# Hivemind

> Use this tool when you need to leverage the collective knowledge of multiple large language models to generate more accurate and reliable responses. Hivemind solves problems of inconsistent or biased outputs by aggregating responses from various models, including OpenAI, Anthropic, and Google. It takes natural language queries as input and returns consensus-based answers, making it ideal for applications requiring high confidence and precision.

Canonical page: https://skillsregistry.net/skills/quantulabs-hivemind  
JSON: https://api.skillsregistry.net/v1/skills/quantulabs-hivemind

## Description

Hivemind enables AI assistants to query multiple large language models simultaneously and aggregate their responses for consensus-based answers. Supports OpenAI, Anthropic, and Google models, allowing comparison and synthesis across providers.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-04-25

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/quantulabs-hivemind)
- **Repository:** <https://github.com/quantulabs/hivemind>

## 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": "quantulabs-hivemind"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/quantulabs-hivemind` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/quantulabs-hivemind/pull`

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