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Qdrant Integration

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Developed by

Apify

Transfer data from Apify Actors to a Qdrant vector database.

4.5 (2)

Pricing

Pay per usage

Monthly users

Runs succeeded

5.9%

Last modified

10 days ago

Integrations

Open source

You can access the Qdrant Integration programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

1# Start Server-Sent Events (SSE) session and keep it running
2curl "https://actors-mcp-server.apify.actor/sse?token=<YOUR_API_TOKEN>&actors=apify/qdrant-integration"
3
4# Session id example output:
5# event: endpoint
6# data: /message?sessionId=9d820491-38d4-4c7d-bb6a-3b7dc542f1fa

Using Qdrant Integration via Model Context Protocol (MCP) server

MCP server lets you use Qdrant Integration within your AI workflows. Send API requests to trigger actions and receive real-time results. Take the received sessionId and use it to communicate with the MCP server. The message starts the Qdrant Integration Actor with the provided input.

1curl -X POST "https://actors-mcp-server.apify.actor/message?token=<YOUR_API_TOKEN>&session_id=<SESSION_ID>" -H "Content-Type: application/json" -d '{
2  "jsonrpc": "2.0",
3  "id": 1,
4  "method": "tools/call",
5  "params": {
6    "arguments": {
7      "datasetFields": [
8            "text"
9      ],
10      "dataUpdatesStrategy": "deltaUpdates",
11      "dataUpdatesPrimaryDatasetFields": [
12            "url"
13      ],
14      "deltaUpdatesPrimaryDatasetFields": [
15            "url"
16      ]
17},
18    "name": "apify/qdrant-integration"
19  }
20}'

The response should be: Accepted. You should received response via SSE (JSON) as:

1event: message
2data: {
3  "result": {
4    "content": [
5      {
6        "type": "text",
7        "text": "ACTOR_RESPONSE"
8      }
9    ]
10  }
11}

Configure local MCP Server via standard input/output for Qdrant Integration

You can connect to the MCP Server using clients like ClaudeDesktop and LibreChat or build your own. The server can run both locally and remotely, giving you full flexibility. Set up the server in the client configuration as follows:

1{
2  "mcpServers": {
3    "actors-mcp-server": {
4      "command": "npx",
5      "args": [
6        "-y",
7        "@apify/actors-mcp-server",
8        "--actors",
9        "apify/qdrant-integration"
10      ],
11      "env": {
12        "APIFY_TOKEN": "<YOUR_API_TOKEN>"
13      }
14    }
15  }
16}

You can further access the MCP client through the Tester MCP Client, a chat user interface to interact with the server.

To get started, check out the documentation and example clients. If you are interested in learning more about our MCP server, check out our blog post.

Pricing

Pricing model

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage.

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144

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Takes the ID of the key-value store, archives all their keys into a zip file, and saves them into the key-value store of the actor. For more than 1000 keys, multiple zip files are created. If their total size is bigger than the actor's available memory, it creates multiple smaller zip files.