Connectto Cloudflare, Resend, GitHub MCP Servers

Create powerful collaborative AI workflows by connecting multiple MCP servers including Cloudflare, Resend, GitHub for enhanced multi-agent automation capabilities in Klavis AI.

Cloudflare icon

Cloudflare

featured

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
GitHub icon

GitHub

featured

Enhanced GitHub MCP Server

Available Tools:

  • github_get_me
  • github_get_issue
  • github_search_issues
  • +31 more tools

Quick Setup Guide

Follow these steps to connect CrewAI to these MCP servers

1

Create Your Account

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

2

Configure Agents & Tools

Set up your CrewAI agents with your desired MCP servers tools and configure authentication settings for collaborative workflows.

3

Deploy Your Crew

Test your multi-agent workflows and start using your enhanced collaborative AI capabilities.

CrewAI + KlavisAI Integration Snippets

import os
from crewai import Agent, Task, Crew, Process
from crewai_tools import MCPServerAdapter
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType

# Initialize clients
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))

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,
)

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

# Initialize MCP tools for each server
cloudflare_tools = MCPServerAdapter(cloudflare_mcp_instance.server_params)
resend_tools = MCPServerAdapter(resend_mcp_instance.server_params)
github_tools = MCPServerAdapter(github_mcp_instance.server_params)

# Create specialized agents for each service
cloudflare_agent = Agent(
    role="Cloudflare Specialist",
    goal="Handle all Cloudflare related tasks and data processing",
    backstory="You are an expert in Cloudflare operations and data analysis",
    tools=cloudflare_tools,
    reasoning=True,
    verbose=False
)

resend_agent = Agent(
    role="Resend Specialist",
    goal="Handle all Resend related tasks and data processing",
    backstory="You are an expert in Resend operations and data analysis",
    tools=resend_tools,
    reasoning=True,
    verbose=False
)

github_agent = Agent(
    role="GitHub Specialist",
    goal="Handle all GitHub related tasks and data processing",
    backstory="You are an expert in GitHub operations and data analysis",
    tools=github_tools,
    reasoning=True,
    verbose=False
)

# Define collaborative tasks
research_task = Task(
    description="Gather comprehensive data from all available sources",
    expected_output="Raw data and initial findings from all services",
    agent=cloudflare_agent,
    markdown=True
)

analysis_task = Task(
    description="Analyze and synthesize the gathered data",
    expected_output="Comprehensive analysis with insights and recommendations",
    agent=resend_agent,
    markdown=True
)

# Create multi-agent crew
multi_agent_crew = Crew(
    agents=[cloudflare_agent, resend_agent, github_agent],
    tasks=[research_task, analysis_task],
    verbose=False,
    process=Process.sequential
)

result = multi_agent_crew.kickoff()

Frequently Asked Questions

Everything you need to know about connecting CrewAI to these MCP servers

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