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No-Code

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For Developer

Follow the instructions below to integrate YouTube MCP server to your AI application using our API or SDK.

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Prerequisites

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1. Create a YouTube MCP Server

Use the following endpoint to create a new remote YouTube MCP server instance:

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Request

from klavis import Klavis
from klavis.types import McpServerName

klavis_client = Klavis(api_key="<YOUR_API_KEY>")

# Create a YouTube MCP server instance
youtube_server = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.YOUTUBE,
    user_id="<YOUR_USER_ID>"
)

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Response

{
  "serverUrl": "https://youtube-mcp-server.klavis.ai/mcp/?instance_id=<instance-id>",
  "instanceId": "<instance-id>"
}
serverUrl specifies the endpoint of the YouTube MCP server, which you can connect and use this MCP Server to interact with YouTube data and functionality.
instanceId is used for authentication and identification of your server instance.

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Explore MCP Server Tools

For more details about tool input schema, use the list_tool API.