claude mcp add mcp-server-pronunciation -- npx -y mcp-server-pronunciation
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3 ★ · JuhongPark/mcp-server-pronunciation · read from the GitHub search API · (checked 2026-10-16 20:00:20)
Source
collected from the punkpeye/awesome-mcp-servers list · type: MCP server
Harvest history
first seen 2026-10-09 · last seen 2026-10-16 · seen 32× · listed by 7 sources
Score
score 703 · 3 ★ · 7 sources · mcp
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repository JuhongPark/mcp-server-pronunciation;first catalogued 2026-10-09;last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
> **Accuracy and safety notice** > > This project is a local language-learning practice tool. It may contain bugs, > runtime errors, inaccurate transcripts, inaccurate pronunciation feedback, or > platform-specific recording issues. Pronunciation feedback is a coaching > signal, not a standardized-test, clinical, employment, or high-stakes > assessment. Review outputs carefully before relying on them. See > DISCLAIMER.md. An MCP (Model Context Protocol) server that lets you **talk to your MCP assistant by voice while getting English pronunciation, grammar, and fluency feedback** in the same turn. Use it for casual voice chat with light coaching, or switch to drill mode when you want to practice a specific sentence. Built for Codex CLI, Claude Desktop, Claude Code, Cursor, VS Code, and other MCP clients. Everything runs locally — audio is captured with your mic, transcribed by faster-whisper on-device, and never leaves your machine. mcp-name: io.github.JuhongPark/pronunciation Why Voice MCP servers today treat speech as a typing replacement. English tutor MCP servers are text-only. This one combines the two: you speak freely, your assistant replies, and feedback on what you just said (pronunciation, grammar, fluency) surfaces inside the same tool call so the assistant can weave it into a natural reply — or stay out of the way when you're just chatting. Features - **Voice conversation** with your MCP assistant. Speak, auto-stop on silence, then let the assistant read your transcript and respond. - **Phoneme-level drill feedback** (when a reference sentence is given): Needleman-Wunsch word alignment, per-word expected vs produced IPA, learner-profile hints, minimal-pair drills, and prosody checks (word stress, final-rise intonation, intra-clause pauses). - **Extensible learner-profile support**: the current rule pack includes Korean-L1 pronunciation-pattern hints and Korean-language tips. Contributions for additional L1 profiles are welcome. - **Whisper-bias mitigation** via optional [phoneme] extra: wav2vec2 CTC forced alignment verifies whether the user actually produced each reference word, so rare proper nouns and domain-specific terms that Whisper rewrites toward more common alternatives no longer surface as mispronunciations. - **Inline English feedback in conversation**: pronunciation, grammar (common irregular-verb errors), and fluency (pace + long pauses). - **Drill mode** (practice, quick_practice, retry) for focused sentence practice. - **Local-only**: Whisper model runs on your machine, audio never leaves it. - **Cross-platform**: macOS, Linux, Windows, and WSL2 (recording auto-routes through Windows). - **Fast startup**: lazy imports + background model pre-load keep the MCP handshake under a second. Requirements - Python 3.11+ - A working microphone - ~150 MB disk space for the default Whisper model (base.en) - Additional ~360 MB if you install the optional [phoneme] extra (wav2vec2 weights for forced alignment) - MCP spec: targets 2025-06-18 via the official Python SDK (mcp>=1.2) Installation Stable release Install the latest stable release: For pip users: To pin this release explicitly: Run doctor before relying on the server in a live session: General install commands Linux: install PortAudio first sounddevice ships PortAudio inside the wheel on macOS and Windows, but on Linux you need the system library: First-time check Before wiring the server into an MCP client, run the preflight: Optional — pre-download the Whisper model (~150 MB) so the first call is instant: Add to your MCP client Codex CLI Claude Code Claude Desktop Edit claude_desktop_config.json: On macOS, if Claude Desktop can't find uvx (spawn uvx ENOENT), use an absolute path. Find it with which uvx in your terminal. Cursor Add to ~/.cursor/mcp.json: VS Code (with MCP support) Add to .vscode/mcp.json or your user settings: Usage Examples 1. Voice chat with feedback > **You**: "Let's have a voice chat. I'll ask you about the weekend. Use the converse tool." > > **Assistant** (calls converse): *records your speech, transcribes it, notes that you said "buyed" instead of "bought"*