Nestoria MCP. Find global properties by city name or coordinates.
Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Nestoria connects your AI agent directly to a global property database. Use it to find houses or apartments for sale or rent across major markets like the UK, Spain, France, Germany, and Australia.
You can filter listings by price range, number of bedrooms, specific keywords (like 'pool' or 'garden'), and even coordinates. It centralizes real estate data from dozens of regional portals into one chat command.
What your AI agents can do
Search listings
Searches for real estate listings on Nestoria using location, filters, and keywords.
You give a city name or coordinates, and it finds all relevant properties across multiple countries.
It limits search results based on criteria like price range, minimum number of bedrooms, and if the listing is a house or flat.
You tell it whether you are looking for properties to purchase or those available only for long-term lease.
It searches the listing descriptions using specific terms like 'pool,' 'garden,' or 'private courtyard.'
You specify how you want the listings sorted—by price, newest date, or relevance—to see what matters most first.
Ask AI about this MCP
Supported MCP Clients
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Nestoria: 1 Tool for Global Real Estate Search
The `search_listings` tool lets your AI agent find, filter, and compare properties across major international markets in a single conversational step.
019e5d3asearch listings
Searches for real estate listings on Nestoria using location, filters, and keywords.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Nestoria, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
You connect your AI agent to the Nestoria MCP Server using the search_listings tool. This lets you run deep searches across global real estate databases, pulling listings for sale or long-term rent from major markets like the UK, Spain, France, Germany, and Australia—all in one command. You never have to jump through dozens of regional property portals again; your agent gathers and filters everything right there in the chat.
The search_listings tool handles all your search needs. When you need properties, you simply give it a city name or specific geographical coordinates, and it finds every relevant listing across multiple countries. You're not limited to one region; you can find stuff worldwide.
You can really nail down what you’re looking for by filtering results based on core property details. Do you know your budget? Tell the agent your desired price range. Need space? You can set a minimum number of bedrooms, or specify if it has to be a house or just a flat.
The more specific you are, the better the search.
Want to make sure you're only seeing what matters? You tell it whether you’re looking for properties to purchase or if you need something available only for long-term lease. It keeps your intent straight—you won't get mixed results.
For advanced searches, you apply specific keywords directly to the listing descriptions. Want a pool, a garden, or maybe a private courtyard? Just use those terms, and it drills down into the listings that have them. This is way better than just scrolling through thousands of irrelevant photos.
When the results come back, you can control how they're organized. You tell the agent exactly how you want to see things sorted—by price (high or low), by which bedroom count is listed, or even by the date it hit the market. This means you always see what’s most relevant or urgent right at the top.
The search_listings tool aggregates real estate data from dozens of regional sources into one conversation thread. You pass location parameters—a city name, a pair of coordinates—and it executes the query. Then, you can refine that initial sweep by setting price minimums and maximums, narrowing the search to properties with at least two bedrooms for example.
It distinguishes between intent, so you tell your agent if you're buying or renting.
It supports searching across major global markets. Whether it’s a listing in the UK or one popping up in Brazil, you get the same powerful filtering capability. You can apply advanced keywords like 'renovated kitchen' or 'balcony view,' forcing the search engine to check the full description text for those exact phrases.
The tool lets you sort results by relevance score first, which is usually what you want, but you can switch that out for sorting purely by price point or even just by date uploaded.
It centralizes data from sources that previously required multiple logins and manual filtering. Your agent runs the search, processes the location, applies all your filters—from property type to keyword—and gives you a single, sorted list of actionable listings. You don't need separate tools for searching international markets; it handles the complexity of varied global databases automatically.
How Nestoria MCP Works
- 1 First, call
search_listingsand provide the initial parameters: location (city/coordinates), transaction type (buy/rent), and any core filters (e.g., min bedrooms). - 2 Next, you refine the search by adding advanced constraints like price ranges or specific keywords ('garden'). The agent passes these updates to the tool.
- 3 Finally, it returns a curated list of properties that match every criteria. You can then ask it to sort those results by 'newest' or 'price low-to-high' for final review.
The bottom line is: you describe your ideal property in natural language, and the server handles all the cross-country data retrieval and filtering automatically.
Who Is Nestoria MCP For?
Anyone who needs to move or invest across borders. This tool saves time for relocation specialists drowning in local listings, real estate investors needing quick market trend checks across continents, and first-time buyers overwhelmed by regional property portals.
Uses search_listings to quickly check housing availability for a client in a new country (e.g., finding suitable rentals in Madrid, Spain) without manual data entry.
Runs targeted searches across multiple markets using keywords and price filters to monitor market trends or find investment opportunities in specific districts.
Asks the agent to search for properties matching a precise lifestyle criteria—like 'a house with 4 bedrooms, a garden, and a pool'—in their target city.
What Changes When You Connect
- Stop jumping between dozen of real estate portals. Nestoria aggregates and filters listings across countries like the UK, Spain, France, Germany, Italy, Brazil, and Australia into a single chat flow.
