How to Use the MoeGo MCP in CrewAI

Q: Does CrewAI support selective tool exposure for MoeGo?

Yes. Use the toolfilter option to ensure your agents only access the specific tools they need for their assigned role.

Deploy autonomous crews of agents in CrewAI to monitor and manage your MoeGo operations without human intervention.

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Connect MoeGo MCP to CrewAI

Create your Vinkius account to connect MoeGo 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 MoeGo with CrewAI

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Autonomous Scheduling Crews in CrewAI

Assign specialized agents to handle different parts of the grooming cycle. One agent monitors `list_appointments` while another acts on `create_appointment`. This creates a collaborative team that manages your business. They share context, allowing them to make informed decisions about your schedule.

Role-Based MoeGo Management

Give your moderator agent access to `list_staff` and `list_services` to handle resource allocation. The agent balances the workload based on actual business data. This removes the need for manual oversight. Your crew continuously checks for gaps and optimizes the calendar as new requests arrive.

Shared Memory for Grooming Operations

Use the shared memory feature to keep agents updated on pet history fetched via `get_pet`. The entire crew benefits from the data retrieved by a single agent. This prevents redundant tool calls. Your agents stay efficient, and your business operations run smoother by avoiding duplicate queries.

Setup guide

Set up MoeGo 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 MoeGo tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent MoeGo 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 MoeGo. 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.

Why Choose Vinkius

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Common questions about MoeGo MCP in CrewAI

Simply pass the server URL in your agent configuration. The agents will automatically gain access to the tools you specify.

Yes. Agents share context and memory, allowing one to research customer needs while another executes the final booking.

Yes. Use the tool_filter option to ensure your agents only access the specific tools they need for their assigned role.

The server runs in a secure sandbox. Only the agent currently executing a task can access the pet or customer records required for that step.

Yes. You can build a monitor agent that triggers an alert if it detects conflicting appointments or missing staff information.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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Pydantic AI sdk-python

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Mastra AI sdk-typescript

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