How to Use the Picktime MCP in AutoGen

Q: Can AutoGen use Picktime to resolve schedule conflicts?

Yes. Agents can debate potential times by checking getavailability. They converge on a slot that satisfies all constraints set by the service details.

Q: How do I list services in AutoGen using Picktime?

The agents trigger listservices to understand what is bookable. They then use this info to debate the best service for the customer's needs.

Debate scheduling logic in AutoGen. Use the Picktime MCP Server to let agents negotiate bookings and handle conflicts autonomously.

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Setup Picktime with AutoGen

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Negotiate bookings with AutoGen

Configure multiple agents to debate slot availability using `get_availability`. One agent proposes a time while another checks for staff conflicts via `list_staff`. This process ensures bookings are validated before they are finalized. It forces the system to consider constraints before acting.

Deploy the Picktime MCP Server

Use the MCP adapter to give your AutoGen team access to `cancel_booking`. Agents discuss the cancellation reason before executing the call. This adds a layer of deliberation to your operations. It ensures that only authorized cancellations proceed through the system.

Manage staff with AutoGen

Have your agents verify `list_staff` roles before assigning them to a task. The agents reach a consensus based on who is available and qualified. This removes the guesswork from scheduling. Your AutoGen team makes decisions based on the current staff status retrieved via the tools.

Setup guide

Set up Picktime 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 Picktime 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="Picktime_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

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

You pass the tool list to the AssistantAgent constructor. This allows all agents in the group conversation to call scheduling tools when needed.

Yes. Agents can debate potential times by checking `get_availability`. They converge on a slot that satisfies all constraints set by the service details.

It works perfectly through the MCP tool adapter. The adapter handles schema conversion, allowing your agents to interact with the scheduling API directly.

The agents trigger `list_services` to understand what is bookable. They then use this info to debate the best service for the customer's needs.

All scheduling data, including customer contact info and booking details, is accessed via encrypted tokens. The agents only see what you allow them to retrieve during their conversation.

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