How to Use the Berg System CRM MCP in CrewAI

Q: How do CrewAI agents collaborate on Berg System CRM opportunities?

One agent can run listsalesopportunities to identify high-value deals. It then passes that structured data to a second agent, which uses getcustomerdetails to prepare a personalized pitch.

Deploy specialized agent teams using CrewAI to manage your Berg System CRM pipelines and customer records.

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Connect Berg System CRM MCP to CrewAI

Create your Vinkius account to connect Berg System CRM to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Berg System CRM with CrewAI

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Coordinate multi-agent sales research with CrewAI

`list_crm_customers` acts as the primary data source for your CrewAI research agent to analyze client profiles. A separate CrewAI analyst agent then takes this output and cross-references it with active Berg System CRM files to identify cross-selling opportunities. This collaborative workflow runs autonomously, delivering finished briefs directly to your inbox. Because CrewAI supports shared memory, the agents remember previous query results throughout the execution block. This reduces redundant calls to the Berg System CRM MCP Server, keeping your API usage efficient.

Automate policy audits using this MCP Server

`list_insurance_policies` provides your CrewAI audit agent with the raw policy data needed to check for coverage gaps. The CrewAI agent matches active policies against current financial regulations to flag any compliance issues. A separate coordinator agent then schedules follow-up tasks for the account manager if discrepancies are found. If the CrewAI audit agent needs to review original contracts, it calls `list_stored_documents` to find the relevant attachments. This multi-step process requires no human intervention, freeing up your compliance team for higher-value work.

Delegate task management to specialized agents

`list_crm_tasks` lets a CrewAI coordinator agent monitor the team's pending deadlines. If a critical follow-up is overdue, the agent assigns a subtask to a researcher agent to gather the necessary background information from Berg System CRM. This hierarchical execution model ensures that complex client requests are handled systematically. When the CrewAI researcher agent finishes, the coordinator can call `get_customer_details` to verify that all client records are fully updated before closing the loop. Your advisor team gets automated updates without having to manually dig through the Berg System CRM.

Setup guide

Set up Berg System CRM 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 Berg System CRM tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Berg System CRM 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="Berg System CRM Analyst",
        goal="Access and analyze Berg System CRM data via MCP.",
        backstory="Expert analyst with direct Berg System CRM access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Berg System CRM 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 Berg System. 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 Berg System CRM MCP in CrewAI

Pass the Vinkius HTTP URL into the mcps list when defining your CrewAI agent. The framework automatically detects the MCP Server and exposes the tools to that specific agent.

Yes. Use the MCPServerHTTP class from the crewai.mcp package and apply a tool filter to the MCP Server. This restricts the agent to specific operations like list_crm_tasks while blocking write access.

One agent can run list_sales_opportunities to identify high-value deals. It then passes that structured data to a second agent, which uses get_customer_details to prepare a personalized pitch.

The server supports stdio, SSE, and Streamable HTTP transports. For most multi-agent deployments, the standard HTTP transport provided by Vinkius is the easiest to configure.

Yes, because Vinkius executes all server tools in secure, ephemeral V8 isolates. Your sensitive sales opportunities and customer records are processed in memory and never written to persistent storage.

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