How to Use the InvestorLift MCP in AutoGen

Q: Can multiple AutoGen agents use the InvestorLift tools simultaneously?

Yes, any agent in your group chat can call getdeal or listdeals to gather data. The framework manages tool execution context across the entire conversation.

Q: How is my InvestorLift credential data protected during multi-agent debates?

Your API tokens and buy box details fetched by getbuybox never leave your secure local runtime. Vinkius handles the connection via an ephemeral, zero-trust sandbox that isolates your credentials.

Run multi-agent debates over wholesale real estate deals using AutoGen and the InvestorLift MCP Server.

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Connect InvestorLift MCP to AutoGen

Create your Vinkius account to connect InvestorLift 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 InvestorLift with AutoGen

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Consensus-Driven Deal Sourcing in AutoGen

The `list_deals` tool provides the raw property inventory for your multi-agent conversation loops. One agent filters the raw listings based on yield, while a second agent challenges the underwriting assumptions before moving forward. This debate prevents bad acquisitions. Instead of relying on a single model's opinion, your AutoGen agents analyze the properties from multiple angles, converging only on the highest-margin opportunities.

Multi-Agent Buy Box Alignment

The `get_buy_box` tool exposes your current target criteria to your entire agent cluster. An underwriting agent uses this data to grade deals, while a strategy agent suggests updates using `update_buy_box` when inventory runs low. This negotiation happens entirely in the background. The agents debate whether to widen your geographic parameters, ensuring you never miss out on adjacent market opportunities.

Collaborative Outreach Execution

The `send_message` tool executes seller outreach only after your agents reach a consensus on the offer. A compliance agent checks the message draft against platform rules, while an acquisition agent verifies the deal ID via `get_deal`. This collaborative check prevents automated spam. You maintain strong relationships with wholesale sellers because every outgoing message has been thoroughly vetted and approved by your agent team.

Setup guide

Set up InvestorLift 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 InvestorLift 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="InvestorLift_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

You use the MCP tool adapter to convert the server's tools into a format AutoGen understands. You then pass this list to your AssistantAgent constructor.

Yes, any agent in your group chat can call `get_deal` or `list_deals` to gather data. The framework manages tool execution context across the entire conversation.

The agents exchange messages until they reach a consensus or meet your termination condition. This prevents the system from triggering `send_message` on a low-margin property.

The integration supports both stdio and Streamable HTTP transports. You can run the server locally or connect to a hosted endpoint on Vinkius.

Your API tokens and buy box details fetched by `get_buy_box` never leave your secure local runtime. Vinkius handles the connection via an ephemeral, zero-trust sandbox that isolates your credentials.

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