How to Use the DealMachine MCP in CrewAI

Q: How do I connect the DealMachine MCP Server to CrewAI?

Install the framework using pip install crewai "crewaitools". You can pass your Vinkius endpoint URL directly into the mcps array on your agent definition. Advanced setups should use MCPServerHTTP for granular tool filtering.

Q: Can CrewAI agents add new leads to DealMachine?

They do this natively. Assign the addnewlead tool to a specific agent in your crew. That agent will persist the address and initiate the property data resolution automatically.

Q: How do I restrict which DealMachine tools a CrewAI agent can use?

Use the toolfilter parameter when configuring the server connection. This prevents a researcher agent from accidentally triggering a marketing campaign. Role-based specialization works best when tools are strictly limited.

Deploy autonomous real estate teams. Connect DealMachine to CrewAI and let specialized agents research properties and manage campaigns.

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Connect DealMachine MCP to CrewAI

Create your Vinkius account to connect DealMachine 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 DealMachine with CrewAI

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Perplexity

Research properties with CrewAI agents

Dedicated research agents use the `get_property_details` tool to pull deed history and mortgage info. Giving a single script too many jobs usually ends poorly. This specialist focuses entirely on evaluating equity without worrying about marketing logic. A secondary investigator agent calls the `get_lead_details` tool to track down real contact information from LLCs. Finding the actual owner requires looking past the registered agent. The agents share memory, meaning the investigator already knows the address the researcher evaluated.

Run DealMachine MCP marketing operations

Manager agents watch your spend by checking credit balances with the `get_account_details` tool. Direct mail requires constant monitoring to avoid wasting money. If the balance drops too low, the manager halts the operation and alerts a human. Daily performance reports start with the `list_marketing_campaigns` tool pulling recipient counts and engagement metrics. Tracking what actually got sent is critical. An analyst agent synthesizes this raw data across the board for the team.

Automate lead generation and tagging

Vague inputs from web forms resolve into accurate property records via the `search_leads_by_address` tool. Scouting for distressed houses happens around the clock. The framework executes this sequentially before passing the clean address to the next step. Keeping the CRM clean requires a moderator agent running the `list_lead_tags` tool. It finds appropriate labels and applies them to newly resolved properties. This hierarchical execution ensures no lead enters the database untagged.

Setup guide

Set up DealMachine 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 DealMachine tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent DealMachine 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 DealMachine. 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 DealMachine MCP in CrewAI

Install the framework using pip install crewai "crewai[tools]". You can pass your Vinkius endpoint URL directly into the mcps array on your agent definition. Advanced setups should use MCPServerHTTP for granular tool filtering.

They do this natively. Assign the add_new_lead tool to a specific agent in your crew. That agent will persist the address and initiate the property data resolution automatically.

Use the tool_filter parameter when configuring the server connection. This prevents a researcher agent from accidentally triggering a marketing campaign. Role-based specialization works best when tools are strictly limited.

Yes, the integration exposes workspace metadata. An agent can call list_driving_teams to see active drivers and their roles. This helps autonomous managers assign follow-up tasks to the right human scout.

Your agents will read estimated property equity, mortgage balances, and personal owner metadata. Vinkius manages the secure connection through zero-trust ephemeral environments. No data persists on the middleware layer after the agent finishes its task.

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