Short Video MCP Server

Instructions

      提取视频内容，需要传递apikey，否则无法使用视频内容提取功能！
      参数:
      - text: 抖音分享文本，包含分享链接
      - api_base_url: API基础URL，默认使用siliconflow.cn
      - model: 语音识别模型，默认使用FunAudioLLM/SenseVoiceSmall
      

Implementation Reference

• yby6_video_mcp_server/server.py:54-62 (registration)

  Registration of the MCP tool 'share_text_parse_tool_wrapper' using @mcp.tool decorator. The description string defines the tool schema including parameters and usage.

  @mcp.tool(
      description="""
            提取视频内容，需要传递apikey，否则无法使用视频内容提取功能！
            参数:
            - text: 抖音分享文本，包含分享链接
            - api_base_url: API基础URL，默认使用siliconflow.cn
            - model: 语音识别模型，默认使用FunAudioLLM/SenseVoiceSmall
            """
  )

• yby6_video_mcp_server/server.py:63-82 (handler)

  The handler function that implements the logic for 'share_text_parse_tool_wrapper'. It delegates to the core 'share_text_parse_tool' utility function in utils/tools.py.

  async def share_text_parse_tool_wrapper(
      text: str,
      api_base_url: Optional[str] = None,
      model: Optional[str] = None,
      ctx: Context = None,
  ) -> Dict[str, Any]:
      """
      解析抖音分享链接，提取无水印视频地址
      下载无水印视频
      提取音频
      转换音频为文本
      清理临时文件
  
      参数:
      - text: 抖音分享文本，包含分享链接
      - api_base_url: API基础URL，默认使用SiliconFlow
      - model: 语音识别模型，默认使用SenseVoiceSmall
      """
      return await share_text_parse_tool(text, api_base_url, model, ctx)

• yby6_video_mcp_server/utils/tools.py:61-151 (helper)

  Core helper function 'share_text_parse_tool' that contains the main implementation logic for parsing share text, downloading video, extracting audio, transcribing to text, and cleanup. Called by the wrapper handler.

  async def share_text_parse_tool(
      text: str,
      api_base_url: Optional[str] = None,
      model: Optional[str] = None,
      ctx: Context = None,
  ) -> Dict[str, Any]:
      """
      解析抖音分享链接，提取无水印视频地址
      下载无水印视频
      提取音频
      转换音频为文本
      清理临时文件
  
      参数:
      - text: 抖音分享文本，包含分享链接
      - api_base_url: API基础URL，默认使用SiliconFlow
      - model: 语音识别模型，默认使用SenseVoiceSmall
      """
      if not text or not isinstance(text, str):
          return create_error_response("文本参数不能为空")
      
      try:
          # 获取配置参数
          api_key, api_base_url, model = get_api_configuration(ctx, api_base_url, model)
          
          if not api_key:
              error_msg = "没有传递apikey，请通过参数传入apikey或请求头传入apikey，或者设置环境变量API_KEY，否则无法使用视频内容提取功能！"
              logger.error(error_msg)
              return create_error_response(error_msg)
  
          processor = VideoProcessor(api_key, api_base_url, model)
  
          # 解析视频链接
          video_share_url = extract_url_from_text(text)
          if not video_share_url:
              error_msg = f"无法从文本中提取视频链接: {text}"
              logger.error(error_msg)
              return create_error_response(error_msg)
  
          video_obj = await parse_video_share_url(video_share_url)
          video_info = create_success_response("解析成功", video_obj.__dict__)
  
          # 处理视频下载和文本提取
          try:
              download_video_info = {
                  "url": video_info["data"]["video_url"],
                  "title": video_info["data"]["title"],
                  "video_id": str(int(time.time())),
              }
              
              logger.info(f"开始下载视频: {download_video_info['title']}")
              video_path = await processor.download_video(download_video_info)
              ctx.info(f"视频下载地址: {video_path}")
              
              logger.info("开始提取音频")
              audio_path = processor.extract_audio(video_path)
              ctx.info(f"音频提取地址: {audio_path}")
              
              logger.info("开始转换音频为文本")
              text_content = processor.extract_text_from_audio(audio_path)
              ctx.info(f"文本提取内容: {text_content}")
              
              logger.info("清理临时文件")
              processor.cleanup_files(video_path, audio_path)
              ctx.info(f"临时文件清理: {video_path}, {audio_path}")
              
              return {
                  "code": DEFAULT_RESPONSE_CODES['SUCCESS'],
                  "msg": "解析成功",
                  "data": video_info["data"],
                  "text_content": text_content,
              }
          except Exception as processing_err:
              logger.error(f"视频处理失败: {processing_err}")
              # 确保清理可能存在的临时文件
              try:
                  if 'video_path' in locals() and 'audio_path' in locals():
                      processor.cleanup_files(video_path, audio_path)
              except Exception:
                  pass
              raise processing_err
      except ValueError as err:
          logger.error(f"参数错误: {err}")
          if ctx:
              ctx.error(f"参数错误: {str(err)}")
          return create_error_response(str(err))
      except Exception as err:
          logger.error(f"未知错误: {err}")
          if ctx:
              ctx.error(f"解析失败: {str(err)}")
          return create_error_response(f"解析失败: {str(err)}")