Melo MCP. Analyze property values and track blockchain assets.
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…and any MCP-compatible client
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Melo connects your AI client to on-chain real estate intelligence. It lets you run complex queries—like finding properties, tracking transaction history, or getting local market trends—all through natural conversation.
Don't just list addresses; analyze the assets themselves via Melo.
What your AI agents can do
Get market insights
Runs a query to pull real estate market trend data for a specified location or region.
Get onchain metadata
Retrieves the specific blockchain-recorded metadata associated with a property ID.
Get property
Pulls comprehensive, current details for one single identified property using its address or unique ID.
The agent retrieves real-time, localized property value changes and neighborhood demand statistics.
You can pull technical on-chain details for any given property ID or address.
The server finds listings by text search, filtering results across different regions simultaneously.
It provides a timeline of recorded sales and financial events associated with an asset.
The agent pulls comprehensive lists of current listings, organized by status (for sale/rent) or collection type.
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Supported MCP Clients
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Melo MCP Server: 10 Tools for Real Estate Intelligence
These ten tools let your AI agent perform every step of a property analysis—from broad searches to deep, blockchain-verified metadata retrieval.
019d75d1get market insights
Runs a query to pull real estate market trend data for a specified location or region.
019d75d1get onchain metadata
Retrieves the specific blockchain-recorded metadata associated with a property ID.
019d75d1get property
Pulls comprehensive, current details for one single identified property using its address or unique ID.
019d75d1get property history
Generates a full timeline of recorded sales, price changes, and ownership transfers for an asset.
019d75d1list active listings
Lists all properties currently marked as available for sale or rent in a specified area.
019d75d1list neighborhoods
Provides a list of known neighborhoods within a given city, helping narrow market searches.
019d75d1list properties
Lists general real estate properties without specific search criteria, useful for broad regional overviews.
019d75d1list property collections
Retrieves lists of curated or themed property groups defined by the platform.
019d75d1list transactions
Lists multiple real estate transactions that occurred in a specified time frame or region.
019d75d1search properties
Searches for properties using keywords, addresses, or specific terms across the entire database.
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 Melo, 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
Yo, you're connecting your AI client right into Melo's engine. This thing gives you deep access to on-chain real estate data and market intel—no more guessing games with property values. You can run complex queries in plain English; it’ll pull everything from current listings to the deepest blockchain transaction history.
Don't just look up an address; you analyze the asset itself.
Analyzing Local Market Trends
You want to know what the neighborhood is doing? Use get_market_insights to query real estate trends for any spot or region you name. It pulls live data on property value changes and demand stats across whole areas. If you need help narrowing your search, first run list_neighborhoods to get a list of recognized neighborhoods within the city, then use that info to refine your market analysis.
Searching and Filtering Properties
Need to find something specific? The search_properties tool lets you look up listings using keywords or addresses across the entire database. You can also run list_property_collections if you're interested in curated groups of properties defined by the platform, or use list_properties for a general overview of available regional assets without any specific criteria.
Tracking Ownership History and Transactions
Understanding who owned what and when is crucial. Run get_property_history to generate a full timeline showing every recorded sale, price shift, and ownership transfer an asset has seen. To see multiple events at once, use list_transactions, which pulls a list of real estate transactions that happened in a given timeframe or area.
Listing Available Properties
When you need to know what’s actually available right now, the server handles it. You can pull comprehensive lists of current listings using list_active_listings, filtering by status—whether they're listed for sale or rent. If you just want a broad view of all assets currently on the books, use the general list_properties function.
Deep Asset Intelligence and Metadata
When you get down to brass tacks, Melo gives you the dirt. Use get_property with an address or unique ID to pull current, comprehensive details for a single property. For even deeper technical dives, run get_onchain_metadata, which retrieves the specific blockchain-recorded metadata attached to any given property ID. This lets your agent see the raw data backing up the listing.
Putting It All Together
You can combine these tools. You might start by running search_properties for a certain zip code, then use that result set to pull specific details with get_property, check its full life story using get_property_history, and finish up by querying the local market conditions with get_market_insights. The server handles connecting all these data points so your agent gets one clean answer.
You'll also find you can list general transaction records using list_transactions for a specified region or time period, making it easier to audit an area’s entire financial history.
How Melo MCP Works
- 1 Subscribe to the Melo server and enter your API Key into your AI client.
- 2 Ask your agent a natural language query (e.g., 'What's the market trend in Miami?').
- 3 The agent executes the necessary tools (
get_market_insights,list_properties) against the data and presents the synthesized answer.
The bottom line is: you talk to your AI client, and it handles the complex, multi-step database calls itself. You get a single, actionable report.
Who Is Melo MCP For?
Anyone who needs real estate data beyond a simple Google search—think investment analysts, property developers, or diligence officers. If your job involves tracking asset value across multiple sources (blockchain, local MLS, market reports), this is for you.
Uses Melo to compare a target property's on-chain metadata against historical transaction data to calculate potential valuation ranges.
Runs search_properties and list_active_listings across multiple neighborhoods to identify land parcels suitable for new builds.
Checks a property's ownership chain by calling get_property_history and cross-referencing it with local market trends using get_market_insights.
