Provides Model Context Protocol (MCP) servers for file searching and speech-to-text conversion.
Most AI and media services work still happens through a UI a human drives. File Finder & Whisper STT MCP server moves it into the conversation instead. Provides Model Context Protocol (MCP) servers for file searching and speech-to-text conversion.
The server publishes 9 tools. What each one is for:
name — имя файлаpath — абсолютный путь к файлуsize — размер файла в байтахcreated — дата и время создания файлаaudio — строка в формате base64, содержащая аудиоданныеtext — полный транскрибированный текстsegments — массив сегментов с временными меткамиlanguage — определенный языкlanguage_probability — вероятность определения языкаInstallation goes through your MCP client rather than a global install: point it at pip on npm and it is fetched when the client starts. The copy-paste blocks for Claude Desktop, Claude Code and Cursor are further down this page.
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. File Finder & Whisper STT's toolset — name, path, size and 6 more — is a fair guide to whether it matches your workflow. It is maintained by sergey-fintech; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against File Finder & Whisper STT's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| name | имя файла |
| path | абсолютный путь к файлу |
| size | размер файла в байтах |
| created | дата и время создания файла |
| audio | строка в формате base64, содержащая аудиоданные |
| text | полный транскрибированный текст |
| segments | массив сегментов с временными метками |
| language | определенный язык |
| language_probability | вероятность определения языка |
{
"mcpServers": {
"file-finder-whisper-stt": {
"command": "npx",
"args": ["-y", "pip"]
}
}
}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.