How to Use the NFe.io MCP in CrewAI
Deploy specialized agent teams to manage your Brazilian NFe.io tax compliance automatically using CrewAI.
Works with every AI agent you already use
…and any MCP-compatible client
Connect NFe.io MCP to CrewAI
Create your Vinkius account to connect NFe.io 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.
Collaborative tax invoice generation in CrewAI
The `issue_service_invoice` tool gives your billing agent the power to generate NFS-e documents while a supervisor agent reviews the output. In a CrewAI setup, one agent can gather customer details while another executes the tax filing. This MCP Server handles the connection to Brazilian municipal services seamlessly. If the issuing agent encounters a municipal tax error, the supervisor agent can step in to correct the city code before retrying.
Multi-agent returns and cancellation management
The `cancel_merchandise_invoice` tool is triggered by your operations agent to void NF-e documents when a logistics agent flags a failed delivery. Your CrewAI squad collaborates to update inventory and tax records in parallel. Before executing the cancellation, a researcher agent can call `get_merchandise_invoice` to confirm the tax document's current validity. This prevents your team from trying to cancel already voided invoices.
Autonomous company audits and setup
The `create_company` tool allows your onboarding agent to set up new corporate issuers autonomously when your sales agent closes a deal. Your CrewAI team manages the entire corporate setup flow without manual data entry. Meanwhile, an auditor agent can run `list_companies` and `list_webhooks` to verify that all active entities have their tax notifications correctly configured. This ensures your system stays compliant as you scale.
Set up NFe.io MCP in CrewAI
Prerequisites
- Python 3.10+ installed
-
crewaipackage (pip install crewai) - Active Vinkius subscription with a valid endpoint token
- 1
Install CrewAI
Run
pip install crewaito install the framework. MCP support is built-in via themcpsparameter. - 2
Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the
mcpslist. 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
Crewwith your agent and tasks. Callcrew.kickoff()— the agent will automatically invoke NFe.io tools as needed.
from crewai import Agent, Task, Crew
agent = Agent(
role="NFe.io Analyst",
goal="Access and analyze NFe.io data via MCP.",
backstory="Expert analyst with direct NFe.io access.",
mcps=[
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
],
)
task = Task(
description="List recent NFe.io transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Prerequisites
- Python 3.10+ installed
-
crewai+crewai-toolspackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install crewai crewai-tools. TheMCPServerAdapterhandles lifecycle management and tool conversion. - 2
Connect with MCPServerAdapter
Use
MCPServerAdapteras a context manager withSseServerParameterspointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle. - 3
Assign tools and run
Pass the returned
mcp_toolsto your agent'stoolsparameter. The adapter converts MCP tools to nativeBaseToolobjects compatible with all CrewAI agents.
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="NFe.io Analyst",
goal="Access and analyze NFe.io data via MCP.",
backstory="Expert analyst with direct NFe.io access.",
tools=mcp_tools,
)
task = Task(
description="List recent NFe.io transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by NFe.io. 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 NFe.io MCP in CrewAI
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