How to Use the HQBeds MCP in AutoGen

Q: How do I configure AutoGen to use HQBeds?

Install autogen-extmcp. You use mcpservertools with a StreamableHttpServerParams URL, then pass the returned list directly into your AssistantAgent constructor.

Q: How does AutoGen handle the HQBeds MCP schemas?

The McpToolAdapter automatically converts the standard JSON schema into the format AutoGen requires. You don't need to write custom parsing logic for the tool inputs.

Connect AutoGen to the HQBeds MCP Server to build multi-agent systems that debate pricing, analyze occupancy, and negotiate bookings.

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Connect HQBeds MCP to AutoGen

Create your Vinkius account to connect HQBeds 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 HQBeds with AutoGen

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Debate availability via the MCP Server

The `list_availability` tool feeds raw open bed data into your AutoGen agent chat. One agent pulls the ISO 8601 date ranges to check capacity, while a second agent evaluates that data against historical trends. They discuss the findings in the console before deciding if the property is overbooked. When they reach a consensus on capacity, a third agent can trigger `create_reservation`. The system doesn't just blindly commit a booking. The financial agent reviews the rate, the operations agent confirms the bed placement, and they execute the API call only when all constraints are met.

Analyze reservation constraints

The `list_reservations` and `get_reservation` tools give your agents the complete picture of incoming and outgoing traffic. An auditor agent reads the active booking list to find anomalies. It flags reservations that conflict with maintenance schedules or group blocks. A resolution agent then takes those flagged IDs and calls `get_guest`. It investigates the specific traveler details to determine if they can be moved to a different dorm. You watch the agents debate the best course of action for room consolidation before they present a final recommendation.

Map physical property limits

The `list_rooms` tool provides the foundational constraints for your AutoGen agents. They retrieve the exact bed counts and room types. An operations agent uses this map to argue against a sales agent that wants to push more group bookings into a specific wing of the hostel. They verify the system state using `check_hqbeds_status` and `get_account` before making any API calls. You build a resilient architecture where technical agents monitor the connection health while business agents focus purely on maximizing occupancy and revenue.

Setup guide

Set up HQBeds 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 HQBeds 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="HQBeds_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent HQBeds 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="HQBeds_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

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

Install `autogen-ext[mcp]`. You use `mcp_server_tools` with a `StreamableHttpServerParams` URL, then pass the returned list directly into your `AssistantAgent` constructor.

Yes. You can equip different agents with different tools. A frontend agent might have read access to availability, while a backend agent holds the reservation creation tool.

The API requires ISO 8601 dates. You must write system prompts that force your agents to format dates correctly before they attempt to check availability or create bookings.

The `McpToolAdapter` automatically converts the standard JSON schema into the format AutoGen requires. You don't need to write custom parsing logic for the tool inputs.

The server touches sensitive financial data and personal guest information. Vinkius executes all tool calls in a zero-trust V8 Isolate Sandbox. The process is completely ephemeral, ensuring no data persists after your agents finish their conversation.

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