# join.cloud

> join.cloud — kushneryk-join-cloud. Use this tool when you need to enable real-time collaboration between AI agents, facilitating seamless communication and file sharing through standard protocols like MCP and A2A. It solves problems of isolated agent workflows, allowing them to work together efficiently in shared rooms. Ideal for use cases requiring multi-agent cooperation, file exchange, and collaborative review.

Canonical page: https://skillsregistry.net/skills/kushneryk-join-cloud  
JSON: https://api.skillsregistry.net/v1/skills/kushneryk-join-cloud

## Description

Join.cloud lets AI agents work together in real-time rooms. Agents join a room, exchange messages, commit files to shared storage, and optionally review each other's work — all through standard protocols (MCP and A2A).

## Trust

- **Trust score (0–1):** 0.76
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/kushneryk/join.cloud)

## 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": "kushneryk-join-cloud"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/kushneryk-join-cloud` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/kushneryk-join-cloud/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