How to Use the Leal MCP in CrewAI

Deploy autonomous loyalty crews using the Leal MCP Server and CrewAI multi-agent teams.

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Connect Leal MCP to CrewAI

Create your Vinkius account to connect Leal 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 Leal with CrewAI

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Perplexity

Specialized loyalty crews

Assign a researcher agent to `list_transactions` and an analyst agent to `get_member_balance`. They work together to spot churn risks before they happen. This removes the need for you to dig through logs. Your crew identifies the patterns and flags them for you to review.

Autonomous store monitoring

Task your crew with `list_stores` and `get_store` to track performance across your retail footprint. Agents report back when store activity deviates from the norm. You keep eyes on your entire operation at all times. It is like having a fleet of analysts working around the clock.

Collaborative reward management

Use `list_rewards` as a shared knowledge base for your agents. One agent suggests offers, and another validates them against the current member balance. This prevents your agents from suggesting invalid rewards to your users. They coordinate to ensure every recommendation is accurate and actionable.

Setup guide

Set up Leal 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 Leal tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Leal 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 →

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Common questions about Leal MCP in CrewAI

You define roles for each agent and grant them access to specific tools. This ensures your research agents focus on data retrieval while your action agents handle member updates.

Yes, CrewAI provides shared memory between agents. Once one agent retrieves a member's profile via `get_member`, the rest of the crew can act on that information.

It is straightforward—pass the server URL directly into your agent configuration. You can filter tools to limit what each agent can do for better control.

The server provides access to member names, point balances, and detailed transaction histories. This data allows your agents to build a complete picture of customer loyalty.

Your endpoint token strictly scopes the data access for your agents. The system is designed to keep member transaction records isolated and inaccessible to unauthorized processes.

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