Ingest Document

Immutable Catalog + Curated Guide

This lossless descriptor comes from the active Portal catalog and is enhanced with reviewed examples.

WRITEqdrant.qdrant-ingest-document

Contract tier: agent_ready
Risk: write
Catalog version: qdrant-2026.07.12.2
Descriptor hash: 8fab19032b5d43819fa206e49283d46166a8bc2c9620cfb341980b41ae8532f6

Ingest general documents/content (document workflow) from source URL or inline text.

Request Body

{
  "jsonrpc": "2.0",
  "id": "qdrant-qdrant-ingest-document-example",
  "method": "tools/call",
  "params": {
    "name": "qdrant.qdrant-ingest-document",
    "arguments": {
      "collection_name": "school",
      "source_url": "https://files.example.com/course-rubric.pdf",
      "file_name": "course-rubric.pdf",
      "file_type": "pdf",
      "chunk_size": 1200,
      "chunk_overlap": 150,
      "metadata": {
        "class": "COM120",
        "material_type": "rubric"
      }
    }
  }
}

Arguments Schema

{
  "type": "object",
  "title": "Qdrant Ingest Document input",
  "required": [
    "collection_name"
  ],
  "properties": {
    "ocr": {
      "type": "boolean",
      "title": "Ocr",
      "default": true,
      "description": "Enable OCR for PDF extraction (default: true)."
    },
    "text": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Text",
      "default": null,
      "description": "Raw text content (for txt/md uploads)."
    },
    "doc_id": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Doc Id",
      "default": null,
      "description": "Document id for update/delete workflows."
    },
    "metadata": {
      "anyOf": [
        {
          "type": "object",
          "additionalProperties": true
        },
        {
          "type": "null"
        }
      ],
      "title": "Metadata",
      "default": null,
      "description": "Base memory metadata overrides (type, entities, source, scope, confidence, etc.)."
    },
    "doc_title": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Doc Title",
      "default": null,
      "description": "Document title stored with each chunk."
    },
    "file_name": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "File Name",
      "default": null,
      "description": "Original file name (used to infer file type and title)."
    },
    "file_type": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "File Type",
      "default": null,
      "description": "File type/extension: txt, md, csv, pdf, doc, docx."
    },
    "mime_type": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Mime Type",
      "default": null,
      "description": "Optional MIME type for file type inference."
    },
    "chunk_size": {
      "anyOf": [
        {
          "type": "integer"
        },
        {
          "type": "null"
        }
      ],
      "title": "Chunk Size",
      "default": null,
      "description": "Chunk size in characters (defaults to MCP_MAX_TEXT_LENGTH)."
    },
    "source_url": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Source Url",
      "default": null,
      "description": "HTTP(S) URL or upload:// URI returned by qdrant-finish-file-upload."
    },
    "chunk_overlap": {
      "anyOf": [
        {
          "type": "integer"
        },
        {
          "type": "null"
        }
      ],
      "title": "Chunk Overlap",
      "default": null,
      "description": "Chunk overlap in characters (default 200)."
    },
    "dedupe_action": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Dedupe Action",
      "default": null,
      "description": "How to handle existing doc_id: update or skip. Defaults to MCP_DEDUPE_ACTION."
    },
    "content_base64": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Content Base64",
      "default": null,
      "description": "Base64-encoded file content."
    },
    "collection_name": {
      "type": "string",
      "title": "Collection Name",
      "description": "The collection to store the document in"
    },
    "return_chunk_ids": {
      "type": "boolean",
      "title": "Return Chunk Ids",
      "default": false,
      "description": "Return IDs for the stored chunks."
    },
    "source_url_headers": {
      "anyOf": [
        {
          "type": "object",
          "additionalProperties": {
            "type": "string"
          }
        },
        {
          "type": "null"
        }
      ],
      "title": "Source Url Headers",
      "default": null,
      "description": "Optional headers to use when fetching source_url (e.g., User-Agent, Authorization)."
    }
  },
  "description": "Validated input contract for the qdrant-ingest-document 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-ingest-document: extract, chunk, embed, and store a supported document source.",
      "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
Node.js
Python

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-ingest-document-example",
  "method": "tools/call",
  "params": {
    "name": "qdrant.qdrant-ingest-document",
    "arguments": {
      "collection_name": "school",
      "source_url": "https://files.example.com/course-rubric.pdf",
      "file_name": "course-rubric.pdf",
      "file_type": "pdf",
      "chunk_size": 1200,
      "chunk_overlap": 150,
      "metadata": {
        "class": "COM120",
        "material_type": "rubric"
      }
    }
  }
}'

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-ingest-document-example",
  "method": "tools/call",
  "params": {
    "name": "qdrant.qdrant-ingest-document",
    "arguments": {
      "collection_name": "school",
      "source_url": "https://files.example.com/course-rubric.pdf",
      "file_name": "course-rubric.pdf",
      "file_type": "pdf",
      "chunk_size": 1200,
      "chunk_overlap": 150,
      "metadata": {
        "class": "COM120",
        "material_type": "rubric"
      }
    }
  }
}),
});
const data = await response.json();
console.log(data);

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-ingest-document-example",
  "method": "tools/call",
  "params": {
    "name": "qdrant.qdrant-ingest-document",
    "arguments": {
      "collection_name": "school",
      "source_url": "https://files.example.com/course-rubric.pdf",
      "file_name": "course-rubric.pdf",
      "file_type": "pdf",
      "chunk_size": 1200,
      "chunk_overlap": 150,
      "metadata": {
        "class": "COM120",
        "material_type": "rubric"
      }
    }
  }
}
response = requests.post(url, headers=headers, json=payload, timeout=60)
print(response.json())

Example Responses

200 Success
422 Validation Error

{
  "ok": true,
  "chunksIngested": 124,
  "collection": "school"
}

{
  "ok": false,
  "error_code": "validation_error",
  "suggested_http_status": 422,
  "stage": "submit",
  "message": "collection_name is required"
}

Request Body​

Arguments Schema​

Output Schema​

Code Examples​

Example Responses​

Request Body

Arguments Schema

Output Schema

Code Examples

Example Responses