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Save To S3

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Save To S3

Save To S3

drinksight/save-to-s3
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Designed to be run from an ACTOR.RUN.SUCCEEDED webhook, this actor downloads a task run's default dataset and saves it to an S3 bucket.

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Maintained by Community

Actor Metrics

  • 12 monthly users

  • No reviews yet

  • 3 bookmarks

  • 23% runs succeeded

  • Created in May 2019

  • Modified 2 years ago

You can access the Save To S3 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.

1# Start Server-Sent Events (SSE) session and keep it running
2curl "https://actors-mcp-server.apify.actor/sse?token=<YOUR_API_TOKEN>&actors=drinksight/save-to-s3"
3
4# Session id example output:
5# event: endpoint
6# data: /message?sessionId=9d820491-38d4-4c7d-bb6a-3b7dc542f1fa

Using Save To S3 via Model Context Protocol (MCP) server

MCP server lets you use Save To S3 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 Save To S3 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      "objectKeyFormat": "${resource.id}_${resource.startedAt}.${format}",
8      "datasetOptions": {}
9},
10    "name": "drinksight/save-to-s3"
11  }
12}'

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 Save To S3

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        "drinksight/save-to-s3"
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.