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Prerequisites Before you begin, create an account and get your API Key.

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Getting started

Connect to YouTube to extract video transcripts, analyze content, and automate video data processing workflows through AI agents.
  • API
  • UI
  • Open Source
1

Install the SDKs (optional)

pip install klavis
2

Create a Strata MCP Server with YouTube

from klavis import Klavis
from klavis.types import McpServerName

klavis_client = Klavis(api_key="YOUR_API_KEY")

# Create a Strata MCP server with YouTube
response = klavis_client.mcp_server.create_strata_server(
    servers=[McpServerName.YOUTUBE],
    user_id="user123"
)

API Reference

Full Strata API endpoints
🎉 Your YouTube MCP Server is ready! You can now use your MCP server URL with any MCP-compatible client.

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Available Tools

Tool NameDescription
get_youtube_video_transcriptRetrieve the transcript or video details for a given YouTube video. The ‘start’ time in the transcript is formatted as MM:SS or HH:MM:SS.
For more details about tool input schema, use the get_tools API.

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Next Steps

AI Platform Integrations

Integrate Klavis MCP Servers with leading AI platforms

Integrations

Explore available MCP servers

API Reference

REST endpoints and schemas

White-label Authentication

Customize OAuth flows with your own branding
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