What Changes When You Connect
- Full Audit Trail: You get a clear picture of an asset's life cycle by using
get_property_history. This tool pulls every recorded sale and price adjustment, letting you build a complete financial timeline—that’s key for due diligence. - Local Market Context: Don't guess about value. Use
get_market_insightsto get real-time data on neighborhood demand. It gives you the macro view that simple property listings miss, telling you why a price point might be high or low. - Deep Filtering Power: Forget clicking through multiple pages. By running
search_properties, your agent runs cross-database queries, letting you find exactly what you need—a three-bedroom condo in zip code 90210 that transacted under $1M last year. - On-Chain Verification: The
get_onchain_metadatatool connects the physical asset to its digital record. This verifies ownership and transaction details directly from the blockchain source, adding a layer of security you can't get anywhere else. - Broad Scope Listing: Need an overview? Running
list_propertiesorlist_active_listingsquickly gives you a comprehensive inventory check for a region without needing to know specific addresses first.
Real-World Use Cases
Assessing investment risk on a new parcel.
A developer needs to assess the viability of a raw plot. They ask their agent to run list_neighborhoods for the area, then use those results with get_market_insights to see if current demand supports high-end residential pricing. Finally, they check nearby assets using search_properties to gauge competition.
Verifying a property's true value.
A client is considering buying an older home. Instead of just trusting the listing price, they ask their agent to run get_property_history and cross-reference the sale data with get_onchain_metadata. This reveals if previous sales were inflated or undervalued.
Tracking a corporate portfolio's assets.
A portfolio manager needs to audit 50 different assets. They use list_property_collections first, then iterate through the results using get_onchain_metadata for each one. This ensures every asset in their collection has verifiable digital proof of existence and ownership.
Finding all available inventory quickly.
A listing agent needs to know everything available right now in a market. They run list_active_listings for the region, then use search_properties to filter those results by price range or specific features (e.g., 'pool' and 'over $2M').
The Tradeoffs
Treating it like a simple directory search.
Typing 'Show me all properties in Austin.' This only gives general listings, missing the critical market context or ownership history. You're asking for data when you need intelligence.
→
You gotta be more specific: 'What are the average sale prices and recent transaction patterns in the Westlake neighborhood?' This forces the agent to run get_market_insights alongside list_neighborhoods, giving you actionable context.
Forgetting to check the chain record.
Relying solely on a local Multiple Listing Service (MLS) report. These reports are great, but they don't show the immutable truth of ownership transfers recorded on-chain.
→
Always validate key transactions by running get_onchain_metadata and comparing it to the MLS data. This tells you if the current listing matches the verified digital asset record.
Running too many disconnected queries.
Asking for 'Properties in TX' then separately asking for 'Market trends'. You have two answers that don't talk to each other, leaving you to piece together the story manually.
→
Ask one combined prompt: 'What are the top three market insights for properties listed in Austin over the last quarter?' This forces a single call using get_market_insights and narrows down the search with list_properties.
When It Fits, When It Doesn't
Use Melo if your analysis requires fusing disparate data types—specifically, local market trends (like those from get_market_insights) with verifiable blockchain ownership records (get_onchain_metadata). If you're just trying to find a property by its address and price point, a standard listing API might suffice. But if you need the why behind the price—the historical volatility, the underlying asset provenance, or neighborhood-specific demand data—you need Melo. Don't use it if you only want basic contact info; use it when you need to build a financial narrative around an asset. The key difference is that we move beyond 'what it costs now' to 'how its value has been proven over time.'
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Melo. 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 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Sifting through property data feels like pulling teeth.
Today, checking a single asset requires jumping between four different places: the local MLS portal for current listings; a specialized blockchain explorer to check ownership; a separate market intelligence dashboard for neighborhood trends; and finally, an internal spreadsheet to calculate your risk score. You spend 45 minutes copy-pasting IDs and cross-referencing dates just to get a basic valuation.
With Melo MCP Server, you just tell your agent: 'Analyze the investment potential of this property.' It automatically runs `get_property`, pulls `get_market_insights` for that zip code, checks `list_transactions`, and spits out one report. You don't touch a dashboard; you get an answer.
Melo MCP Server: Get full property data using the `get_property` tool.
Manual research means calling out to different endpoints just for basic facts—you get the address from one API, the owner ID from another, and the size from a third. It's slow, prone to failure, and you always lose context when you switch tabs.
Now, `get_property` pulls all those details into one stream. You ask for the property, and it returns every available data point—from current listing status to foundational metadata—without any manual stitching required.
Common Questions About Melo MCP
How do I find my Melo API Key? +
Log in to Melo, go to your Dashboard settings, and look for the API section to generate or copy your key.
What is 'on-chain' property data? +
This refers to real estate information recorded on a blockchain, providing a transparent and immutable history of ownership and events.
Is my real estate data secure? +
Absolutely. Your token is encrypted at rest and injected securely at runtime.
What happens if I run `list_active_listings` too many times? +
The server enforces standard rate limits to ensure system stability. If you exceed the allowed calls, your agent will receive a 429 error code and must wait before attempting to retrieve more listings.
How can I refine my search using `search_properties`? +
You can narrow results by adding specific parameters like zip codes, keywords, or price ranges into the search term. The tool passes these filters directly to the underlying property database.
What data structure does `get_onchain_metadata` return? +
The output is a structured JSON object detailing verifiable metadata. This includes smart contract addresses, token IDs, and all recorded on-chain timestamps for the asset in question.
Does `get_market_insights` need a city or a neighborhood name? +
You must provide at least a valid city to run this tool. Providing a specific neighborhood helps localize the data, giving you hyper-specific market trends instead of general city averages.
How do I combine property details and its history using multiple tools? +
You first call get_property to retrieve the base ID. Then, pass that exact ID into the get_property_history tool. This sequence reliably pulls both static data and all historical records.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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