How to Use the Keap MCP in CrewAI

Q: How do I expose Keap tools to my CrewAI agents?

Pass the Vinkius URL directly into the mcps array on your Agent definition. For more control, use MCPServerHTTP to filter which tools specific agents can see.

Q: Can I restrict a CrewAI agent to only read Keap data?

Yes. Use the toolfilter parameter when setting up the server connection. Give the research agent access to search features while blocking it from creating records.

Deploy autonomous multi-agent teams in CrewAI to manage your Keap CRM and campaigns.

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Connect Keap MCP to CrewAI

Create your Vinkius account to connect Keap 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 Keap with CrewAI

Ask AI about this MCP

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Perplexity

Assign agents to analyze Keap marketing campaigns

`list_campaigns` pulls the active promotional sequences running in your account. You assign a specialized marketing agent to read the campaign data and evaluate performance metrics through the MCP server. A secondary agent then uses `list_tags` to cross-reference which customer segments are receiving those emails. The crew works hierarchically, with a manager agent deciding if the current strategy requires adjustment.

Automate lead routing via an intelligent MCP Server

`list_opportunities` grabs every open deal in your sales pipeline. A triage agent reviews the deal size and stage, then determines which sales rep should take over. To find the right rep, the agent calls `list_users` to see who is available in your application. The system operates entirely without human intervention, routing high-value leads to senior staff automatically.

Research business profiles and contact history

`get_business_profile` retrieves your core company configuration before the crew starts executing outbound tasks. The agents understand your business context before they draft a single message. When interacting with a specific lead, a research agent runs `get_contact` to read their history. The agents share this memory natively, so the response agent knows exactly what the lead asked three days ago.

Setup guide

Set up Keap 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 Keap tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Pass the Vinkius URL directly into the `mcps` array on your Agent definition. For more control, use `MCPServerHTTP` to filter which tools specific agents can see.

Yes. Use the `tool_filter` parameter when setting up the server connection. Give the research agent access to search features while blocking it from creating records.

The framework supports standard input/output, Server-Sent Events, and Streamable HTTP. You choose the transport based on how you deploy your Python environment.

Yes. When one agent pulls a list of users, that data enters the crew's shared memory. The next agent in the sequence can act on that information immediately.

The server handles sensitive promotional campaigns and internal user lists. Vinkius secures this by offloading the OAuth complexity and executing every request inside a stateless sandbox that leaves no persistent storage behind.

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