MCPify Playground

Worked examples showing how MCPify transforms APIs into AI-ready tools — the request an agent sends, the response it gets back, and the metadata that makes it usable.

These are illustrative examples, not live traffic. They are not connected to a running MCPify deployment.

Rate-Aware API Call

See how MCPify exposes rate limit metadata to agents

REQUEST

{
  "method": "tools/call",
  "params": {
    "name": "crm.search_customers",
    "arguments": {
      "query": "enterprise",
      "limit": 10
    }
  }
}

RESPONSE

{
  "result": {
    "data": [...],
    "_meta": {
      "rate_limits": {
        "remaining": 45,
        "reset_at": "2025-08-25T10:30:00Z",
        "limit": 60
      },
      "cache": {
        "hit": false,
        "ttl": 300
      },
      "latency_ms": 127
    }
  }
}

Want to see this against your own API?

Tell us which API you want to make AI-ready and we will walk through what the generated tools would look like.

Read the guideBook a demo