OpenTag: Smart mentions for Slack and GitHub, free and open source
·1 min read·Intermediate
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Tired of copy-pasting code between Slack and GitHub? Now you can tag an AI agent directly in chat and get results in a thread without jumping between apps.
In 30 seconds
01OpenTag connects Slack and GitHub with AI (Codex, Claude) to execute tasks directly in chat without switching between apps.
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What this means for you
If you spend a lot of time between Slack and GitHub, OpenTag saves you hours of copy-pasting per month. Tag an agent, get the result in the thread, keep working. No more open apps.
Building a desktop app feels like wizardry, right? This new open-source kit lets you make one, fast, just knowing web basics.
·2 min·2·Beginner
Open source tool by Amplify HQ, deployable on your own server: zero third-party API costs and full data control.
03Built for teams spending 40% of time on Slack: removes context switching across 6 apps, keeps workflow continuous.
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How does this system actually work?
OpenTag is an open source tool that connects Slack and GitHub to AI models like Codex and Claude Code. When you tag the agent in a conversation, the request gets routed to your chosen model, which processes the task and returns results directly in the thread. No redirects, no new windows: everything happens where you're already working.
The project is hosted on GitHub by Amplify HQ, which released OpenTag as an open source solution for collaborative automation. You can deploy it on your own server, customize it to your needs, and integrate it into your team's workflows without depending on closed third-party services.
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Why would a developer actually use this?
Most AI tools for devs require constant context switching. Open ChatGPT, copy the code, paste it in GitHub, wait for feedback, go back to chat. OpenTag kills these steps by keeping everything in one place: Slack becomes your conversational IDE.
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According to the maintainers, the tool is designed specifically for teams already using Slack as a communication hub. If you're already spending 40% of your work day on Slack, adding native AI capabilities makes economic sense: fewer micro-interactions, more continuous workflow. Not magic, but pragmatic.
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Who actually needs this?
Mainly engineer and dev teams working in small groups, tech startups, and companies wanting to avoid vendor lock-in with proprietary AI solutions. If your stack is GitHub + Slack, integrating an open source agent means zero third-party API costs and full data control.
The alternative? Keep jumping between six apps hoping you remember where you left the last version of the code.
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