Airweave is an open-source dev tool that lets agents search any app. It connects to apps, databases, or document stores and turns their contents into searchable knowledge bases for agents.
A few months ago we were building agents that interacted with various apps. We were frustrated when they struggled with vague natural language requests like "resolve that Jira ticket about missing auth configs", "refund payments in Stripe for unsatisfied customers", or "what were Q1 returns from the financial sheet in gdrive?" The agents would then inefficiently chain multiple function calls, fail to retrieve data, or hallucinate answers.
We also noticed that despite the rise of MCP creating more desire for agents to interact with external resources, the majority of agent dev tooling focused on function calling and actions instead of search. We were annoyed by the lack of tooling that enabled agents to semantically search workspace or database contents, so we started building Airweave first as an internal solution. Then we decided to open-source it and pursue it full time after we saw the positive reactions from agent builders.
The best part for us about building Airweave is continually seeing the amazing things our users create with it.
Looking forward to the comments 👋
- Lennert & Rauf
About Airweave on Product Hunt
“Let Agents Search Any App”
Airweave launched on Product Hunt on May 27th, 2025 and earned 206 upvotes and 39 comments, placing #10 on the daily leaderboard. Airweave is an open-source dev tool that lets agents search any app. It connects to apps, databases, or document stores and turns their contents into searchable knowledge bases for agents.
On the analytics side, Airweave competes within Open Source, Developer Tools and Artificial Intelligence — topics that collectively have 1M followers on Product Hunt. The dashboard above tracks how Airweave performed against the three products that launched closest to it on the same day.
Who hunted Airweave?
Airweave was hunted by Garry Tan. 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 Airweave including community comment highlights and product details, visit the product overview.
Garry Tan
A few months ago we were building agents that interacted with various apps. We were frustrated when they struggled with vague natural language requests like "resolve that Jira ticket about missing auth configs", "refund payments in Stripe for unsatisfied customers", or "what were Q1 returns from the financial sheet in gdrive?" The agents would then inefficiently chain multiple function calls, fail to retrieve data, or hallucinate answers.
We also noticed that despite the rise of MCP creating more desire for agents to interact with external resources, the majority of agent dev tooling focused on function calling and actions instead of search. We were annoyed by the lack of tooling that enabled agents to semantically search workspace or database contents, so we started building Airweave first as an internal solution. Then we decided to open-source it and pursue it full time after we saw the positive reactions from agent builders.
The best part for us about building Airweave is continually seeing the amazing things our users create with it.
Looking forward to the comments 👋
- Lennert & Rauf