Can I check the status of a specific invoice?

Yes! Use the `get_invoice_details` tool with the unique invoice ID. The agent will return the full record, including the current balance and payment status.

How do I see all active subscriptions?

Use the `list_billing_subscriptions` tool. Your agent will fetch all customer packages, allowing you to filter for those that are currently in an active state.

Where do I find my API Public and Private keys?

Log in to your ChargeOver account and navigate to **Settings > Developer > REST API**. You can generate and copy your keys from that section.

ChargeOver MCP Server for CrewAI 8 tools — connect in under 2 minutes

Name: ChargeOver
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

Connect your CrewAI agents to ChargeOver through Vinkius, pass the Edge URL in the `mcps` parameter and every ChargeOver 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

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="ChargeOver Specialist",
    goal="Help users interact with ChargeOver effectively",
    backstory=(
        "You are an expert at leveraging ChargeOver 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 ChargeOver "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 8 available tools "
        "and what they can do."
    ),
)

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

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

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 ChargeOver MCP Server

Connect your ChargeOver account to any AI agent and take full control of your recurring billing and invoicing operations through natural conversation. Streamline how you manage subscriptions and customer payments.

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

Customer Oversight — List and retrieve details for all customer profiles and their contact information natively
Invoice Management — Monitor generated invoices and their current payment status flawlessly
Subscription Tracking — List and retrieve details for active and inactive customer packages securely
Transaction Auditing — Access and monitor all billing transactions and payment history flawlessly
Quote Control — List and review sales quotes to manage your revenue pipeline securely
Account Visibility — Retrieve core account and user information directly within your workspace

The ChargeOver MCP Server exposes 8 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 ChargeOver to CrewAI via MCP

Follow these steps to integrate the ChargeOver 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 8 tools from ChargeOver

Why Use CrewAI with the ChargeOver MCP Server

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

ChargeOver + CrewAI Use Cases

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

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

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

ChargeOver MCP Tools for CrewAI (8)

These 8 tools become available when you connect ChargeOver to CrewAI via MCP:

get_chargeover_account

Retrieve core account and user information

get_customer_details

Get detailed information for a specific customer

get_invoice_details

Get detailed information for a specific invoice

list_billing_quotes

List all sales quotes

list_billing_subscriptions

List all customer subscriptions (packages)

list_billing_transactions

List all billing transactions

list_chargeover_customers

List all customers

list_chargeover_invoices

List all invoices

Example Prompts for ChargeOver in CrewAI

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

"Show me the last 5 invoices in ChargeOver."

"List all customers with active subscriptions."

"What was my total transaction volume today?"

Troubleshooting ChargeOver MCP Server with CrewAI

Common issues when connecting ChargeOver 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.

ChargeOver + CrewAI FAQ

Common questions about integrating ChargeOver 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.