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Connectto Cloudflare, Resend, Plai MCP Servers

Create powerful AI workflows by connecting multiple MCP servers including Cloudflare, Resend, Plai for enhanced automation capabilities in Klavis AI.

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Cloudflare icon

Cloudflare

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Cloudflare provides content delivery network services, DDoS protection, and security.

Resend icon

Resend

featured

Resend is a modern email API for sending and receiving emails programmatically

Available Tools:

  • resend_send_email
  • resend_create_audience
  • resend_get_audience
  • +12 more tools
Plai icon

Plai

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Plai is an AI-powered advertising platform that simplifies creating, managing, and optimizing Facebook, Instagram, and LinkedIn ad campaigns. It provides tools for lead generation, campaign insights, and automated ad management to help businesses scale their digital marketing efforts effectively.

Available Tools:

  • plai_create_user_profile
  • plai_get_user_profile
  • plai_create_link
  • +7 more tools

Quick Setup Guide

Follow these steps to connect Google Gemini to these MCP servers

1

Create Your Account

Sign up for KlavisAI to access our MCP server management platform.

2

Configure Connections

Add your desired MCP servers to Gemini and configure authentication settings.

3

Test & Deploy

Verify your connections work correctly and start using your enhanced AI capabilities.

Google Gemini + KlavisAI Integration Snippets

View Documentation
import os
from google import genai
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType, ToolFormat

# Initialize clients
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))
client = genai.Client(api_key=os.getenv("GOOGLE_API_KEY"))

user_message = "Your query here"

cloudflare_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.CLOUDFLARE,
    user_id="1234",
    platform_name="Klavis",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

resend_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.RESEND,
    user_id="1234",
    platform_name="Klavis",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

plai_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.PLAI,
    user_id="1234",
    platform_name="Klavis",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

# Get tools from all MCP servers
cloudflare_tools = klavis_client.mcp_server.list_tools(
    server_url=cloudflare_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)
resend_tools = klavis_client.mcp_server.list_tools(
    server_url=resend_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)
plai_tools = klavis_client.mcp_server.list_tools(
    server_url=plai_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)

# Combine all tools
all_tools = []
all_tools.extend(cloudflare_tools.tools)
all_tools.extend(resend_tools.tools)
all_tools.extend(plai_tools.tools)

response = client.models.generate_content(
    model="gemini-2.5-flash",
    contents=user_message,
    config=genai.types.GenerateContentConfig(
        tools=all_tools,
    ),
)

Frequently Asked Questions

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