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EarScribe is a browser-based transcription tool that converts audio to text on-device using OpenAI
EarScribe is a browser-based transcription tool that converts audio to text on-device using OpenAI
This is a well-constructed, read-only MCP server that exposes canonical information about EarScribe with no authentication requirements, no external API calls, no credential handling, and minimal attack surface. The server is stateless, serves only static markdown content, and has clean dependency management with a single required package. No security vulnerabilities or dangerous patterns were identified. Supply chain analysis found 2 known vulnerabilities in dependencies (0 critical, 2 high severity).
4 files analyzed · 2 issues found
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Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-rocnubie-earscribe-mcp": {
"args": [
"-y",
"msa-earscribe-mcp"
],
"command": "npx"
}
}
}From the project's GitHub README.
MCP server for EarScribe
A Model Context Protocol server that exposes the canonical EarScribe knowledge surface — local-first AI workflows, FAQ, official links — to MCP-compatible AI clients such as Claude Desktop, Cursor, Windsurf, and Continue. Read-only, no API keys, no quota, ~50 ms cold start.
Official website: https://earscribe.app
EarScribe is a browser-based transcription tool that converts audio files into text entirely on the user's device. Powered by OpenAI's Whisper model running locally via WebGPU or WebAssembly, it produces timestamped transcripts and subtitle files without sending any audio to external servers. There is no account to create, no subscription to manage, and no per-minute fee — the tool works in the browser, caches the Whisper model locally after the first load, and can operate offline from that point forward. It supports a wide range of audio formats and handles recordings up to approximately two hours long, making it a practical option for anyone who regularly works with spoken audio.
EarScribe is well-suited for anyone who transcribes audio regularly and either has privacy concerns about uploading recordings to cloud services or wants to avoid ongoing subscription costs. Journalists, academic researchers, and UX professionals dealing with confidential or sensitive interviews will find the local processing model particularly useful. Podcasters and video creators who want subtitle files without paying per-minute fees are a natural fit, as are students converting lecture recordings into study material. The tool also works for individual users who simply want a free, no-account transcription option that handles common audio formats without any setup beyond a modern browser.
get_local_setupReturn canonical local-setup guidance for running the AI workflow on-device. (EarScribe)
Input: no parameters. Returns: text/markdown.
get_official_linksReturn the canonical list of official links for EarScribe (website, support, docs when available).
Input: no parameters. Returns: text/markdown.
site://earscribe/local-setup — Local-first setup notes for on-device AI workflows.site://earscribe/faq — Short FAQ generated from public site metadata.site://earscribe/links — Canonical URLs to share with users.tell_me_about_earscribeSummarize what the site is, who it's for, and how it works. — EarScribe
walkthrough_local_setup_earscribeWalk through the local-first setup steps for the site, end-to-end. — EarScribe
npx -y @smithery/cli install earscribe-mcp --client claude
(Replace claude with cursor, windsurf, or continue for those clients.)
git clone https://github.com/rocnubie/earscribe-mcp.git
cd earscribe-mcp
pnpm install
Then add to your MCP client config (claude_desktop_config.json for Claude Desktop, mcp.json for Cursor / Windsurf / Continue):
{
"mcpServers": {
"earscribe-mcp": {
"command": "node",
"args": [
"/absolute/path/to/earscribe-mcp/src/index.mjs"
]
}
}
}
npx @modelcontextprotocol/inspector node src/index.mjs
pnpm install
pnpm start # run the server over stdio
MIT
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