git clone https://github.com/engr-faizanali/text-to-speech-mcp.git
cd text-to-speech-mcp
python -m pip install -e .Then configure the client to run text-to-speech-mcp directly.
Read arbitrary text:
Use the Text to Speech tool to read aloud: The deployment completed successfully.Read the final answer:
Use the Text to Speech tool to read your final response aloud before displaying it.Read visible intermediate progress updates in order:
Use the text_to_speech MCP server's speak_text tool for spoken progress updates.
For every meaningful intermediate update that you display to me:
1. Write a concise, natural-language version of the update.
2. Call speak_text with that text.
3. Wait for the call to finish before producing or speaking the next update.
4. Then display the same update in text.
Also read the final answer aloud before displaying it. Never narrate hidden
reasoning, chain-of-thought, secrets, credentials, raw tool output, terminal
logs, or source code. Do not invoke speech calls in parallel. If the tool is
unavailable, continue normally in text and report the failure once.The text_to_speech portion is the client-side server name from the Codex configuration. Other clients may display a different namespace while keeping the tool name speak_text.
| Field | Value |
|---|---|
| Tool name | speak_text |
| Input | text, required string, 1-10,000 characters |
| Result | Completion message after local playback finishes |
| Ordering | FIFO, one active playback at a time |
| Queue limit | 32 pending requests |
| Network use with SAPI | None |
The tool is model-controlled under MCP. The user decides when to ask the model to call it, and the MCP client may show or require approval for tool calls.
With the default SAPI backend, text is passed from the MCP client to a local Python process and then to Windows speech components. It is not sent to this project, an external API, or a cloud TTS provider. Generated WAV files are written under %TEMP%\text-to-speech-mcp and deleted after playback unless TEXT_TO_SPEECH_KEEP_AUDIO=true is set.
Do not ask an AI assistant to speak secrets, credentials, private keys, hidden reasoning, or sensitive tool output.
The default requires no configuration:
TEXT_TO_SPEECH_BACKEND = "sapi"Advanced users can set TEXT_TO_SPEECH_BACKEND to piper, transformers_mms, or http. These options require their own local model, binary, Python dependencies, or endpoint. See PACKAGE_MCP.md.
Legacy CODEX_TTS_BACKEND and CODEX_TTS_FALLBACK_BACKEND environment variables remain supported for compatibility.
python -m pip install -e ".[dev]"
python -m unittest discover -s tests -v
python scripts/validate_release.py --online
python -m build
python -m twine check dist/*See MCP_PUBLIC_RELEASE.md for the full release process.
stdioserver.json using the 2025-12-11 schemamcp-name commentio.github.Engr-FaizanAli/text-to-speechOfficial references:
MIT. See LICENSE.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.