Give your AI agents access to WhatsApp

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Hi, I built Chat-Man because I wanted a cheap way to give my agents access to WhatsApp without integrating a WhatsApp library separately in every project. You get WhatsApp MCP server, so you can connect WhatsApp to an agent and programmatically read, search, extract and send messages - but also have a web UI for non-techies. You can also receive webhooks for incoming messages for starred conversations. What you can do with the MCP? -Read WhatsApp messages and turn them into CRM records -Summarise conversations or groups -Extract structured information from messages -Find messages, participants or other WhatsApp data -Send messages -Manage group memberships Of course.. you always need to follow data protection regulation. The web UI: -Edit group details -See who joined or left -See who is most active -Export group members -Match members against a CSV (e.g. from a CRM) -Bulk message members -Bulk kick members -Create invite links For individual contacts, you can send messages directly from the UI. Why I built it for myself? I needed WhatsApp access for several projects (hermo.ai, florahaus.co.uk, …) and didn't want to pay for a WhatsApp integration for each project. Link: https://chat-man.net I’d love to get some feedback, especially from people building agents that need access to WhatsApp. Fabian

Visit product View on Hacker NewsSep 16, 2026

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best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, mcp · Missing: mac, macos, cursor

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TrustMRRLess likely to generate early MRR · Strong signals: way, para · Missing: mobile apps, ios, personal

37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

29%29% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Strong signals: arr, active · Missing: mrr, revenue, profit

21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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