Qdrant Collection Vectors

Immutable Catalog Entry

This descriptor comes from the active versioned Portal catalog.

READqdrant.qdrant-collection-vectors

• Contract tier: agent_ready
• Risk: read
• Catalog version: qdrant-2026.07.12.2
• Descriptor hash: 3e0a0779b8ec8b35d105d03165e19411562240e165cd1b81b94891d88ba05355

Use this when you need to list a collection's vector names, dimensions, and distance settings. It does not intentionally change Qdrant or MCP state. It contacts the configured Qdrant service or uses MCP-owned job/upload state. Returns normalized provider data in data plus safe request and trace metadata in meta. Requires an authenticated MAD MCP Portal request and any provider configuration named by the input schema.

Request Body

{
  "jsonrpc": "2.0",
  "id": "qdrant-qdrant-collection-vectors-example",
  "method": "tools/call",
  "params": {
    "name": "qdrant.qdrant-collection-vectors",
    "arguments": {
      "collection_name": "collection_name_example"
    }
  }
}

Arguments Schema

{
  "type": "object",
  "title": "Qdrant Collection Vectors input",
  "properties": {
    "collection_name": {
      "type": "string",
      "title": "Collection Name",
      "default": "",
      "description": "Validated collection name input used by Qdrant Collection Vectors; follow the type, limits, and defaults in this schema."
    }
  },
  "description": "Validated input contract for the qdrant-collection-vectors native Qdrant MCP tool."
}

Output Schema

{
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "data",
    "meta"
  ],
  "properties": {
    "data": {
      "type": "object",
      "description": "Normalized result data for qdrant-collection-vectors: list a collection's vector names, dimensions, and distance settings.",
      "additionalProperties": true
    },
    "meta": {
      "type": "object",
      "properties": {
        "bytes_in": {
          "type": "integer",
          "description": "Approximate serialized input byte count."
        },
        "warnings": {
          "type": "array",
          "items": {
            "type": "string"
          },
          "description": "Safe recovery warnings."
        },
        "bytes_out": {
          "type": "integer",
          "description": "Approximate serialized output byte count."
        },
        "elapsed_ms": {
          "type": "integer",
          "description": "Tool execution time in milliseconds."
        },
        "request_id": {
          "type": "string",
          "description": "Stable request trace identifier."
        },
        "server_version": {
          "type": "string",
          "description": "Deployed source revision when available."
        },
        "serialization_ms": {
          "type": "integer",
          "description": "Response serialization time in milliseconds."
        },
        "server_uptime_ms": {
          "type": "integer",
          "description": "Server process uptime in milliseconds."
        },
        "server_instance_id": {
          "type": "string",
          "description": "Ephemeral server-process identifier."
        }
      },
      "description": "Secret-safe request, trace, size, timing, and warning metadata.",
      "additionalProperties": true
    }
  },
  "description": "Qdrant MCP normalized response envelope.",
  "additionalProperties": false
}

Code Examples

cURL

curl -X POST 'https://portal.madpanda3d.com/api/mcp' \
  -H 'Authorization: Bearer mad_live_***' \
  -H 'Content-Type: application/json' \
  -d '{
  "jsonrpc": "2.0",
  "id": "qdrant-qdrant-collection-vectors-example",
  "method": "tools/call",
  "params": {
    "name": "qdrant.qdrant-collection-vectors",
    "arguments": {
      "collection_name": "collection_name_example"
    }
  }
}'

Node.js

const response = await fetch('https://portal.madpanda3d.com/api/mcp', {
  method: 'POST',
  headers: {
    Authorization: 'Bearer mad_live_***',
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
  "jsonrpc": "2.0",
  "id": "qdrant-qdrant-collection-vectors-example",
  "method": "tools/call",
  "params": {
    "name": "qdrant.qdrant-collection-vectors",
    "arguments": {
      "collection_name": "collection_name_example"
    }
  }
}),
});
const data = await response.json();
console.log(data);

Python

import requests

url = 'https://portal.madpanda3d.com/api/mcp'
headers = {
    'Authorization': 'Bearer mad_live_***',
    'Content-Type': 'application/json',
}
payload = {
  "jsonrpc": "2.0",
  "id": "qdrant-qdrant-collection-vectors-example",
  "method": "tools/call",
  "params": {
    "name": "qdrant.qdrant-collection-vectors",
    "arguments": {
      "collection_name": "collection_name_example"
    }
  }
}
response = requests.post(url, headers=headers, json=payload, timeout=60)
print(response.json())

Example Responses

200 Success

{
  "ok": true,
  "message": "Tool qdrant.qdrant-collection-vectors executed successfully.",
  "note": "Response shape varies by MCP tool. Inspect live responses for exact fields."
}

502 Upstream Error

{
  "ok": false,
  "classification": "upstream_http_error",
  "message": "Upstream MCP returned a non-success status."
}