Can I check if an invoice has been paid through the agent?

Yes. The `list_accounting_invoices` tool allows your AI agent to see the current status of all invoices, including whether they are 'PAID', 'SAVED' (unpaid), or still in 'DRAFT' status.

How do I add a new client to my Wave account using chat?

You can use the `create_accounting_customer` tool. Just provide the customer's name and email address, and your agent will register them in your Wave business instantly.

Can I delete a draft invoice if I made a mistake?

Yes. The `delete_draft_invoice` tool allows you to permanently remove unfinalized draft invoices. Note that once an invoice is approved (SAVED) or paid, it cannot be deleted through this specific tool.

Wave Accounting MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Wave Accounting
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Wave Accounting through Vinkius, pass the Edge URL in the `mcps` parameter and every Wave Accounting 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="Wave Accounting Specialist",
    goal="Help users interact with Wave Accounting effectively",
    backstory=(
        "You are an expert at leveraging Wave Accounting 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 Wave Accounting "
        "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 Wave Accounting MCP Server

Connect your Wave Accounting account to any AI agent and manage your business finances through natural conversation.

When paired with CrewAI, Wave Accounting becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Wave Accounting 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 Management — List all registered customers, create new profiles, and update contact information directly from your agent
Invoice Lifecycle — Create draft invoices, approve them for sending, and monitor their payment status (DRAFT, SAVED, PAID)
Deep Invoicing — Retrieve full details for any invoice, including line items, taxes, totals, and public payment URLs
Financial Auditing — Browse your customer base and billing activity to stay on top of your accounts receivable
Data Integrity — Safely delete unfinalized draft invoices or obsolete customer records through simple chat commands
Business Insights — Quickly find unique customer and invoice IDs required for complex accounting workflows

The Wave Accounting 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 Wave Accounting to CrewAI via MCP

Follow these steps to integrate the Wave Accounting 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 Wave Accounting

Why Use CrewAI with the Wave Accounting MCP Server

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

Wave Accounting + CrewAI Use Cases

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

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

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

Wave Accounting MCP Tools for CrewAI (10)

These 10 tools become available when you connect Wave Accounting to CrewAI via MCP:

approve_draft_invoice

Finalizes a draft invoice, moving it to an unpaid/saved status

create_accounting_customer

Provide name and email. Creates a new customer record in Wave

create_draft_invoice

Provide a customer ID and a JSON array of items. Creates a new draft invoice in Wave

delete_accounting_customer

This action is irreversible. Permanently deletes a customer record

delete_draft_invoice

Saved or paid invoices cannot be deleted via this endpoint. Permanently deletes an unfinalized draft invoice

get_customer_details

Retrieves details for a specific customer in Wave

get_invoice_details

Retrieves full details for a specific Wave invoice

list_accounting_customers

Lists customers registered in the Wave Accounting business

list_accounting_invoices

). Lists invoices issued by the Wave business

update_customer_profile

Provide the unique customer ID. Updates the profile of an existing customer

Example Prompts for Wave Accounting in CrewAI

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

"List all my customers in Wave Accounting."

"Create a new customer for 'John Doe' with email 'john@example.com'."

"What is the status of my latest invoices?"

Troubleshooting Wave Accounting MCP Server with CrewAI

Common issues when connecting Wave Accounting 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.

Wave Accounting + CrewAI FAQ

Common questions about integrating Wave Accounting 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.