No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by blacktop · MCP Server · ★ 72
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is mcp-tts safe to install? View the security audit →
mcp-tts MCP Server for TTS (Text-to-Speech) What? 🤔 Adds Text-to-Speech to things like Claude Desktop and Cursor IDE. It registers four TTS tools: - - Uses the macOS binary to speak the text with built-in system voices Uses the ElevenLabs text-to-speech API to speak the text with premium AI voices Uses Google's [Gemini TTS models](https://ai.google.dev/gemini-api/docs/speech
| Stars | 72 |
| Forks | 19 |
| Language | Go |
| Category | MCP Server |
| License | MIT |
| Quality Score | 67.2886828200725/100 |
| Open Issues | 3 |
| Last Updated | 2026-09-14 |
| Created | 2025-03-23 |
| Platforms | go, mcp |
| Est. Tokens | ~19k |
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mcp-tts is MCP Server for Text to Speech. It is categorized as a MCP Server with 72 GitHub stars.
mcp-tts is primarily written in Go. It covers topics such as elevenlabs, golang, google-tts.
You can find installation instructions and usage details in the mcp-tts GitHub repository at github.com/blacktop/mcp-tts. The project has 72 stars and 19 forks, indicating an active community.
mcp-tts is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to mcp-tts on Agent Skills Hub include gram, weather-mcp-server, openrouter-mcp-multimodal. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: