WhatsApp MCP lets AI agents read personal chats on Cloudflare Workers
A GitHub project called WhatsApp MCP lets an AI agent read a user’s personal WhatsApp messages by running a small server inside a Cloudflare Workers account. After linking a phone once – the same way WhatsApp Web is linked – the server stores the chat history in a SQLite database inside a Durable Object. AI tools that speak the MCP protocol, such as Claude Code or Claude Desktop, can then ask…
Key points
- Runs on a Cloudflare Workers Paid plan, costing a few dollars a month.
- Uses the Baileys library to emulate WhatsApp Web, which violates WhatsApp’s terms.
- AI agents can query, search, and summarize chats but cannot send messages.
The deployment requires a Cloudflare Workers Paid plan, which the author says costs a few dollars a month, Node 20 or later, and a WhatsApp‑linked phone. The code uses the open‑source Baileys library to mimic the WhatsApp Web protocol, a method that WhatsApp’s terms prohibit. Data never leaves the user’s Cloudflare account, and media files are stored only as labels (e.g., [image], [voice note 12s]) without transcription. The author notes that the first import may be fragile on the free plan and that the server must be re‑linked if the phone removes the device.
Because the server is a personal deployment, each instance handles a single WhatsApp account and its own login credentials. The design deliberately avoids contacting external contacts services; instead, the AI agent can look up unknown numbers in the user’s own contacts and save names back into the database.
Show HN: WhatsApp MCP running free on Cloudflare
github.com · 18 October 2026Loading the full article…
This text was published by github.com. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗
Coverage and discussion
1source- Hacker News discussion · 43 pointsnews.ycombinator.com
The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.
More in Agents & Tools
All →- Anthropic consults law firms to develop negotiation norms for AI agents · 3 src
- Opinion: GPT-6.1 Sol may be the best default model for Codex users · 1 src
- Simon Willison releases llm-tools-datasette 0.1.1 · 1 src
- TinyFish provides free search and fetch, benchmark shows $9.30 per 1,000 tasks · 1 src
- Six AI agents spam MP office and leak data while chasing £350 train refund · 2 src
Comments
via GitHub Discussions