Can I check the payment status of a specific invoice?

Yes! Use the `get_invoice` tool with the Invoice ID. Your agent will fetch the latest details and payment status (e.g., Draft, Issued, Paid).

How do I list all my customers in Billit?

Simply ask the agent to `list_parties`. It will retrieve the directory of all companies and persons registered as customers or suppliers in your account.

Can I see recent expenses or receipts?

Yes. Use the `list_expenses` tool to retrieve a list of all incoming invoices and receipts recorded in your Billit account.

Billit MCP Server for CrewAI 9 tools — connect in under 2 minutes

Name: Billit
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 9 Tools Framework

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

Get MCP Server for AI Agents

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Billit Specialist",
    goal="Help users interact with Billit effectively",
    backstory=(
        "You are an expert at leveraging Billit 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 Billit "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 9 available tools "
        "and what they can do."
    ),
)

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

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* 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 Billit MCP Server

Connect your Billit account to any AI agent and orchestrate your e-invoicing and accounting workflows through natural conversation.

When paired with CrewAI, Billit becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Billit 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

Invoicing Oversight — List and retrieve detailed e-invoices across the Peppol network.
Party Management — Manage your CRM of customers and suppliers (Parties) within Billit.
Expense Tracking — Query incoming expenses and receipts.
Product Catalog — Access your products and services list.
Company Information — Retrieve the authenticated company's core details.

The Billit MCP Server exposes 9 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 Billit to CrewAI via MCP

Follow these steps to integrate the Billit 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 9 tools from Billit

Why Use CrewAI with the Billit MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Billit 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

Billit + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Billit 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 Billit, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Billit 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 Billit against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Billit MCP Tools for CrewAI (9)

These 9 tools become available when you connect Billit to CrewAI via MCP:

create_invoice

Create a new invoice

create_party

Create a new party (customer)

get_company_info

Get your company information

get_invoice

Get specific invoice details

get_party

Get specific party details

list_expenses

List all expenses

list_invoices

List all invoices

list_parties

List all parties (customers/suppliers)

list_products

List all products

Example Prompts for Billit in CrewAI

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

"List all active invoices."

"Find the contact details for 'Acme Corp'."

"Show my last 3 expenses."

Troubleshooting Billit MCP Server with CrewAI

Common issues when connecting Billit 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.

Billit + CrewAI FAQ

Common questions about integrating Billit 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.