# DeskCrew

> Use this tool when you need to automate support ticket management and streamline customer service workflows. DeskCrew solves problems related to manual ticket handling, providing a scalable and cost-effective solution that pays per action in USDC. It accepts support tickets as input and outputs resolved issues, making it ideal for businesses looking to optimize their helpdesk operations.

Canonical page: https://skillsregistry.net/skills/io-deskcrew-support  
JSON: https://api.skillsregistry.net/v1/skills/io-deskcrew-support

## Description

Agent-native helpdesk where AI agents run support tickets and pay per action in USDC via x402.

## 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/io.deskcrew%2Fsupport)

## Use it

MCP endpoint published by the skill: `https://deskcrew.io/api/mcp/{tenant_slug}`

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": "io-deskcrew-support"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/io-deskcrew-support` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/io-deskcrew-support/pull`

---
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