Deprecated

Pricing

$5.00/month + usage

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Weaviate Integration

Deprecated

See alternative Actors

Developed by

Datastorm

Easily integrate Apify & Weaviate Push selected fields from Apify Actor into any Weaviate class. If the Weaviate class does not exist the integration will created it. Efficient & user-friendly data handling solution.

0.0 (0)

Pricing

$5.00/month + usage

Total users

Monthly users

Last modified

2 years ago

Developer tools

Automation

You can access the Weaviate 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

{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/sse?actors=datastorm/weaviate-integration",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

Configure MCP server with Weaviate Integration

You have a few options for interacting with the MCP server:

Use mcp.apify.com via mcp-remote from your local machine to connect and authenticate using OAuth or an API token (as shown in the JSON configuration above).
Set up the connection directly in your MCP client UI by providing the URL https://mcp.apify.com/sse?actors=datastorm/weaviate-integration along with an API token (or use OAuth).
Connect to mcp.apify.com via Server-Sent Events (SSE), as shown below:

{
    "mcpServers": {
        "apify": {
            "type": "sse",
            "url": "https://mcp.apify.com/sse?actors=datastorm/weaviate-integration",
            "headers": {
                "Authorization": "Bearer <YOUR_API_TOKEN>"
            }
        }
    }
}

You can connect to the Apify MCP Server using clients like Tester MCP Client, or any other MCP client of your choice.

If you want to learn more about our Apify MCP implementation, check out our MCP documentation. To learn more about the Model Context Protocol in general, refer to the official MCP documentation or read our blog post.

Weaviate Integration

apify/weaviate-integration

This integration transfers data from Apify Actors to a Weaviate and is a good starting point for a question-answering, search, or RAG use case.

Apify

4.7

Pinecone Integration

apify/pinecone-integration

This integration transfers data from Apify Actors to a Pinecone and is a good starting point for a question-answering, search, or RAG use case.

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Kafka Integration

brasil-scrapers/kafka-integration

This integration facilitates the processing of data from an Apify dataset and its delivery to a Kafka topic. It is configured via a schema that includes details about the dataset, Kafka configuration, and batch processing size.

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Chroma Integration

apify/chroma-integration

This integration transfers data from Apify Actors to a Chroma and is a good starting point for a question-answering, search, or RAG use case.

Apify

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RabbitMQ Integration

brasil-scrapers/rabbitmq-integration

This integration processes data from an Apify dataset and delivers it to a RabbitMQ queue. It is configured via a schema that includes details about the dataset and RabbitMQ connection settings.

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OpenSearch Integration

apify/opensearch-integration

Transfer data from Apify Actors to Amazon OpenSearch Service. This Actor is a good starting point for building question-answering systems, search functionality, or Retrieval-Augmented Generation (RAG) use cases.

Apify

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Power Webhook Integration

pocesar/run-webhook-digest

Allows you to provide multiple HTTP endpoints, that receive a more complete JSON from the run, and allow you to hit those endpoints using a proxy, and enable you to do conditional webhook calls with some lines of Javascript code and you can link/chain one actor to another

Paulo Cesar

Milvus Integration

apify/milvus-integration

This integration transfers data from Apify Actors to a Milvus/Zilliz database and is a good starting point for a question-answering, search, or RAG use case.

Apify

4.5