How to Use the MoonClerk MCP in CrewAI

Q: How do I configure MoonClerk for my CrewAI agents?

You pass the server URL directly into the agent's mcps parameter. The agents then gain access to the full suite of MoonClerk tools for their tasks.

Build autonomous payment monitoring teams in CrewAI with this integrated MoonClerk MCP server.

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Connect MoonClerk MCP to CrewAI

Create your Vinkius account to connect MoonClerk 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 MoonClerk with CrewAI

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Perplexity

Specialized agents for MoonClerk monitoring

Assign a monitoring agent to watch `list_payments` while a separate moderator agent handles customer inquiries. CrewAI lets them share memory so they never duplicate work. This setup creates a feedback loop. One agent finds the issue, and the other resolves it using the appropriate tool.

Autonomous coupon management

Give your research agent access to `list_coupons` to audit your current promotions. It can report on which codes are active without you opening the dashboard. This frees up your time for strategy. The agent handles the data collection and summarizes the findings for your team.

Payment detail retrieval at scale

Use `get_payment` within a hierarchical crew structure to investigate specific transactions. The executive agent delegates the deep dive to an analyst agent. This ensures your senior agents stay focused on high-level decisions. The specialized agents handle the technical data retrieval.

Setup guide

Set up MoonClerk 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 MoonClerk tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

You pass the server URL directly into the agent's `mcps` parameter. The agents then gain access to the full suite of MoonClerk tools for their tasks.

Yes. Use the tool filter feature to limit access. You can provide only `list_payments` to your research agent while keeping `get_customer` for your support agent.

They use shared memory buffers to store results. If one agent fetches a customer record, the entire crew can reference that data in subsequent steps.

Data is handled via ephemeral memory sessions. Once the task finishes, the agent context clears, leaving no trace of the processed payment details.

You can wrap your crew execution in a cron job or script. The agents will wake up, query the tools, and perform their assigned operations automatically.

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