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Connectto Asana, QuickBooks, Mem0 MCP Servers

Create powerful AI workflows by connecting multiple MCP servers including Asana, QuickBooks, Mem0 for enhanced automation capabilities in Klavis AI.

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Asana icon

Asana

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Asana is a web and mobile application designed to help teams organize, track, and manage their work. It provides project management tools, task assignment, collaboration features, and progress tracking to boost team productivity

Available Tools:

  • asana_create_task
  • asana_get_task
  • asana_search_tasks
  • +16 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
Mem0 icon

Mem0

featured

Mem0 is an intelligent memory layer for AI applications that provides long-term memory storage and retrieval. Store code snippets, implementation details, and programming knowledge for seamless context retention across conversations

Available Tools:

  • mem0_add_memory
  • mem0_get_all_memories
  • mem0_search_memories
  • +2 more tools

Quick Setup Guide

Follow these steps to connect your AI agents 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 your AI client and configure authentication settings.

3

Test & Deploy

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

Integrate in minutes, Scale to millions

View Documentation
from klavis import Klavis

klavis_client = Klavis(api_key="KLAVIS_API_KEY")

servers = ["Asana", "QuickBooks", "Mem0"]
responses = []

for server in servers:
    mcp_server = klavis_client.mcp_server.create_server_instance(
        server_name=server,
        user_id="<USER_ID>",
        platform_name="<PLATFORM_NAME>"
    )
    responses.append(mcp_server)

Frequently Asked Questions

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