How to Use the Hub Planner MCP in AutoGen

Q: How do I give my AutoGen agents access to Hub Planner tools?

Install the autogen-extmcp package. Then, use the mcpservertools function with your Vinkius server URL. This function returns a list of tool-proxy objects that you can pass directly to your AssistantAgent constructor.

Create teams of AutoGen agents that debate and manage Hub Planner resources, projects, and schedules to find the best plan.

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Connect Hub Planner MCP to AutoGen

Create your Vinkius account to connect Hub Planner 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 Hub Planner with AutoGen

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Let Agents Debate Resource Plans

Don't just assign tasks, let your agents find the best path forward. You can create a multi-agent system where one agent, a 'Planner', uses `list_unassigned` to find work and `list_resources` to propose a candidate. A second 'Auditor' agent can then challenge that proposal by checking the candidate's schedule with `list_bookings` and `list_events`. This conversational approach surfaces issues that a single agent might miss. The agents go back and forth, using Hub Planner data as their evidence, until they reach a consensus on the most logical schedule. The entire debate is transparent.

Assign Roles to Hub Planner Agents

Build a virtual team to manage your operations. Create a 'ProjectManager' agent that monitors `list_projects` for status changes. Set up a 'ResourceManager' agent that keeps an eye on `list_unassigned` and `list_resources`. Have them talk to each other in a group chat to coordinate work. This setup mirrors how a real agency works. When a new project is created, the 'ProjectManager' can ask the 'ResourceManager' to staff it. The 'ResourceManager' then uses its tools to find the right people and reports back. You're not just running a script; you're simulating a team.

Use this MCP Server for Consensus-Driven Decisions

AutoGen excels at problems where there's no single right answer. Use it to decide which project to prioritize or how to reallocate resources when someone calls in sick. One agent can argue for one course of action, pulling data with `list_projects`, while another presents a counter-argument using `list_bookings`. The final output is a decision that has been vetted by multiple, specialized perspectives. You can build a system that automatically balances project deadlines, resource utilization, and team well-being, with each agent responsible for one part of the equation.

Setup guide

Set up Hub Planner 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 Hub Planner 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="Hub Planner_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

    result = await agent.run("List recent Hub Planner 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 Hub Planner. 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 Hub Planner MCP in AutoGen

Install the `autogen-ext[mcp]` package. Then, use the `mcp_server_tools` function with your Vinkius server URL. This function returns a list of tool-proxy objects that you can pass directly to your `AssistantAgent` constructor.

Yes. You could have one agent get the project requirements, a second agent use `list_resources` and `list_bookings` to find available staff, and a user proxy agent to approve the final plan. The agents would converse to solve the scheduling puzzle.

Agents in AutoGen communicate through messages in a group chat. One agent can call `list_clients`, for example, and then post the results into the chat. Other agents can then read that message and use the data in their own reasoning process.

AutoGen allows you to model complex, multi-step workflows that require negotiation. Instead of writing rigid if-then logic, you define agent roles and a goal, and they figure out the details by debating the data they pull from tools like `list_projects` and `list_teams`.

The connection exposes operational data like your project list, resource schedules, client names, and team structures, limited by your API key's scope. All communication between AutoGen and the MCP server is secured by your Vinkius token, and no Hub Planner data is logged or stored.

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