Relay FAQs

Question 1

How does Relay improve feedback collection over traditional methods?

Accepted Answer

Relay uses a persistent GUI process and a local HTTP API to efficiently collect feedback (text, images) without `ARG_MAX` limits. It avoids spawning a UI per tool call and manages multiple requests via a multi-tab hub.

Question 2

Can Relay handle multiple concurrent feedback requests?

Accepted Answer

Absolutely. Relay features a multi-tab hub that efficiently manages concurrent feedback requests from different IDE threads, using `client_tab_id` to merge streams and prevent 'tab chaos.'

Question 3

Is Relay designed for privacy and local operation?

Accepted Answer

Yes, Relay operates entirely locally. All Answers, logs, and GUI state reside on your machine, and there is no built-in telemetry, ensuring your data remains private and secure.

Question 4

What is Relay's primary function for AI IDE agents?

Accepted Answer

Relay integrates seamless human-in-the-loop interaction by transforming interactive human feedback into blocking tool calls for AI IDE agents. It pauses the agent, collects your input via a dedicated GUI, and returns it directly.

Question 5

What configuration options does Relay offer?

Accepted Answer

Relay provides configurable auto-reply mechanisms for instant responses, attachment auto-purge settings to manage storage, and flexible integration into MCP-compatible IDEs via JSON configuration.

Relay

Relay

Características Principales

Casos de Uso

Características Principales

Casos de Uso