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Connectto Close, Resend, Firecrawl Web Search MCP Servers

Create powerful AI workflows by connecting multiple MCP servers including Close, Resend, Firecrawl Web Search for enhanced automation capabilities in Klavis AI.

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Close icon

Close

featured

Close is a modern CRM platform built for sales teams, providing powerful lead management, contact organization, and sales pipeline tracking to help businesses close more deals

Available Tools:

  • close_create_lead
  • close_get_lead
  • close_search_leads
  • +20 more tools
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
Firecrawl Web Search icon

Firecrawl Web Search

featured

Advanced web crawling, scraping, and search capabilities powered by Firecrawl

Available Tools:

  • firecrawl_scrape
  • firecrawl_map
  • firecrawl_crawl
  • +6 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
import google.generativeai as genai
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType, ToolFormat

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

# Constants
GEMINI_MODEL = "gemini-2.5-flash"
user_message = "Your query here"

close_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.CLOSE,
    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,
)

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

# Get tools from all MCP servers
close_tools = klavis_client.mcp_server.list_tools(
    server_url=close_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,
)
firecrawl_web_search_tools = klavis_client.mcp_server.list_tools(
    server_url=firecrawl_web_search_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)

# Combine all tools
all_tools = []
all_tools.extend(close_tools.tools)
all_tools.extend(resend_tools.tools)
all_tools.extend(firecrawl_web_search_tools.tools)

model = genai.GenerativeModel(
    model_name=GEMINI_MODEL,
    tools=all_tools
)

chat = model.start_chat()
response = chat.send_message(user_message)

Frequently Asked Questions

Everything you need to know about connecting to these MCP servers

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