# AgentRelay

> AgentRelay — arumwu-agentrelay. Use this tool when you need to coordinate multiple AI coding agents and prevent redundant work. AgentRelay enables seamless handoffs and shared context between agents, solving problems of duplicated effort and inconsistent outcomes. It accepts task assignments and file ownership as inputs and outputs coordinated decisions via MCP tools, ideal for use in collaborative coding environments.

Canonical page: https://skillsregistry.net/skills/arumwu-agentrelay  
JSON: https://api.skillsregistry.net/v1/skills/arumwu-agentrelay

## Description

A local coordination layer that enables multiple AI coding agents to share context, task leases, file ownership, and decisions via MCP tools, preventing repeated work and allowing seamless handoffs.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** productivity
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/bd3khebbod)
- **Repository:** <https://github.com/arumwu/agentrelay>

## 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": "arumwu-agentrelay"
    }
  }
}
```

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