# getuserfeedback.com

> Use this tool when you need to collect and analyze user feedback through customizable surveys, solving problems related to understanding user needs and preferences. It allows you to create and edit feedback surveys, with inputs including survey questions and outputs including user responses. Use it to inform product development, improve user experience, and make data-driven decisions.

Canonical page: https://skillsregistry.net/skills/com-getuserfeedback-mcp  
JSON: https://api.skillsregistry.net/v1/skills/com-getuserfeedback-mcp

## Description

Create and edit feedback surveys and read responses from your AI assistant.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 0.1.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-06-18

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/com.getuserfeedback%2Fmcp)

## Use it

MCP endpoint published by the skill: `https://mcp.getuserfeedback.com/`

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": "com-getuserfeedback-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/com-getuserfeedback-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/com-getuserfeedback-mcp/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