How to Use the Exact Online Bouw MCP in AutoGen

Debate your construction tasks with AutoGen. Let agents negotiate project entries for Exact Online Bouw.

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Connect Exact Online Bouw MCP to AutoGen

Create your Vinkius account to connect Exact Online Bouw 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 Exact Online Bouw with AutoGen

Ask AI about this MCP

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Claude

Perplexity

Multi-agent budget debate

Assign one agent to monitor budgets and another to propose costs using `create_cost_transaction`. They debate the validity of each expense before committing it to the ledger. This creates a consensus-based approval loop. It prevents rogue entries and ensures every cost aligns with your project constraints.

Automated time entry review

Have a clerk agent pull `list_time_transactions` while a manager agent reviews them for accuracy. They discuss discrepancies and fix records before they reach the final project report. This removes the need for manual oversight. Your agents handle the verification process, flagging only the items that require human intervention.

Strategic project planning

Use `list_project_wbs` to feed project structures to your agent team. They debate the best path for resource allocation based on actual progress recorded in the system. This allows for dynamic adjustments to your project plan. Your agents negotiate the schedule based on real-time data provided by the server.

Setup guide

Set up Exact Online Bouw 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 Exact Online Bouw 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="Exact Online Bouw_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Exact Online Bouw 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="Exact Online Bouw_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

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

Get your connection token →

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Common questions about Exact Online Bouw MCP in AutoGen

You provide the MCP tools to the AssistantAgent. The agents then call these functions as needed during their debate to get or post data.

Yes. Agents pass the results of tool calls back and forth. This allows them to build a shared understanding of project status during their discussion.

The server manages all API communication via a secure endpoint. Your agents only receive the data they need to perform their specific tasks.

You set up an auditor agent that compares transaction logs. It uses the tools to flag unusual activity for your review.

The conversation history stays within your local agent environment. Sensitive financial information from the server is never exposed to external systems.

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