How to Use the Moneybird MCP in AutoGen
Deploy AutoGen multi-agent teams to debate and execute Moneybird billing tasks with built-in consensus.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Moneybird MCP to AutoGen
Create your Vinkius account to connect Moneybird to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Multi-agent consensus with this MCP Server
This MCP Server allows multiple AutoGen agents to collaborate and cross-verify billing actions before they go live. A sales agent drafts an invoice using `create_sales_invoice`, while a compliance agent checks the details. The compliance agent runs `list_tax_rates` to verify the VAT matches current Dutch regulations. This setup prevents costly errors by requiring agreement between agents. Only after both agents approve the transaction — and that’s it — does the execution agent run `send_sales_invoice` to deliver it to the client.
Automated bank reconciliation debates
This MCP Server enables agents to resolve complex bank matching issues through structured debate. One agent fetches bank transactions using `list_financial_mutations`, while another pulls unpaid bills using `list_sales_invoices`. They compare dates and amounts to find matches. Let’s look at the numbers. If a transaction doesn't match perfectly, the agents debate the best ledger category. They query `list_ledger_accounts` to find the correct account and resolve the discrepancy without human intervention.
Intelligent recurring template management
This MCP Server automates the review and execution of recurring billing templates. Your agents use `list_recurring_invoices` to retrieve active templates and verify their schedules. They cross-reference this list with `list_crm_contacts` to ensure customer accounts are active and valid. The agents flag expired contracts or outdated pricing before generating new bills. This keeps your recurring revenue stream accurate and saves hours of manual review. Simple enough.
Set up Moneybird MCP in AutoGen
Prerequisites
- Python 3.10+ installed
-
autogen-ext[mcp]package - Active Vinkius subscription with a valid endpoint token
- 1
Install AutoGen with MCP
Run
pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includesmcp_server_toolsfor stateless tool access. - 2
Fetch tools from the MCP
Call
mcp_server_tools(SseServerParams(url=...))with your Vinkius endpoint. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. - 3
Run your agent
Pass the tools to
AssistantAgentand callagent.run(). The agent invokes Moneybird tools and returns structured results.
from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
server_params = SseServerParams(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
tools = await mcp_server_tools(server_params)
agent = AssistantAgent(
name="Moneybird_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Moneybird data")
print(result.messages[-1].content) Prerequisites
- Python 3.10+ installed
-
autogen-ext[mcp]+autogen-agentchat - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Same packages as above.
McpWorkbenchis ideal when your agent needs stateful sessions across multiple tool calls. - 2
Use McpWorkbench as context manager
Wrap your agent in
async with McpWorkbench(...)to maintain shared state and resources. The workbench manages the full MCP session lifecycle. - 3
Run with workbench
Pass
workbench=workbenchto your agent. State is preserved across multiple tool calls within the same session.
from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
server_params = SseServerParams(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
async with McpWorkbench(server_params) as workbench:
agent = AssistantAgent(
name="Moneybird_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Moneybird data")
print(result.messages[-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Moneybird. 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 Moneybird MCP in AutoGen
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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