Connectto Gong, OneDrive MCP Servers

Create powerful collaborative AI workflows by connecting multiple MCP servers including Gong, OneDrive for enhanced multi-agent automation capabilities in Klavis AI.

Gong icon

Gong

featured

Gong is a revenue intelligence platform that captures and analyzes all revenue-related interactions to help sales teams close more deals. It provides conversation analytics, deal insights, and sales performance tracking through call recordings and transcripts

Available Tools:

  • gong_get_transcripts_by_user
  • gong_get_extensive_data
  • gong_get_call_transcripts
  • +2 more tools
OneDrive icon

OneDrive

coming soon

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

Quick Setup Guide

Follow these steps to connect CrewAI to these MCP servers

1

Create Your Account

Sign up for KlavisAI to access our MCP server management platform.

2

Configure Agents & Tools

Set up your CrewAI agents with your desired MCP servers tools and configure authentication settings for collaborative workflows.

3

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"))

gong_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.GONG,
    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,
)

# Initialize MCP tools for each server
gong_tools = MCPServerAdapter(gong_mcp_instance.server_params)
onedrive_tools = MCPServerAdapter(onedrive_mcp_instance.server_params)

# Create specialized agents for each service
gong_agent = Agent(
    role="Gong Specialist",
    goal="Handle all Gong related tasks and data processing",
    backstory="You are an expert in Gong operations and data analysis",
    tools=gong_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
)

# 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=gong_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=[gong_agent, onedrive_agent],
    tasks=[research_task, analysis_task],
    verbose=False,
    process=Process.sequential
)

result = multi_agent_crew.kickoff()

Frequently Asked Questions

Everything you need to know about connecting CrewAI to these MCP servers

Ready to Get Started?

Join developers who are already using KlavisAI to power their CrewAI multi-agent systems with these MCP servers.

Start For Free