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ChatDrop
Turn WeChat exports into a local archive for AI tools
Share selected WeChat messages to ChatDrop on Mac, choose a conversation, and query your local archive with Codex, Claude Code or any tool with shell access. Filter by conversation and date, reuse matching messages, and fill missing attachments from later exports. MIT open source. Apple Silicon Mac; Python 3.9+ for the CLI.
I built ChatDrop because project decisions often stayed in WeChat while my development work happened in a terminal with an AI assistant. WeChat's native export provides a ZIP; ChatDrop supplies the receiving, organizing and querying layer.
You select the messages and name the local conversation. The CLI returns JSON, context and attachment paths. Original files stay on your Mac. ChatDrop itself does not upload your chats; an external AI tool has its own data handling.
The first release targets Apple Silicon Mac. Conversation naming is manual because the exports we observed do not contain stable group IDs. Deduplication is based on content rather than native message IDs, so identical same-minute messages in separate exports can remain ambiguous.
I'd love feedback from Mac users who want to bring selected project discussions into their existing AI workflow. Please use synthetic or redacted data in bug reports.
About ChatDrop on Product Hunt
“Turn WeChat exports into a local archive for AI tools”
ChatDrop was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #89 on the daily leaderboard. Share selected WeChat messages to ChatDrop on Mac, choose a conversation, and query your local archive with Codex, Claude Code or any tool with shell access. Filter by conversation and date, reuse matching messages, and fill missing attachments from later exports. MIT open source. Apple Silicon Mac; Python 3.9+ for the CLI.
On the analytics side, ChatDrop competes within Productivity, Open Source, Developer Tools and GitHub — topics that collectively have 1.3M followers on Product Hunt. The dashboard above tracks how ChatDrop performed against the three products that launched closest to it on the same day.
Who hunted ChatDrop?
ChatDrop was hunted by e0_7. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of ChatDrop including community comment highlights and product details, visit the product overview.
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