How to Use the Asaas MCP in CrewAI

Deploy autonomous agent crews to manage Brazilian billing, collections, and payouts using CrewAI and this MCP Server.

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Connect Asaas MCP to CrewAI

Create your Vinkius account to connect Asaas 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 Asaas with CrewAI

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Run an autonomous collections crew with CrewAI

A specialized billing agent monitors defaults using `list_payments` while a customer relations agent drafts personalized emails. Because these CrewAI agents share memory, they coordinate without stepping on each other's toes. The billing agent checks the account status and hands the payment ID to the collections agent. That agent then verifies the customer's subscription history via `list_subscriptions` before sending the reminder.

Reconcile Asaas accounts using this MCP Server

A CrewAI analyst agent pulls financial data using `list_transfers` and `get_balance` to verify daily payouts against your internal database. If the agent spots a discrepancy, it flags the transaction and alerts your accounting team. You get automated, continuous bookkeeping without writing custom API integrations for every financial event. The crew handles the heavy lifting of parsing Brazilian banking records autonomously.

Automate Brazilian customer signup with CrewAI

The account manager agent uses `create_customer` to register new enterprise clients the moment contract terms are signed. This multi-agent coordination ensures that no steps are missed during onboarding. By checking `get_account_check` first, the crew verifies the API connection before attempting to write any new customer records. The entire process runs in the background without requiring manual data entry.

Setup guide

Set up Asaas 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 Asaas tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

You can pass the MCP server URL directly into the tool parameters when defining your CrewAI agent. This gives that specific agent access to tools like `create_payment` while keeping other agents restricted.

Yes, if you give the agent access to the transfer tools. To prevent unauthorized payouts, you can use CrewAI's tool filters to only expose read-only tools like `list_payments` to your research agents.

CrewAI agents use shared memory to pass context. If your researcher agent pulls a transaction list using `list_payments`, it shares that specific list with the analyst agent to process the accounting logic.

Yes. You can use the CrewAI library to connect to your managed MCP endpoint over secure HTTP.

All API credentials and session data are isolated in Vinkius sandboxes. When your agents run `list_transfers` or read bank balances, the data goes directly from the gateway to your local execution environment without persistent cloud storage.

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