A high-performance speech recognition MCP server based on Faster Whisper, providing efficient audio transcription capabilities.
Whisper Speech Recognition MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. A high-performance speech recognition MCP server based on Faster Whisper, providing efficient audio transcription capabilities.
Once Whisper Speech Recognition is connected, these are the calls the assistant has available:
Dependencies — The Dependencies tool exposed by this servertorch on PyPI is all you need. Most clients run it directly, so configuration is a few lines and a restart.
Among the AI and media services options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. Whisper Speech Recognition's toolset — Dependencies — is a fair guide to whether it matches your workflow. It is maintained by BigUncle; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
| Tool | What it does |
|---|---|
| Dependencies | The Dependencies tool exposed by this server. |
{
"mcpServers": {
"fast-whisper": {
"command": "uvx",
"args": ["torch"]
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.