# MCP Feedback Enhanced (Hunter Fork)

> Use this tool when you need to facilitate interactive feedback sessions with multiple participants or across several windows. It solves problems of disorganized and limited communication by providing features like multiple chat tabs and clipboard support for image sharing. Ideal for collaborative environments, it takes input from users through chat and clipboard interactions, and outputs organized feedback sessions.

Canonical page: https://skillsregistry.net/skills/olojiang-mcp-feedback-ji  
JSON: https://api.skillsregistry.net/v1/skills/olojiang-mcp-feedback-ji

## Description

Enables interactive feedback sessions in Cursor with support for multiple chat tabs, clipboard (copy/paste images), and robust connection management across multiple windows.

## Trust

- **Trust score (0–1):** 0.64
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/xni21adyuz)
- **Repository:** <https://github.com/olojiang/mcp_feedback_ji>

## 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": "olojiang-mcp-feedback-ji"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/olojiang-mcp-feedback-ji` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/olojiang-mcp-feedback-ji/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