Better Qdrant MCP Server

MIT License

Overview InspectNew Endpoints Schema Related Servers Reviews Score

add_documents

Upload and process documents into a Qdrant collection using specified embedding services like OpenAI or Ollama. Define text chunk size and overlap for efficient semantic search integration.

Instructions

Add documents to a Qdrant collection with specified embedding service

Input Schema

Name	Required	Description
`chunkOverlap`	No	Overlap between chunks (optional)
`chunkSize`	No	Size of text chunks (optional)
`collection`	Yes	Name of the collection to add documents to
`embeddingService`	Yes	Embedding service to use
`filePath`	Yes	Path to the file to process

Input Schema (JSON Schema)

{
  "properties": {
    "chunkOverlap": {
      "description": "Overlap between chunks (optional)",
      "type": "number"
    },
    "chunkSize": {
      "description": "Size of text chunks (optional)",
      "type": "number"
    },
    "collection": {
      "description": "Name of the collection to add documents to",
      "type": "string"
    },
    "embeddingService": {
      "description": "Embedding service to use",
      "enum": [
        "openai",
        "openrouter",
        "fastembed",
        "ollama"
      ],
      "type": "string"
    },
    "filePath": {
      "description": "Path to the file to process",
      "type": "string"
    }
  },
  "required": [
    "filePath",
    "collection",
    "embeddingService"
  ],
  "type": "object"
}

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