Connectto Close, Dropbox, QuickBooks MCP Servers

Create powerful AI workflows by connecting multiple MCP servers including Close, Dropbox, QuickBooks for enhanced automation capabilities in Klavis AI.

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
Dropbox icon

Dropbox

featured

Complete file management solution for Dropbox cloud storage. Upload, download, organize files and folders, manage sharing and collaboration, handle file versions, create file requests, and perform batch operations on your Dropbox files and folders

Available Tools:

  • dropbox_list_folder
  • dropbox_continue_folder_listing
  • dropbox_create_folder
  • +40 more tools
QuickBooks icon

QuickBooks

featured

QuickBooks is a comprehensive accounting software solution that helps small and medium businesses manage their finances, track expenses, create invoices, manage payroll, and generate financial reports with integrated banking and tax preparation features

Available Tools:

  • create_account
  • get_account
  • list_accounts
  • +32 more tools

Quick Setup Guide

Follow these steps to connect LangChain 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 LangChain and configure authentication settings.

3

Test & Deploy

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

LangChain + KlavisAI Integration Snippets

import os
import asyncio
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType
from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

# Initialize clients
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))
llm = ChatOpenAI(model="gpt-4o-mini", api_key=os.getenv("OPENAI_API_KEY"))

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,
)

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

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

mcp_client = MultiServerMCPClient({
    "close": {
        "transport": "streamable_http",
        "url": close_mcp_instance.server_url
    },
    "dropbox": {
        "transport": "streamable_http",
        "url": dropbox_mcp_instance.server_url
    },
    "quickbooks": {
        "transport": "streamable_http",
        "url": quickbooks_mcp_instance.server_url
    }
})

tools = asyncio.run(mcp_client.get_tools())

agent = create_react_agent(
    model=llm,
    tools=tools,
)

response = asyncio.run(agent.ainvoke({
    "messages": [{"role": "user", "content": "Your query here"}]
}))

Frequently Asked Questions

Everything you need to know about connecting to these MCP servers

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