- The
search_listingstool lets you use keywords ('pool', 'garden') to narrow results, bypassing generic searches for specific lifestyle needs in any major city. - It handles both buying and renting in one go. Just specify your intent when calling
search_listings, saving you the time of running separate searches for sale vs. lease properties. - Need market insights? You can sort results by price (high/low) or relevance, giving you immediate visibility into which listings are currently most popular or undervalued.
- Coordinates work too. Instead of guessing a neighborhood name, you pass precise coordinates to
search_listingsfor highly accurate property targeting.
Real-World Use Cases
Tracking an Investment Opportunity
An investor needs to monitor the market in Paris. They ask their agent to use search_listings, specifying 'France', 'Paris', and a price range of £1M-£3M, sorted by 'newest'. The agent returns fresh listings instantly, letting them track market movement without checking multiple sites.
Finding a Family Home Abroad
A family is moving to Brazil. They ask the agent to use search_listings for 'Brazil', specifying 'houses' and keywords like 'garden' and '4 bedrooms'. The tool returns localized listings, helping them narrow down suitable neighborhoods fast.
Comparing Rental Markets
A client is deciding between Madrid and Barcelona. They use search_listings twice: once for rent in Madrid (1000-2000 euros) and once for rent in Barcelona. The agent compiles both sets of results, letting the user compare market density side-by-side.
Quick Local Search
You know a general area but don't have the exact city name. You pass coordinates to search_listings. The tool uses those specific points to pull up listings, giving you immediate results where generic searching fails.
The Tradeoffs
Jumping between portals
Manually visiting Zillow, Rightmove, and local Spanish listing sites, then trying to copy-paste details into a spreadsheet.
→
Just call the search_listings tool once. Provide all criteria (location, price, bedrooms) in one prompt, and let the agent handle the cross-platform aggregation.
Searching for only 'houses'
Only asking for houses, but missing great flats that meet your needs because you didn't account for all property types.
→
Use search_listings and specify the full range of acceptable properties (e.g., 'flats or houses') to ensure comprehensive results.
Ignoring keywords
Searching a whole city for a house, only to find listings that don't have your must-have features like a pool.
→
Always include specific terms in the prompt (e.g., 'pool', 'renovated') when calling search_listings. This forces the agent to filter on those details.
When It Fits, When It Doesn't
Use this server if you need a single, reliable source for global property data—whether buying or renting—and your criteria are highly specific (e.g., '3 beds, over £1M, garden'). The core function of search_listings is aggregation and filtering across multiple countries.
Don't use it if you need hyper-local neighborhood details that require ground photos, or if you only care about listings from one specific local agent. If your goal is simply to find the best coffee shop nearby, this tool won't help; you need a mapping service instead. But for any multi-national real estate search, this is the go-to mechanism.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Nestoria. 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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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 1 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Finding international property listings shouldn't feel like operating seven different websites.
Today, finding a flat in Italy means opening one portal. Finding a house in Spain means logging into a second one. Checking the market in Germany requires a third tab, and if you need to compare all four, you're wasting time on manual data consolidation.
With Nestoria, your agent runs `search_listings` once. You tell it: 'Show me apartments for rent across Italy and Spain under €2000.' It handles the complex cross-border API calls and hands you a single, filtered list of actionable results.
Nestoria MCP Server makes `search_listings` work everywhere.
You don't have to remember the specific rules for every country—whether it's using coordinates in Australia or a price range in France. You just give your agent the parameters, and the tool handles the underlying complexity of each national market.
It cuts out the friction point: you go from 'I need property data' to 'Here are 12 options' instantly. The search is finished.
Common Questions About Nestoria MCP
Can I search for properties using specific coordinates instead of a city name? +
Yes! Use the search_listings tool and provide the centre_point parameter with latitude and longitude separated by a comma (e.g., '51.50,-0.12').
How do I filter results by price and property type? +
You can use the price_min, price_max, and property_type (e.g., 'house' or 'flat') parameters within the search_listings tool to narrow down your search results.
Is it possible to see the newest listings first? +
Absolutely. Set the sort parameter to 'newest' when calling the search_listings tool to get the most recent entries at the top of your results.
When using the `search_listings` tool, do I need to provide an API key or just a User Agent? +
You only need the optional User Agent string for identification. This helps Nestoria track usage and is not required for basic functionality of the search tool.
If I plan to run multiple searches, what are the rate limits for calling `search_listings`? +
The API enforces standard rate limiting. For high-volume tasks or batch processing, implement a slight delay between calls, or check our documentation for specific guidelines on bulk requests.
What happens if the `search_listings` tool fails because of bad input parameters? +
The agent receives clear error codes and messages detailing the invalid input. These errors specify unsupported criteria, like a property type or an invalid date range, so you can adjust your prompt.
Does `search_listings` only pull data from major city centers, or does it cover rural areas too? +
The tool covers listings across multiple urban and regional zones. You should use specific geographic coordinates in the search to target any area, no matter how remote.
How does `search_listings` prioritize keyword filters when I combine them with price ranges? +
The tool processes all constraints simultaneously. It first applies your geo-location and then cross-references keywords and budget, returning results that meet every single criterion.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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