How to Use the Mashvisor MCP in AutoGen
Deploy AutoGen agents to debate and analyze Mashvisor real estate deals before you commit capital.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Mashvisor MCP to AutoGen
Create your Vinkius account to connect Mashvisor 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.
Run multi-agent debates on Mashvisor deals in AutoGen
AutoGen lets you set up an investment committee of AI agents that debate the merits of a Mashvisor property. One AutoGen agent can pull the short-term rental potential using `get_airbnb_listings`, while another checks traditional lease rates on Mashvisor with `get_rental_rates`. They'll argue over which Mashvisor strategy yields the best risk-adjusted return based on hard numbers within the AutoGen framework. This collaborative AutoGen approach prevents you from making emotional Mashvisor purchases. The AutoGen agents use Mashvisor's `get_investment_analysis` to stress-test the deal, calculating worst-case vacancy rates before presenting a unified recommendation. You get a vetted Mashvisor investment thesis instead of a single AutoGen agent's guess.
Build specialized Mashvisor research teams using AutoGen
Assign specific roles to your AutoGen agents to speed up your Mashvisor market research. You can have an AutoGen sourcing agent that constantly scans for new Mashvisor properties using `search_properties` and a finance agent that analyzes the numbers. When the AutoGen sourcing agent finds a lead, it passes the ID to the finance agent to run Mashvisor's `get_property`. This AutoGen division of labor keeps your Mashvisor workflows organized and efficient. The AutoGen finance agent can independently pull historical trends with Mashvisor's `get_historical_performance` to verify if the sourcing agent's leads are actually viable.
Automate city-wide Mashvisor sweeps with AutoGen
Use AutoGen's `McpToolAdapter` to automatically convert this MCP Server's schemas into tools your agents can understand for Mashvisor analysis. Your team of AutoGen agents can coordinate to sweep entire cities using Mashvisor's `get_city_listings` to find properties that have been on the market too long. They can negotiate price cuts based on the Mashvisor listing history they uncover in the AutoGen chat. The AutoGen integration supports both stdio and streamable HTTP transports, ensuring low-latency communication between your agents and the Vinkius Mashvisor sandbox. This means your AutoGen agents can quickly loop through multiple neighborhoods using Mashvisor's `list_neighborhoods` without hitting communication bottlenecks.
Set up Mashvisor 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 includesmcp_server_toolsfor 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
AssistantAgentand callagent.run(). The agent invokes Mashvisor tools and returns structured results.
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="Mashvisor_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Mashvisor data")
print(result.messages[-1].content) 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.
McpWorkbenchis 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=workbenchto your agent. State is preserved across multiple tool calls within the same session.
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="Mashvisor_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Mashvisor data")
print(result.messages[-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Mashvisor. 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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