Building a Portuguese (PT-BR) Audio & Video Transcription Pipeline with Whisper Large-v3, Pyannote Speaker Diarization, and MCP

A developer built Transcreva, a browser-accessible PT-BR transcription and subtitle platform that pairs Whisper Large-v3 speech-to-text with Pyannote speaker diarization to produce speaker-labeled transcripts with word-level timestamps, plus SRT/VTT subtitle export. The workflow is also exposed to AI coding assistants such as Cursor, Claude Desktop and Windsurf through an open-source Model Context Protocol server, transcreva-mcp, installable via npx.

Transcribing multi-speaker audio and video in Brazilian Portuguese PT-BR comes with unique acoustic challenges: regional accents, colloquial expressions, overlapping speech in interviews, and low-bitrate voice notes such as .opus / .ogg files from WhatsApp . In this guide, we walk through how we architected Transcreva https://transcreva.net/ — a fast, browser-accessible AI transcription and subtitle generation platform with automatic speaker diarization — and how we exposed its workflow to AI coding agents using the Model Context Protocol MCP . When you run standard speech-to-text on a 45-minute podcast or academic interview, a wall of unsegmented text is hard to read. To produce dialogue-ready transcripts with Speaker 1 , Speaker 2 labels and word-level timestamps, we combine two stages: interface TranscriptSegment { id: string; speaker: string; // e.g., "Speaker 1" startTime: number; // seconds endTime: number; text: string; } export function formatSrtTimestamp seconds: number : string { const hrs = Math.floor seconds / 3600 ; const mins = Math.floor seconds % 3600 / 60 ; const secs = Math.floor seconds % 60 ; const ms = Math.round seconds % 1 1000 ; return ${String hrs .padStart 2, "0" }:${String mins .padStart 2, "0" }:${String secs .padStart 2, "0" },${String ms .padStart 3, "0" } ; } .opus / .ogg and Video Subtitles .srt / .vtt Two of the most common real-world workflows for Brazilian journalists, researchers, and creators are: transcreva-mcp To bring transcription utilities directly into AI coding assistants Cursor, Claude Desktop, Windsurf , we also built an open-source Model Context Protocol server: transcreva-mcp https://github.com/arkyu2077/transcreva-mcp . You can add it to your MCP configuration in seconds: { "mcpServers": { "transcreva": { "command": "npx", "args": "-y", "transcreva-mcp" } } }