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Connectto Attio, OneDrive, Mem0 MCP Servers

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

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Attio icon

Attio

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Attio is a next-generation CRM platform that helps teams build stronger relationships with their customers through powerful data management and automation

Available Tools:

  • attio_search_people
  • attio_search_companies
  • attio_search_deals
  • +2 more tools
OneDrive icon

OneDrive

featured

OneDrive is a file hosting service and synchronization service operated by Microsoft

Available Tools:

  • onedrive_rename_item
  • onedrive_move_item
  • onedrive_delete_item
  • +9 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 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"

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

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

mem0_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.MEM0,
    user_id="1234",
    platform_name="Klavis",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

# Get tools from all MCP servers
attio_tools = klavis_client.mcp_server.list_tools(
    server_url=attio_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)
onedrive_tools = klavis_client.mcp_server.list_tools(
    server_url=onedrive_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)
mem0_tools = klavis_client.mcp_server.list_tools(
    server_url=mem0_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)

# Combine all tools
all_tools = []
all_tools.extend(attio_tools.tools)
all_tools.extend(onedrive_tools.tools)
all_tools.extend(mem0_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

Everything you need to know about connecting to these MCP servers

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