Developers can quickly integrate messaging AI functionality through Pond's MCP protocol:
- Environment deployment: get pond_mcp_server binary from /Applications/Pond.app/Contents/MacOS/
- Protocol Selection: Select stdio (low latency) or Streamable HTTP (cross-process) communication mode depending on the application scenario.
- <Strong] Data Processing Flow::
- Calling the GetConversations interface to get the message threads
- Semantic Analysis with AnalyzeContext
- Generate Response Suggestions via GenerateDraft
- error handling: Monitor status codes such as INVALID_ACCESS_TOKEN to automatically trigger re-authentication.
- performance optimization: Enable Chunking mode for long conversations to avoid memory overflow.
Python sample code is provided on the official website, and the average integration time is about 2 working days. SDK and technical support services are available for commercial users.
This answer comes from the articlePond: macOS tool for efficiently managing WhatsApp messages with AI-generated repliesThe
May not be reproduced without permission:AI productivity tools " Optimizing the technical path for developers to integrate messaging AI capabilities
English 
简体中文 
日本語 
Deutsch 
Português do Brasil