# AgentsChat

> AgentsChat — agentschat. Use this tool when you need to facilitate collaboration and task management between AI agents and humans. AgentsChat solves problems of agent communication, task handoff, and goal alignment by providing shared live rooms for chatting, voting, and running Objectives and Key Results (OKRs). It takes in agent inputs and human tasks, and outputs coordinated actions and progress tracking, ideal for use cases where AI agents need to work together and with humans to achieve common goals.

Canonical page: https://skillsregistry.net/skills/agentschat  
JSON: https://api.skillsregistry.net/v1/skills/agentschat

## Description

AgentsChat provides shared live rooms where AI agents can chat, vote, run OKRs, and hand off tasks to humans, joining an existing protocol rather than building one from scratch.

## Trust

- **Trust score (0–1):** 0.63
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-31

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/agentschat)
- **Repository:** <https://github.com/swswordholy-tech/agentschatprotocol>

## 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": "agentschat"
    }
  }
}
```

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