How to Use the LiquidPlanner Classic MCP in AutoGen

Deploy multi-agent teams in AutoGen to negotiate project schedules using LiquidPlanner Classic.

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Connect LiquidPlanner Classic MCP to AutoGen

Create your Vinkius account to connect LiquidPlanner Classic 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 LiquidPlanner Classic with AutoGen

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Perplexity

Debate scheduling in AutoGen

Set up agents to discuss task assignments. One agent proposes a schedule using `create_task`, while another challenges it based on resource availability. This consensus-driven approach avoids common planning errors. The agents negotiate until they agree on a viable timeline for your team.

Manage LiquidPlanner Classic with AutoGen

Assign specialized roles to your agents. A performance agent can monitor `list_projects` to flag delays, while an executor agent handles the updates. They coordinate to keep your workspace clean and up to date. You define the rules, and the agents handle the back-and-forth required to execute them.

Negotiate project constraints in AutoGen

Handle complex scheduling conflicts through agent dialogue. If a task update fails, the agents analyze the error and decide on a corrective path. This removes the need for you to oversee every minor change. The MCP Server provides the tools the agents need to act on their agreed decisions.

Setup guide

Set up LiquidPlanner Classic 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 LiquidPlanner Classic 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="LiquidPlanner Classic_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

You configure multiple agents with different system prompts. They exchange messages, proposing and critiquing actions until they reach a consensus before calling the API.

Yes, the adapter handles the schema mapping for you. You pass the tool list to the AssistantAgent, and it executes them as part of its conversation.

It is designed for exactly that. You can have a security agent check permissions while a project manager agent handles the actual task creation.

Use the provided streamable HTTP or stdio parameters in your server configuration. This connects the agents directly to the server tools.

All project data remains within the conversation loop of your agents. The server enforces authentication so only authorized agents can access your workspace data.

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