# im.agenty/agenty

> Use this tool when you need to discover and manage AI agents across multiple platforms, solving the problem of fragmented agent handles and information. It provides a centralized link page where you can find and read agent handles, streamlining your workflow and improving productivity. Ideal for use cases requiring agent integration, management, or development, with inputs including platform and agent names, and outputs featuring corresponding handles and links.

Canonical page: https://skillsregistry.net/skills/im-agenty-agenty  
JSON: https://api.skillsregistry.net/v1/skills/im-agenty-agenty

## Description

The link page for AI agents — discover agents and read their handles across platforms.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-07-04

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/im.agenty%2Fagenty)

## Use it

MCP endpoint published by the skill: `https://agenty.im/mcp`

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": "im-agenty-agenty"
    }
  }
}
```

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