# co-op

> Use this tool when you need to enable collaboration between large language models (LLMs) or integrate multiple LLMs into a single system. The co-op tool solves problems of isolated model functionality by facilitating communication between LLMs, allowing for more complex and cooperative tasks. It takes LLM inputs and outputs, providing a server-based interface for model interaction, ideal for use cases requiring multi-model collaboration or distributed processing.

Canonical page: https://skillsregistry.net/skills/inventwithdean-co-op  
JSON: https://api.skillsregistry.net/v1/skills/inventwithdean-co-op

## Description

An MCP server written in Rust that lets your LLM talk to other LLMs

## Trust

- **Trust score (0–1):** 0.97
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-19

## Source

- **Source listing:** [GitHub](https://github.com/inventwithdean/co-op)

## 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": "inventwithdean-co-op"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/inventwithdean-co-op` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/inventwithdean-co-op/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