Today we're launching Airbyte Agents. It's the biggest step we've taken as a company since we open-sourced our first connector six years ago.
We want to explain why we built this product, and why we think it's important.
The problem
As agents move into real workflows, they need access to more tools. That means going through a lot of API plumbing: authentication, pagination, filters, schema, and matching entities across systems.
Simply put, APIs are built for pre-determined workflows that assume you know what you want to query: think specific endpoints, object IDs, and exact fields.
Agents often start one step earlier. They need to discover what data actually matters before they can start reasoning. This is where most of the existing architectures break.
The solution
Airbyte Agents fixes the context layer underneath. The foundation is a piece of infra we call the Context Store. A data index optimized for agentic search, that gives agents a structured way to discover the right records, while still allowing them to read and write directly to upstream systems when needed.
The results
In early benchmarks, calling the Context Store consumed up to 80% fewer tokens and made 40% fewer tool calls compared to querying vendor MCPs and APIs directly.
What does this mean? Lower token usage, fewer rate limits, and more accurate outputs from cleaner context, all while saving money in the process.
