How to Use the Green Street MCP in CrewAI

Q: How do I connect Green Street to my CrewAI agents?

You pass the server URL directly to the agent's mcps parameter. CrewAI then automatically registers the tools for your agents to use.

Q: Can CrewAI agents collaborate using Green Street data?

Yes. Agents share the outputs of tools like getcompanysummary through the CrewAI memory module. This allows for informed, multi-agent decision making.

Q: Is it possible to use Green Street tools selectively in CrewAI?

Yes. Use the toolfilter in your agent definition to restrict access. This ensures that only the research-focused agents have access to specific market tools.

Deploy autonomous research teams with CrewAI and the Green Street MCP server.

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Connect Green Street MCP to CrewAI

Create your Vinkius account to connect Green Street to CrewAI 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 Green Street with CrewAI

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Specialized research crews for CrewAI

Assign an analyst agent to fetch `get_earnings_metrics` while a separate monitor agent tracks sector news using `get_news_articles`. CrewAI coordinates these agents so they share findings in a common memory space. Your team operates autonomously. One agent gathers the facts while the other synthesizes them into a readable summary.

Hierarchical market analysis in CrewAI

Structure your agents so one leads the research using `get_market_sector_summary` and delegates specific tasks like `get_forecast_scenarios` to subordinates. It creates a clear chain of command for your data gathering. This ensures your CrewAI agents focus on their specific roles. The result is a high-quality report without redundant queries.

Autonomous transaction review in CrewAI

Task your agents with cross-referencing new deals using `get_historical_transactions`. If the data deviates from the norm, the agent notifies a human or logs the anomaly. Your CrewAI setup runs these checks in the background. It maintains constant coverage of the market data you care about.

Setup guide

Set up Green Street MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Green Street tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Green Street Analyst",
    goal="Access and analyze Green Street data via MCP.",
    backstory="Expert analyst with direct Green Street access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Green Street transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Green Street Analyst",
        goal="Access and analyze Green Street data via MCP.",
        backstory="Expert analyst with direct Green Street access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Green Street transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

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 Green Street. 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 Green Street MCP in CrewAI

You pass the server URL directly to the agent's `mcps` parameter. CrewAI then automatically registers the tools for your agents to use.

Yes. Agents share the outputs of tools like `get_company_summary` through the CrewAI memory module. This allows for informed, multi-agent decision making.

It works perfectly in hierarchical setups. You can filter tool access so only the appropriate agents can call `get_nav_estimates` or other sensitive tools.

Yes. Use the `tool_filter` in your agent definition to restrict access. This ensures that only the research-focused agents have access to specific market tools.

The server enforces strict endpoint authentication. All retrieved company financial data remains within your private agent session, preventing unauthorized access or data leakage.

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