# MCP Elicitations Demo Server

> Use this tool when you need to collect structured user input interactively across multiple tools and resources. The MCP Elicitations Demo Server demonstrates how to elicit information using the Model Context Protocol, solving problems related to data collection and user interaction. It provides an interface for interactive input collection, generating outputs that can be used to inform model development and decision-making.

Canonical page: https://skillsregistry.net/skills/quantgeekdev-mcp-elicitations-server  
JSON: https://api.skillsregistry.net/v1/skills/quantgeekdev-mcp-elicitations-server

## Description

Demonstrates elicitations for collecting structured user input interactively across tools, resources, and prompts in the Model Context Protocol.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/zhjbdsvtef)
- **Repository:** <https://github.com/QuantGeekDev/mcp-elicitations-server>

## 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": "quantgeekdev-mcp-elicitations-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/quantgeekdev-mcp-elicitations-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/quantgeekdev-mcp-elicitations-server/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