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YouTube Summarizer

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Pay $50.00 for 1,000 videos

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YouTube Summarizer

YouTube Summarizer

piotrv1001/youtube-summarizer
Try for free

Pay $50.00 for 1,000 videos

The YouTube Summarizer extracts key insights from YouTube videos, generating concise summaries, key takeaways, sentiment analysis and actionable insights — ideal for researchers, content creators, and analysts.

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Maintained by Community

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  • >99% runs succeeded

  • Created in Feb 2025

  • Modified 15 days ago

You can access the YouTube Summarizer programmatically from your own applications by using the Apify API. You can 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
2curl https://actors-mcp-server.apify.actor/sse?token=<APIFY_TOKEN>
3
4# Session id example output:
5# event: endpoint
6# data: /message?sessionId=9d820491-38d4-4c7d-bb6a-3b7dc542f1fa

Using YouTube Summarizer via Model Context Protocol (MCP) server

MCP server lets you use YouTube Summarizer 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 YouTube Summarizer 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": {  # Actor inputs
7        "videoUrls": ...,
8        ...
9    },
10    "name": "HLdJ2U1umqEazok65"
11  }
12}'

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

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

Configure local MCP Server via standard input/output for YouTube Summarizer

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", "@apify/actors-mcp-server",
7      "--actors", "HLdJ2U1umqEazok65"
8    ],
9    "env": {
10       "APIFY_TOKEN": "YOUR_API_TOKEN"
11    }
12  }
13}
14}

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.