# agentos-mesh

> agentos-mesh — agentossoftware-agentos-mesh. Use this tool when you need to facilitate seamless interaction between AI agents, enabling real-time data exchange and collaborative decision-making. Agentos-mesh solves problems of agent isolation, delayed communication, and limited coordination, making it ideal for applications requiring synchronized AI actions. It accepts agent IDs and message inputs, producing output streams that update agents in real-time, and is particularly useful in contexts like multi-agent systems, distributed AI, and real-time control systems.

Canonical page: https://skillsregistry.net/skills/agentossoftware-agentos-mesh  
JSON: https://api.skillsregistry.net/v1/skills/agentossoftware-agentos-mesh

## Description

Enables real-time communication between AI agents.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

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

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/agentossoftware-agentos-mesh)

## 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": "agentossoftware-agentos-mesh"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/agentossoftware-agentos-mesh` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/agentossoftware-agentos-mesh/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