Can my AI automatically issue an NFS-e for a specific customer?

Yes! Use the `issue_service_invoice` tool with the Company ID and a JSON payload containing the customer data and service values. Your agent will trigger the issuance process with the relevant municipality.

How do I find the correct IBGE code for a Brazilian city?

You can use the `list_cities` tool to search for municipalities by name or state. The agent will return the official IBGE codes required for fiscal document validation.

Can I retrieve the download link for an invoice PDF?

Yes! Use the `get_service_invoice` tool with the unique Invoice ID. Your agent will return the metadata, including official links to download the PDF and XML versions of the document.

NFe.io MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: NFe.io
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to NFe.io through Vinkius, pass the Edge URL in the `mcps` parameter and every NFe.io tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="NFe.io Specialist",
    goal="Help users interact with NFe.io effectively",
    backstory=(
        "You are an expert at leveraging NFe.io tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in NFe.io "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

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

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About NFe.io MCP Server

Connect your AI agents to NFe.io, the leading Brazilian platform for fiscal document automation. This MCP provides 10 tools to manage the full lifecycle of Service Invoices (NFS-e), validate Brazilian municipal codes (IBGE), and monitor corporate metadata for companies integrated into your billing environment.

When paired with CrewAI, NFe.io becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call NFe.io tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Invoice Orchestration — Issue, cancel, and retrieve Service Invoices (NFS-e) for multiple cities across Brazil
Company Management — List and inspect registered companies and their current fiscal configurations
Service Definition — Manage service codes and tax metadata to ensure accurate fiscal reporting
Fiscal Intelligence — Retrieve detailed city capabilities and validate IBGE codes for seamless municipal integration
PDF Retrieval — Generate and retrieve download links for official invoice PDF and XML documents programmatically

The NFe.io MCP Server exposes 10 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect NFe.io to CrewAI via MCP

Follow these steps to integrate the NFe.io MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from NFe.io

Why Use CrewAI with the NFe.io MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with NFe.io through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

NFe.io + CrewAI Use Cases

Practical scenarios where CrewAI combined with the NFe.io MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries NFe.io for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries NFe.io, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain NFe.io tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries NFe.io against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

NFe.io MCP Tools for CrewAI (10)

These 10 tools become available when you connect NFe.io to CrewAI via MCP:

cancel_merchandise_invoice

Cancel an issued Merchandise Invoice (NF-e)

cancel_service_invoice

Cancel an issued Service Invoice (NFS-e)

create_company

get_company_details

Get detailed info for a specific company issuer

get_merchandise_invoice

Retrieve details for a specific Merchandise Invoice (NF-e)

get_service_invoice

Retrieve details for a specific Service Invoice (NFS-e)

issue_merchandise_invoice

Issue a Merchandise Invoice (NF-e)

issue_service_invoice

Issue a Service Invoice (NFS-e)

list_companies

List all companies (issuers) registered in your NFe.io account

list_webhooks

List all configured webhooks in NFe.io

Example Prompts for NFe.io in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with NFe.io immediately.

"List all active companies in my NFe.io account."

"Check the status of service invoice ID 'inv_nfe_999888'."

"Find the IBGE code for the city of 'São Paulo'."

Troubleshooting NFe.io MCP Server with CrewAI

Common issues when connecting NFe.io to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

NFe.io + CrewAI FAQ

Common questions about integrating NFe.io MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.