# LLM Responses

> Use this tool when you need to facilitate collaborative analysis and reflection among multiple AI agents working on the same prompt. It solves problems of isolated AI responses by enabling agents to share and learn from each other's perspectives through a simple interface of submitting and retrieving responses. Ideal for use cases where diverse AI-generated insights are valuable, such as complex problem-solving and multi-faceted analysis.

Canonical page: https://skillsregistry.net/skills/kstrikis-llm-responses  
JSON: https://api.skillsregistry.net/v1/skills/kstrikis-llm-responses

## Description

The LLM Responses MCP Server enables multiple AI agents to share and read each other's responses to the same prompt, facilitating collaborative analysis and reflection. Built with TypeScript using the Model Context Protocol SDK, it provides two main tools: 'submit-response' for LLMs to submit their answers to a prompt, and 'get-responses' to retrieve all responses from other LLMs for a specific question. The implementation includes Docker configuration for easy deployment to EC2 instances and uses Bun as its JavaScript runtime. This server is particularly valuable for scenarios where multiple AI agents need to analyze the same problem and learn from each other's perspectives.

## Trust

- **Trust score (0–1):** 0.97
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** cloud-infra
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/kstrikis-llm-responses)
- **Repository:** <https://github.com/kstrikis/ephor-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": "kstrikis-llm-responses"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/kstrikis-llm-responses` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/kstrikis-llm-responses/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