How to Use the Finmo MCP in CrewAI

Q: How do I assign Finmo tools to specific CrewAI agents?

Pass the specific tool list to the mcps argument in your agent definition. You can isolate createpayout to a single 'Treasurer' agent.

Q: Can CrewAI agents share Finmo data?

Yes. Shared memory allows agents to pass findings from listcustomers to the agent responsible for initiating a payout.

Q: Does Finmo require custom CrewAI configurations?

You can use the standard MCPServerHTTP transport. It works out of the box with your existing crew setup.

Deploy a specialized crew of agents to manage your Finmo operations with CrewAI collaborative intelligence.

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Connect Finmo MCP to CrewAI

Create your Vinkius account to connect Finmo 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 Finmo with CrewAI

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Collaborative Finmo management with CrewAI

Assign one agent to monitor `list_refunds` while another handles `create_customer`. Your crew shares memory to ensure every action is coordinated. This prevents conflicts where one agent tries to move funds while another is still verifying the beneficiary details. They work together to maintain your operational state.

Autonomous treasury monitoring for CrewAI

Let your monitoring agent watch `list_wallets` around the clock. If balances drop, it alerts the primary agent to pause non-essential payouts. You define the roles and the rules. The crew handles the constant checking and balancing, freeing you from watching the dashboard.

Role-based Finmo tool access

Restrict which agents can call `create_payout` versus those that only view `list_payins`. You maintain strict control over your financial operations. This segmentation ensures that only the authorized agent performs high-stakes actions. Every other agent acts as a support or research role for the primary actor.

Setup guide

Set up Finmo 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 Finmo tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Finmo transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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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="Finmo Analyst",
        goal="Access and analyze Finmo data via MCP.",
        backstory="Expert analyst with direct Finmo access.",
        tools=mcp_tools,
    )

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

Pass the specific tool list to the `mcps` argument in your agent definition. You can isolate `create_payout` to a single 'Treasurer' agent.

Yes. Shared memory allows agents to pass findings from `list_customers` to the agent responsible for initiating a payout.

You can use the standard `MCPServerHTTP` transport. It works out of the box with your existing crew setup.

Use a moderator agent to review the output of the action-taking agent. It can verify the transaction parameters before the final submission.

The server uses volatile memory for all tool operations. We never persist your beneficiary lists or bank details on the server host.

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