Radar MCP. Calculate routes, geocode addresses, validate locations.
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Radar is your location intelligence server for AI agents. It handles complex geospatial tasks, letting you convert addresses to coordinates, calculate precise routes and distances between multiple points, check if locations fall inside defined boundaries (geofencing), or pinpoint a user's general region just from an IP address.
What your AI agents can do
Autocomplete
Suggests complete addresses and points of interest as you type them out in the prompt.
Calculate route distance
Gets the total driving distance and estimated time between two specific coordinates or locations.
Calculate routing matrix
Generates a table of travel times and distances for multiple starting points to multiple ending points.
The agent converts a human-readable street address into precise latitude and longitude pairs.
You can calculate the exact driving distance and estimated time needed to get from one point to another, or manage complex multi-stop routes at once.
The agent verifies if a given set of coordinates sits inside or outside specified geographical areas.
You pass in an IP address and the server returns its estimated geographic location, typically down to the country level.
The agent cleans up raw input data and checks if an entire address string is valid and properly formatted for use.
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Supported MCP Clients
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Radar MCP Server: 10 Geospatial Tools for Location Data
Use these ten specialized tools to handle every aspect of spatial data—from validating addresses to calculating complex multi-stop routes.
019d75fcautocomplete
Suggests complete addresses and points of interest as you type them out in the prompt.
019d75fccalculate route distance
Gets the total driving distance and estimated time between two specific coordinates or locations.
019d75fccalculate routing matrix
Generates a table of travel times and distances for multiple starting points to multiple ending points.
019d75fcforward geocode
Converts a text address (like '1 Main St, City') into precise latitude and longitude coordinates.
019d75fcget location context
Retrieves extra data for a location, such as nearby weather or defined service boundaries.
019d75fcip geocode
Determines the geographic region based only on an IP address string.
019d75fcreverse geocode
Takes raw latitude and longitude coordinates and converts them back into a readable street address.
019d75fcsearch geofences
Checks for active, predefined geographical zones (geofences) near a specific set of coordinates.
019d75fcsearch places
Finds nearby points of interest (POIs), like gas stations or restaurants, based on location.
019d75fcvalidate address
Checks and cleans up a structured address to ensure it meets proper formatting rules before use in the system.
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 Radar, 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
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- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
Radar handles everything geospatial for your AI agent. You're dealing with complex location math—address conversions, routing times, checking boundaries—without writing a single line of boilerplate code. This server gives you location intelligence so deep, it feels like having a dedicated GIS team hooked up to your client.
When you start working with addresses and coordinates, you can first clean up the raw input data using validate_address. It checks an entire address string for proper formatting before you use it anywhere else. You'll then convert human-readable street addresses into precise latitude and longitude pairs with forward_geocode. Need to go backward? Just give us raw coordinates, and reverse_geocode turns them back into a readable street address.
For navigation, you can calculate the exact driving distance and estimated time between two specific points using calculate_route_distance. If you're running complex logistics or managing multi-stop routes, use calculate_routing_matrix. It generates a full table showing travel times and distances from multiple starting origins to multiple ending destinations all at once.
When it comes to context, Radar lets you check exactly what’s going on geographically. You can find nearby points of interest (POIs)—think gas stations, restaurants, or specific businesses—by running search_places against a location. If you need to know if a coordinate falls inside a pre-defined zone, use search_geofences. This checks for active geographical boundaries.
Furthermore, you can pull extra data about any location, like nearby weather conditions or established service areas, with get_location_context.
Need to know where an IP address is pointing? You just pass in the IP string, and ip_geocode spits out the estimated geographic region. And remember, if you're building a user experience that requires typed suggestions, autocomplete handles it by suggesting complete addresses or points of interest as your agent types them into the prompt.
Radar makes sure every location query—whether it’s validating an address structure, calculating multi-stop routes, or determining a region from an IP—is handled correctly and immediately. You just call the tool; we handle the messy geography.
How Radar MCP Works
- 1 First, enable the server integration on your Vinkius Marketplace account and add the Radar Publishable API Key.
- 2 Next, instruct your AI client to perform a location task (e.g., 'Calculate the driving distance between X and Y').
- 3 The agent calls the appropriate tool (
calculate_route_distance), sends the coordinates/addresses, and you get back structured data like miles, minutes, or confirmation of an invalid address.
The bottom line is: your AI client handles all the complex API calling; you just ask it what location intelligence you need.
Who Is Radar MCP For?
This server is for technical roles who deal with physical locations and data accuracy. Think of the logistics planner stuck manually checking routes on Google Maps, or the software engineer debugging a bug that says 'coordinates are out of bounds.' If your application's logic depends on knowing where something is—whether it's a package, a user, or an API input—this is for you.
Runs validate_address to clean up user inputs before saving them. Uses forward_geocode to convert map strings into database coordinates.
Uses calculate_routing_matrix to compare 10 different warehouse delivery routes instantly, finding the most efficient sequence of stops.
