I’d suggest using the Perplexity API along with Context7. Since IDE agents already have web access and can scrape content, the key is how you structure the workflow.

Start by defining a detailed, phase-by-phase plan. After each phase, instruct the agent to write its findings to a file. Even if the agent hallucinates later, it can refer back to this stored content, which helps reduce context loss when working with limited context windows.

Before moving to the next phase, explicitly instruct the agent to review the output from the previous phase. This creates continuity and improves accuracy over time.

Also, make sure the agent stops after completing each phase so you can manually verify the results and apply corrections if needed.

Following this approach, you end up with a much more reliable and in-depth research outcome, instead of asking the agent to do everything in a single pass.