clova-speech-lecture-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@clova-speech-lecture-mcpTranscribe and summarize lecture.mp3"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
CLOVA Speech Lecture MCP Server
강의 녹음 STT 및 요약을 위한 MCP 서버입니다.
Google ADK 에이전트에서 네이버 CLOVA Speech / CLOVA Studio API를 호출합니다.
제공 툴
툴 이름 | 설명 | 적합한 상황 |
| 동기 STT (60초 이하) | 짧은 클립, 테스트 |
| 비동기 STT 제출 (강의 전체) | 수십 분~수 시간 강의 |
| 비동기 STT 결과 조회 | submit 후 폴링 |
| 강의 전사본 요약 | 전사 완료 후 |
Related MCP server: audio-transcriber
시작하기
1. API 키 발급
CLOVA Speech (STT)
네이버 클라우드 플랫폼 로그인
AI Services → CLOVA Speech → 이용 신청
서비스 생성 후 Secret Key 복사
CLOVA Studio (요약)
AI Services → CLOVA Studio → 이용 신청
Playground에서 앱 생성
API 키 및 앱 ID 복사
2. .env 설정
cp .env .env.local # 실제 값으로 수정CLOVA_SPEECH_API_KEY=실제_키_입력
CLOVA_STUDIO_CLIENT_ID=실제_Client_ID
CLOVA_STUDIO_CLIENT_SECRET=실제_Client_Secret
CLOVA_STUDIO_APP_ID=실제_앱_ID3. 실행
# Docker
docker-compose up -d
# 로컬 실행
pip install -r requirements.txt
python app/main.py4. ADK 에이전트 연결
# agent.py 예시
tools = [
MCPToolset(
connection_params=SseServerParams(url="http://localhost:8002/sse")
)
]강의 처리 플로우
[강의 오디오 파일]
↓
transcribe_lecture_submit(file_path, enable_diarization=True)
↓ (task_id 반환)
get_transcription_result(task_id) ← 완료까지 자동 폴링
↓ (full_text 반환)
summarize_lecture(text)
↓
[요약문 + 키워드]지원 오디오 형식
.wav .mp3 .flac .m4a .aac .ogg
지원 언어
코드 (단문) | 코드 (장문) | 언어 |
|
| 한국어 |
|
| 영어 |
|
| 일본어 |
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