How to Use the Pipedrive MCP in CrewAI

Q: What is the easiest way to connect CrewAI to my Pipedrive database?

Pass the Vinkius MCP server URL directly into the mcps array when defining your agents in Python.

Run autonomous teams of specialized CrewAI agents that collaborate to manage your Pipedrive sales pipeline.

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Connect Pipedrive MCP to CrewAI

Create your Vinkius account to connect Pipedrive to CrewAI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Pipedrive with CrewAI

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Run multi-agent sales teams on CrewAI

This Pipedrive MCP server lets you assign `list_sales_deals` and `search_deals_by_name` to a dedicated researcher agent while a closer agent handles updates. The agents collaborate, sharing context to move prospects through your pipeline. You configure this by passing the server URL directly in your Python Agent's `mcps` list. The framework automatically exposes the selected tools to the right agents based on their assigned roles.

Autonomous contact and organization lookup

The `list_crm_persons` and `list_crm_organizations` tools allow your research agent to profile incoming leads before sales outreach. The agent queries both tools to build a complete profile of the target account. By using `MCPServerHTTP` from the CrewAI MCP library with a `tool_filter`, you restrict your research agent to read-only tools. This ensures they can check contact details without accidentally editing existing CRM records.

Automated meeting preparation and scheduling

The `list_user_activities` tool enables an administrative agent to monitor calendar events and prepare briefs for upcoming calls. The agent scans scheduled tasks and prepares dossiers on each participant. This setup operates entirely in the background, running sequential tasks without human intervention. Your sales reps walk into every meeting with fresh, AI-generated context pulled directly from your CRM.

Setup guide

Set up Pipedrive MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Pipedrive tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Pipedrive Analyst",
    goal="Access and analyze Pipedrive data via MCP.",
    backstory="Expert analyst with direct Pipedrive access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Pipedrive transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Pipedrive Analyst",
        goal="Access and analyze Pipedrive data via MCP.",
        backstory="Expert analyst with direct Pipedrive access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Pipedrive transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Pipedrive. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Pipedrive MCP in CrewAI

Yes, you can use the tool filter option with the CrewAI MCP server. This lets you assign read tools like `get_deal_details` to a research agent while keeping write tools restricted.

Agents use CrewAI's shared memory. When one agent finds a contact using `list_crm_persons`, that data is instantly accessible to the next agent in the sequence.

Pass the Vinkius MCP server URL directly into the `mcps` array when defining your agents in Python.

Yes, a manager agent can coordinate multiple worker agents, delegating CRM tasks based on the current pipeline state.

Your deals, persons, and activities are routed through isolated, single-use containers. Vinkius uses end-to-end encryption for all MCP tool calls, meaning your CRM data is never exposed to third parties or cached on external servers.

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