# IDE Relay

> Use this tool when you need to inject human judgment into AI-driven development workflows, allowing for precise control over automated tasks by collecting feedback through a intuitive desktop interface. It solves problems of automated workflow interruptions and unattended runs by providing a seamless way to input human decisions, with features like drag-and-drop file responses and automatic reply rules. Ideal for use cases requiring manual validation or exception handling in AI-powered integrated development environments (IDEs).

Canonical page: https://skillsregistry.net/skills/andeya-ide-relay  
JSON: https://api.skillsregistry.net/v1/skills/andeya-ide-relay

## Description

Human feedback layer for AI IDEs that pauses agent workflows to collect human input through a native desktop window. Built with Tauri, Rust, and Vue for cross-platform support on Windows, macOS, and Linux. Features drag-and-drop file responses, automatic reply rules for unattended runs, and timestamped logging. Inspired by interactive-feedback-mcp.

## Trust

- **Trust score (0–1):** 0.66
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** monitoring
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/andeya-ide-relay)
- **Repository:** <https://github.com/andeya/ide-relay-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "andeya-ide-relay"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/andeya-ide-relay` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/andeya-ide-relay/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt