Reembed Points

Snapshot Catalog Entry

This page is generated from broker tools/list snapshot data.

POSTqdrant.qdrant-reembed-points

Re-embed points when embedding version changes.

Request Body

{
  "jsonrpc": "2.0",
  "id": "qdrant-qdrant-reembed-points-example",
  "method": "tools/call",
  "params": {
    "name": "qdrant.qdrant-reembed-points",
    "arguments": {
      "collection_name": "collection_name_example",
      "point_ids": "",
      "memory_filter": "",
      "query_filter": "",
      "batch_size": 1,
      "max_points": "",
      "target_version": "",
      "recompute_text_hash": false,
      "dry_run": false,
      "confirm": false
    }
  }
}

Arguments Schema

{
  "$defs": {
    "MemoryFilterInput": {
      "additionalProperties": true,
      "properties": {
        "type": {
          "anyOf": [
            {
              "type": "string"
            },
            {
              "type": "null"
            }
          ]
        },
        "entities": {
          "anyOf": [
            {
              "items": {
                "type": "string"
              },
              "type": "array"
            },
            {
              "type": "string"
            },
            {
              "type": "null"
            }
          ]
        },
        "labels": {
          "anyOf": [
            {
              "items": {
                "type": "string"
              },
              "type": "array"
            },
            {
              "type": "string"
            },
            {
              "type": "null"
            }
          ]
        },
        "related_ids": {
          "anyOf": [
            {
              "items": {
                "type": "string"
              },
              "type": "array"
            },
            {
              "type": "string"
            },
            {
              "type": "null"
            }
          ]
        },
        "scope": {
          "anyOf": [
            {
              "type": "string"
            },
            {
              "type": "null"
            }
          ]
        },
        "source": {
          "anyOf": [
            {
              "type": "string"
            },
            {
              "type": "null"
            }
          ]
        },
        "created_at_from": {
          "anyOf": [
            {},
            {
              "type": "null"
            }
          ]
        },
        "created_at_to": {
          "anyOf": [
            {},
            {
              "type": "null"
            }
          ]
        },
        "updated_at_from": {
          "anyOf": [
            {},
            {
              "type": "null"
            }
          ]
        },
        "updated_at_to": {
          "anyOf": [
            {},
            {
              "type": "null"
            }
          ]
        },
        "expires_at_from": {
          "anyOf": [
            {},
            {
              "type": "null"
            }
          ]
        },
        "expires_at_to": {
          "anyOf": [
            {},
            {
              "type": "null"
            }
          ]
        },
        "confidence_min": {
          "anyOf": [
            {
              "type": "number"
            },
            {
              "type": "null"
            }
          ]
        },
        "confidence_max": {
          "anyOf": [
            {
              "type": "number"
            },
            {
              "type": "null"
            }
          ]
        },
        "text_hash": {
          "anyOf": [
            {
              "type": "string"
            },
            {
              "type": "null"
            }
          ]
        }
      },
      "type": "object"
    }
  },
  "properties": {
    "collection_name": {
      "type": "string"
    },
    "point_ids": {
      "anyOf": [
        {
          "items": {
            "type": "string"
          },
          "type": "array"
        },
        {
          "type": "null"
        }
      ]
    },
    "memory_filter": {
      "anyOf": [
        {
          "$ref": "#/$defs/MemoryFilterInput"
        },
        {
          "type": "null"
        }
      ]
    },
    "query_filter": {
      "anyOf": [
        {
          "additionalProperties": true,
          "type": "object"
        },
        {
          "type": "null"
        }
      ]
    },
    "batch_size": {
      "type": "integer"
    },
    "max_points": {
      "anyOf": [
        {
          "type": "integer"
        },
        {
          "type": "null"
        }
      ]
    },
    "target_version": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ]
    },
    "recompute_text_hash": {
      "type": "boolean"
    },
    "dry_run": {
      "type": "boolean"
    },
    "confirm": {
      "type": "boolean"
    }
  },
  "type": "object"
}

Code Examples

cURL

curl -X POST 'https://madpanda3d.com/lab/mad-mcps/portal/api/mcp' \
  -H 'Authorization: Bearer mad_live_***' \
  -H 'Content-Type: application/json' \
  -d '{
  "jsonrpc": "2.0",
  "id": "qdrant-qdrant-reembed-points-example",
  "method": "tools/call",
  "params": {
    "name": "qdrant.qdrant-reembed-points",
    "arguments": {
      "collection_name": "collection_name_example",
      "point_ids": "",
      "memory_filter": "",
      "query_filter": "",
      "batch_size": 1,
      "max_points": "",
      "target_version": "",
      "recompute_text_hash": false,
      "dry_run": false,
      "confirm": false
    }
  }
}'

Node.js

const response = await fetch('https://madpanda3d.com/lab/mad-mcps/portal/api/mcp', {
  method: 'POST',
  headers: {
    Authorization: 'Bearer mad_live_***',
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
  "jsonrpc": "2.0",
  "id": "qdrant-qdrant-reembed-points-example",
  "method": "tools/call",
  "params": {
    "name": "qdrant.qdrant-reembed-points",
    "arguments": {
      "collection_name": "collection_name_example",
      "point_ids": "",
      "memory_filter": "",
      "query_filter": "",
      "batch_size": 1,
      "max_points": "",
      "target_version": "",
      "recompute_text_hash": false,
      "dry_run": false,
      "confirm": false
    }
  }
}),
});
const data = await response.json();
console.log(data);

Python

import requests

url = 'https://madpanda3d.com/lab/mad-mcps/portal/api/mcp'
headers = {
    'Authorization': 'Bearer mad_live_***',
    'Content-Type': 'application/json',
}
payload = {
  "jsonrpc": "2.0",
  "id": "qdrant-qdrant-reembed-points-example",
  "method": "tools/call",
  "params": {
    "name": "qdrant.qdrant-reembed-points",
    "arguments": {
      "collection_name": "collection_name_example",
      "point_ids": "",
      "memory_filter": "",
      "query_filter": "",
      "batch_size": 1,
      "max_points": "",
      "target_version": "",
      "recompute_text_hash": false,
      "dry_run": false,
      "confirm": false
    }
  }
}
response = requests.post(url, headers=headers, json=payload, timeout=60)
print(response.json())

Example Responses

200 Success

{
  "ok": true,
  "message": "Tool qdrant.qdrant-reembed-points 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."
}