Connectto Gmail, OneDrive, Mem0 MCP Servers
Create powerful collaborative AI workflows by connecting multiple MCP servers including Gmail, OneDrive, Mem0 for enhanced multi-agent automation capabilities in Klavis AI.
Gmail
Gmail is a free email service provided by Google
Available Tools:
- gmail_send_email
- gmail_draft_email
- gmail_read_email
- +5 more tools
OneDrive
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
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 CrewAI to these MCP servers
Create Your Account
Sign up for KlavisAI to access our MCP server management platform.
Configure Agents & Tools
Set up your CrewAI agents with your desired MCP servers tools and configure authentication settings for collaborative workflows.
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"))
gmail_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.GMAIL,
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,
)
# Initialize MCP tools for each server
gmail_tools = MCPServerAdapter(gmail_mcp_instance.server_params)
onedrive_tools = MCPServerAdapter(onedrive_mcp_instance.server_params)
mem0_tools = MCPServerAdapter(mem0_mcp_instance.server_params)
# Create specialized agents for each service
gmail_agent = Agent(
role="Gmail Specialist",
goal="Handle all Gmail related tasks and data processing",
backstory="You are an expert in Gmail operations and data analysis",
tools=gmail_tools,
reasoning=True,
verbose=False
)
onedrive_agent = Agent(
role="OneDrive Specialist",
goal="Handle all OneDrive related tasks and data processing",
backstory="You are an expert in OneDrive operations and data analysis",
tools=onedrive_tools,
reasoning=True,
verbose=False
)
mem0_agent = Agent(
role="Mem0 Specialist",
goal="Handle all Mem0 related tasks and data processing",
backstory="You are an expert in Mem0 operations and data analysis",
tools=mem0_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=gmail_agent,
markdown=True
)
analysis_task = Task(
description="Analyze and synthesize the gathered data",
expected_output="Comprehensive analysis with insights and recommendations",
agent=onedrive_agent,
markdown=True
)
# Create multi-agent crew
multi_agent_crew = Crew(
agents=[gmail_agent, onedrive_agent, mem0_agent],
tasks=[research_task, analysis_task],
verbose=False,
process=Process.sequential
)
result = multi_agent_crew.kickoff()Frequently Asked Questions
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