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WKN: 5319 | ISIN: US000OPENAI0 | Ticker-Symbol:
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Green Street Launches Its MCP Server, Powered by GreenStreetAI, Connecting CRE Intelligence Directly to Corporate Instances of Claude, ChatGPT, Gemini, and Other AI Platforms

New MCP Server brings Green Street's proprietary research, data, and forecasts inside the AI tools organizations already use.

NEWPORT BEACH, Calif., Aug. 11, 2026 /PRNewswire/ -- Green Street, the leading provider of Real Assets intelligence, data, news, and predictive analytics, today announced the general availability of its MCP (Model Context Protocol) Server. This new capability connects Green Street's proprietary private and public market intelligence directly into the AI platforms real assets professionals already rely on, including corporate instances of Claude, ChatGPT, and Gemini, with support for additional platforms coming soon.

The MCP Server is the newest component of the GreenStreetAI capability, joining AI Summaries, which brings AI-generated executive summaries to every Green Street research report, and the forthcoming AI Assistant, a natural-language Q&A tool spanning more than 14,000 reports and decades of news archives. Together, the three capabilities mark Green Street's most significant investment yet in making its research and data accessible however and wherever clients work.

Grounded in decades of proprietary insights

Built on the Model Context Protocol (MCP), an open standard for connecting AI assistants to external data sources, the Green Street MCP Server gives users natural-language access to the same proprietary datasets that institutional CRE organizations have trusted for more than 40 years - without leaving the AI platform they are already working in, and without manual searching, exporting, or reconciling data across tools.

At launch, the MCP Server connects to Green Street's Research, Company Data, Company Sector Data, Market Data, Market Forecast, Sales Comps, and single-property Automated Valuation Model (AVM) tools, spanning the U.S., Canada, Europe, and selected Australia depending on the dataset. Green Street's pre-built prompts, including "Get Research Summary" and "Get Market Overview", return ready-made research digests and market dashboards on demand, with a broader library of pre-packaged AI Skills being released frequently.

From insight to action, in seconds

Green Street designed the MCP Server to compress workflows that traditionally took days and weeks - underwriting a market, benchmarking a REIT, or building an investment case - into a single natural-language conversation. Users can ask multi-dataset questions, such as comparing REIT valuations against transaction activity or ranking markets by risk-adjusted return, and receive answers grounded in Green Street's trusted data rather than generic web results.

"This is about meeting our clients inside the tools they already use every day," said Travis Valentine, Chief Technology Officer at Green Street. "No new platform, no new login, just Green Street's intelligence, available the moment a question comes up."

"Green Street has been the trusted source of unique insight across real assets industry for over 40 years. With the launch of MCP Server powered by GreenStreetAI, we are meeting the changing ways clients consume and use our content to make critical decisions. MCP Server creates a powerful ability for clients to combine AI capabilities with trusted Green Street intelligence like never before," said Jeff Stuek, Chief Executive Officer of Green Street.

Visit the Green Street website to book a demo and experience GreenStreetAI's MCP Server for yourself.

AI-generated outputs are for informational purposes only and do not constitute investment advice. AI tools do not act as fiduciaries.

About Green Street

Green Street is the leading provider of actionable Real Assets research, news, data, analytics, and advisory services in North America, Europe, Australia, and Asia. For more than 40 years, the world's largest institutional investors have relied on Green Street's independent, unbiased insight to make better-informed investment decisions. Headquartered in Newport Beach, California, Green Street combines thought-leading research, proprietary data, and advanced analytics delivered through a modern platform. Learn more at greenstreet.com.

Media Contact
Green Street Media Team
media@greenstreet.com

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© 2026 PR Newswire
KI braucht Strom
Halbleiter, Speicherchips und Rechenzentren haben Anlegern im KI-Boom bereits enorme Gewinne beschert. Doch jetzt zeichnet sich mit der benötigten Energie der nächste große Flaschenhals ab. Neue KI-Rechenzentren benötigen nicht mehr einige Megawatt, sondern zum Teil mehrere Gigawatt Leistung – so viel wie mehrere moderne Kernkraftwerksblöcke.

Damit beginnt ein weltweites Wettrennen um verfügbare Stromkapazitäten. Hyperscaler sichern sich bereits über langfristige Verträge gewaltige Energiemengen, während Stromnetze und Erzeugungskapazitäten mit dem Ausbau kaum Schritt halten können. Zusätzlich verschärfen geopolitische Risiken rund um den Iran-Krieg und die Straße von Hormus die Situation.

Für Energieversorger und ihre Zulieferer könnte damit ein goldenes Zeitalter beginnen. Steigende Nachfrage, langfristige Abnahmeverträge und wachsende Strompreise schaffen ein Umfeld, in dem ausgewählte Unternehmen zum nächsten großen KI-Trade werden könnten.

In unserem aktuellen Spezialreport stellen wir fünf Aktien vor, die besonders stark vom explodierenden Energiehunger der KI profitieren könnten – und bei Anlegern bislang teilweise noch unter dem Radar laufen.

Jetzt den kostenlosen Report sichern – und die nächsten Gewinner des KI-Booms entdecken!
Werbehinweise: Die Billigung des Basisprospekts durch die BaFin ist nicht als ihre Befürwortung der angebotenen Wertpapiere zu verstehen. Wir empfehlen Interessenten und potenziellen Anlegern den Basisprospekt und die Endgültigen Bedingungen zu lesen, bevor sie eine Anlageentscheidung treffen, um sich möglichst umfassend zu informieren, insbesondere über die potenziellen Risiken und Chancen des Wertpapiers. Sie sind im Begriff, ein Produkt zu erwerben, das nicht einfach ist und schwer zu verstehen sein kann.