Green Street MCP Server for CrewAI 12 tools — connect in under 2 minutes
Connect your CrewAI agents to Green Street through Vinkius, pass the Edge URL in the `mcps` parameter and every Green Street tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
from crewai import Agent, Task, Crew
agent = Agent(
role="Green Street Specialist",
goal="Help users interact with Green Street effectively",
backstory=(
"You are an expert at leveraging Green Street tools "
"for automation and data analysis."
),
# Your Vinkius token. get it at cloud.vinkius.com
mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)
task = Task(
description=(
"Explore all available tools in Green Street "
"and summarize their capabilities."
),
agent=agent,
expected_output=(
"A detailed summary of 12 available tools "
"and what they can do."
),
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Green Street MCP Server
Connect your Green Street account to any AI agent and take full control of your commercial real estate (CRE) and REIT intelligence through natural conversation.
When paired with CrewAI, Green Street becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Green Street tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
What you can do
- Company Orchestration — List all listed REITs and companies in your coverage and retrieve primary financial summaries natively
- Live Metric Retrieval — Resolve deep specific metrics including Net Asset Values (NAVs), earnings (FFO/FAD), and capitalization rates flawlessly
- Market Analytics — Extract market-level analytics and grades to understand competitive rankings across property sectors synchronously
- Strategic Forecasting — Access forward-looking market projections and NOI forecasts generated by Green Street's advisory teams natively
- News Intelligence — Search and retrieve curated commercial real estate news articles and excerpts to stay ahead of market shifts synchronously
- Portfolio Navigation — Identify geographic and property-type breakouts for specific REIT portfolios to audit exposure flawlessly
The Green Street MCP Server exposes 12 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Green Street to CrewAI via MCP
Follow these steps to integrate the Green Street MCP Server with CrewAI.
Install CrewAI
Run pip install crewai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Customize the agent
Adjust the role, goal, and backstory to fit your use case
Run the crew
Run python crew.py. CrewAI auto-discovers 12 tools from Green Street
Why Use CrewAI with the Green Street MCP Server
CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Green Street through the Model Context Protocol.
Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools
CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime
Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls
Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
Green Street + CrewAI Use Cases
Practical scenarios where CrewAI combined with the Green Street MCP Server delivers measurable value.
Automated multi-step research: a reconnaissance agent queries Green Street for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff
Scheduled intelligence reports: set up a crew that periodically queries Green Street, analyzes trends over time, and generates executive briefings in markdown or PDF format
Multi-source enrichment pipelines: chain Green Street tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow
Compliance and audit automation: a compliance agent queries Green Street against predefined policy rules, generates deviation reports, and routes findings to the appropriate team
Green Street MCP Tools for CrewAI (12)
These 12 tools become available when you connect Green Street to CrewAI via MCP:
get_company_summary
Get financial summary for a specific company by symbol
get_earnings_metrics
Get FFO/FAD earnings data for a company
get_forecast_scenarios
Retrieve forward-looking market and sector projections
get_historical_transactions
Retrieve historical transaction summaries
get_market_grades
Get grades and rankings for a specific market
get_market_projections
Get forward-looking NOI projections for a market
get_market_sector_summary
Get analytics and grades for a specific market sector
get_nav_estimates
Get Net Asset Value (NAV) estimates for a company
get_news_articles
Search and retrieve commercial real estate news
get_portfolio_breakout
Get geographic and property-type breakouts for a portfolio
list_companies
List all REITs and real estate companies covered by Green Street
list_sectors
List available real estate sectors
Example Prompts for Green Street in CrewAI
Ready-to-use prompts you can give your CrewAI agent to start working with Green Street immediately.
"List all listed REITs in the Industrial sector"
"What is the market grade for the New York Office market?"
"Show me the portfolio breakout for Prologis (PLD)"
Troubleshooting Green Street MCP Server with CrewAI
Common issues when connecting Green Street to CrewAI through the Vinkius, and how to resolve them.
MCP tools not discovered
Agent not using tools
Timeout errors
Rate limiting or 429 errors
Green Street + CrewAI FAQ
Common questions about integrating Green Street MCP Server with CrewAI.
How does CrewAI discover and connect to MCP tools?
tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.Can different agents in the same crew use different MCP servers?
mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.What happens when an MCP tool call fails during a crew run?
Can CrewAI agents call multiple MCP tools in parallel?
process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.Can I run CrewAI crews on a schedule (cron)?
crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.Connect Green Street with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Green Street to CrewAI
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.