How to Use the Bleez MCP in AutoGen

Q: Can two AutoGen agents discuss a Bleez invoice discrepancy?

Yes, one agent can inspect the invoice history using listinvoices while another flags outliers, debating the correct adjustment in their group chat.

Q: Can I restrict which agent can upload documents?

Yes. You can assign uploaddocument exclusively to your document-processor agent while blocking other agents from calling it.

Let your AutoGen agents debate and verify Brazilian invoices before committing them to your Bleez ledger.

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Connect Bleez MCP to AutoGen

Create your Vinkius account to connect Bleez 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.

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Setup Bleez with AutoGen

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Multi-Agent MCP Server Consensus for Accounting

Don't let a single agent write to your books blindly. With this MCP Server, your AutoGen team can debate before executing `create_accounting_entry`. An AutoGen compliance agent checks local Brazilian rules, a finance agent reviews the amount, and only after consensus does the executor agent write the record to Bleez. This prevents costly tax errors.

Collaborative Invoice Verification

Speed up your billing cycle with automated peer review. One AutoGen agent pulls records using `list_invoices` while another cross-references them with `list_customers` from Bleez. If they find a discrepancy, they discuss it in the AutoGen chat thread. Once resolved, they trigger `create_invoice` to issue the corrected Bleez billing document.

Secure Supplier and Document Audits

Managing local vendors requires strict oversight. Your AutoGen auditing agent uses `list_suppliers` to check credentials against incoming Bleez receipts. Another AutoGen agent uses `upload_document` to queue the receipt in Bleez. They collaborate to ensure every uploaded file matches an approved supplier profile.

Setup guide

Set up Bleez 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 includes mcp_server_tools for 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 AssistantAgent and call agent.run(). The agent invokes Bleez tools and returns structured results.

agent.py

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="Bleez_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Bleez data")
print(result.messages[-1].content)

Get your connection token →

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. McpWorkbench is 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=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

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="Bleez_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Bleez data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Bleez. 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 Bleez MCP in AutoGen

Register the tools using our MCP Server adapter with our hosted HTTP endpoint. Pass the resulting tool list to your `AssistantAgent` to let them run tax operations.

Yes, one agent can inspect the invoice history using `list_invoices` while another flags outliers, debating the correct adjustment in their group chat.

The extension's MCP tool adapter translates the JSON schemas automatically. Your agents will understand the parameters for `create_accounting_entry` without manual mapping.

Yes. You can assign `upload_document` exclusively to your document-processor agent while blocking other agents from calling it.

Your supplier details and payment records are processed in secure, single-tenant V8 isolates. We use strict network isolation to ensure your financial data remains completely private.

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