# agent-consult

> agent-consult — vkirill-agent-consult. Use this tool when you need to facilitate multi-agent AI consultations and achieve consensus among models like Codex, Claude, Anti-Gravity, and Mimo. It solves problems of model inconsistency and disagreement by providing a production-ready Model Context Protocol (MCP) server with Minimax-M3 consensus synthesis. The agent-consult tool takes in multiple AI model inputs and outputs a unified consensus decision, ideal for use cases requiring collaborative AI decision-making.

Canonical page: https://skillsregistry.net/skills/vkirill-agent-consult  
JSON: https://api.skillsregistry.net/v1/skills/vkirill-agent-consult

## Description

Production-ready Model Context Protocol (MCP) server for multi-agent AI consultations (Codex, Claude, Anti-Gravity, Mimo) with Minimax-M3 consensus synthesis

## Trust

- **Trust score (0–1):** 0.79
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/VKirill/agent-consult)

## 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": "vkirill-agent-consult"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/vkirill-agent-consult` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/vkirill-agent-consult/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