# agentmesh

> agentmesh — cerbug45-agentmesh. Use this tool when you need to securely communicate between AI agents, leveraging WhatsApp-style end-to-end encrypted messaging to protect sensitive information and ensure private interactions. It solves problems related to data privacy and security in AI agent communications, enabling trusted exchanges of information. Ideal for use cases requiring high confidentiality and integrity of data, such as secure multi-agent collaborations or private data sharing.

Canonical page: https://skillsregistry.net/skills/cerbug45-agentmesh  
JSON: https://api.skillsregistry.net/v1/skills/cerbug45-agentmesh

## Description

> **WhatsApp-style end-to-end encrypted messaging for AI agents.**.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-05-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** communication
- **Updated:** 2026-09-13

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/cerbug45-agentmesh)

## 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": "cerbug45-agentmesh"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/cerbug45-agentmesh` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/cerbug45-agentmesh/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