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 elevenlabs · MCP Server · ★ 1.5k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is elevenlabs-mcp safe to install? View the security audit →
Official ElevenLabs Model Context Protocol (MCP) server that enables interaction with powerful Text to Speech and audio processing APIs. This server allows MCP clients like Claude Desktop, Cursor, Windsurf, OpenAI Agents and others to generate speech, clone voices, transcribe audio, and more. Quickstart with Claude Desktop
| Stars | 1,533 |
| Forks | 251 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 74.4942614042859/100 |
| Last Updated | 2026-08-20 |
| Created | 2025-03-14 |
| Platforms | mcp, python |
| Est. Tokens | ~15k |
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elevenlabs-mcp is The official ElevenLabs MCP server. It is categorized as a MCP Server with 1.5k GitHub stars.
elevenlabs-mcp is primarily written in Python. It covers topics such as elevenlabs, elevenlabs-api, mcp.
You can find installation instructions and usage details in the elevenlabs-mcp GitHub repository at github.com/elevenlabs/elevenlabs-mcp. The project has 1.5k stars and 251 forks, indicating an active community.
elevenlabs-mcp is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to elevenlabs-mcp on Agent Skills Hub include ai-skills, firecrawl-mcp-server, browser-tools-mcp. 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: