Connectto Pipedrive MCP Server

Seamlessly integrate your CrewAI multi-agent systems with Pipedrive using Klavis AI's comprehensive MCP server connection guide.

Pipedrive icon

Pipedrive

featured

Pipedrive is a sales CRM and pipeline management tool. Manage deals, contacts, organizations, activities, and track your sales pipeline via OpenAPI integration

Quick Setup Guide

Follow these steps to connect CrewAI to this MCP server

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 the MCP server 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"))

pipedrive_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.PIPEDRIVE,
    user_id="1234",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

with MCPServerAdapter(pipedrive_mcp_instance.server_params) as mcp_tools:
    # Create a Pipedrive Analysis Agent
    pipedrive_agent = Agent(
        role="Pipedrive Analyst",
        goal="Research and analyze pipedrive to extract comprehensive insights",
        backstory="You are an expert at analyzing pipedrive and creating professional summaries.",
        tools=mcp_tools,
        reasoning=True,
        verbose=False
    )
    
    # Define Task
    analysis_task = Task(
        description=f"Research and analyze pipedrive data. Extract relevant information and create a comprehensive summary with key points and main takeaways.",
        expected_output="Complete analysis with structured summary, key insights, and main takeaways",
        agent=pipedrive_agent,
        markdown=True
    )
    
    # Create and execute the crew
    pipedrive_crew = Crew(
        agents=[pipedrive_agent],
        tasks=[analysis_task],
        verbose=False,
        process=Process.sequential
    )
    
    result = pipedrive_crew.kickoff()

Frequently Asked Questions

Everything you need to know about connecting CrewAI to this MCP server

Ready to Get Started?

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

Start For Free