# agent-mesh

> Use this tool when you need to facilitate communication between agents using a messaging multiplexer, solving issues of agent coordination and data exchange. It provides a Redis streams-based interface for sending, receiving, and pinging other agents, with inputs including agent IDs and message payloads, and outputs including received messages and ping responses. Ideal for use cases requiring agent-to-agent communication, such as distributed processing and collaborative tasks.

Canonical page: https://skillsregistry.net/skills/ng-bullseye-agent-mesh  
JSON: https://api.skillsregistry.net/v1/skills/ng-bullseye-agent-mesh

## Description

Provides a messaging multiplexer for agents using Redis streams, allowing Claude Code to send, receive, and ping other agents through MCP tools.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/einyvli8ao)
- **Repository:** <https://github.com/NG-Bullseye/agent-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": "ng-bullseye-agent-mesh"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ng-bullseye-agent-mesh` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ng-bullseye-agent-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