Employs ip_geocode on raw IP logs to quickly segment user traffic by country or region for reporting purposes.
What Changes When You Connect
- Stop guessing location data. Use
forward_geocodeto convert any messy street address into reliable latitude/longitude coordinates for your database. - Handle complex logistics planning instantly. The
calculate_routing_matrixtool lets you compare delivery routes between ten stops in a single call, saving hours of manual spreadsheet work. - Build smarter user flows by validating inputs. Running
validate_addressensures that when a user submits an address, your application logic won't crash due to bad formatting. - Know where your users are online. The
ip_geocodetool resolves IP addresses into regional data, letting you understand your user base without collecting physical location permissions. - Map out service areas with confidence. You can use
search_geofencesto confirm if a specific coordinate falls within the boundaries of a store or restricted zone.
Real-World Use Cases
A delivery driver needs the quickest path.
The dispatcher doesn't know the best route through three new stops. They ask their agent to run calculate_routing_matrix using all three addresses as origins and destinations. The agent returns a full matrix, telling them exactly which order minimizes total travel time.
A user submits an incomplete address.
The app receives '123 Main St.' from the client. Before trying to save it, the agent runs validate_address. The tool flags the input as incomplete and prompts the user for the missing zip code, preventing a database error.
A security team needs to track an IP range.
The system logs show suspicious traffic from an unknown IP. An analyst instructs their agent to run ip_geocode on that specific address. The server resolves it, showing the threat originated in a foreign country, allowing immediate action.
A local store needs to check its service boundaries.
The marketing team wants to know if a proposed pop-up kiosk location is inside their established commercial district. They run search_geofences using the coordinates, and the tool confirms that the site falls within an active 'Commercial Zone A' boundary.
The Tradeoffs
Assuming raw coordinates mean a street
A developer writes code that treats any (lat, lng) pair as having a readable address name. This fails when the coordinates are in an open field or ocean.
→
Never assume location context. Always run reverse_geocode on your raw lat/lng data first. That confirms if the point is associated with a recognizable street and city.
Calculating routes without defining start/end
Trying to use basic mapping functions that only accept one pair of coordinates, which ignores multi-stop journeys.
→
For anything more complex than a simple A-to-B trip, use calculate_routing_matrix. It handles the entire logistics network flow, comparing multiple origins and destinations at once.
Using stale or unvalidated address strings
Passing an address like '1600 Amphitheatre Parkway' directly to a database query without checking if it was fully formed.
→
Always pass the input through validate_address first. It cleans up formatting and confirms the structure is sound before you commit to running any geocoding.
When It Fits, When It Doesn't
You should use Radar when your application logic requires definitive knowledge of physical location, boundaries, or connectivity metrics. Use it if you need to confirm: 'Is this address real?' (validate_address), 'Where exactly is this point?' (forward_geocode / reverse_geocode), or 'How long will it take to get there?' (calculate_routing_matrix).
Don't use Radar if your goal is purely informational, like simply displaying a map based on coordinates the user already knows. For simple lookups, you might just need a basic mapping library. But if that lookup result needs to trigger complex business logic—like confirming service eligibility or calculating operational time—you must run through Radar’s specialized tools.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Radar. 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
Checking addresses and locations used to be a messy, multi-step process.
Today, if you need to verify an address for a new client, your team has to open the internal database, run one query to get coordinates. Then, you have to copy those coordinates into a separate mapping tool just to see what street it falls on. If the address is messy, you spend ten minutes manually cleaning up abbreviations and zip codes before you can even start.
With Radar, your agent handles all that. You simply ask it: 'What's wrong with this input?' The server runs `validate_address` or `forward_geocode`, giving you clean coordinates and confirming the address structure in one step. It’s immediate.
Radar MCP Server makes location data actionable right out of the box.
Before this, calculating a multi-stop route meant exporting addresses into a specialized spreadsheet tool and clicking through every leg manually to estimate total driving time. It was slow, prone to human error, and required multiple system logins just to get one number.
Now, you tell your agent the starting point and all 12 stops. The server runs `calculate_routing_matrix` and spits out a full comparison table—total distance, estimated time, and optimal order—all in the chat window. It's done.
Common Questions About Radar MCP
How does Radar calculate routing times using calculate_route_distance? +
It calculates the driving distance and duration between two points based on modeled road networks, predicting travel time while accounting for current traffic data where possible.
What is the difference between forward_geocode and reverse_geocode? +
Forward geocoding converts a written address ('123 Main St') into coordinates (lat/lng). Reverse geocoding does the opposite: it takes raw coordinates and turns them back into a readable street address.
Do I need to use validate_address before forward_geocode? +
While not strictly required, running validate_address first is best practice. It cleans up the input string, increasing the chances that forward_geocode returns accurate results.
Can ip_geocode tell me a user's exact physical location? +
No. The ip_geocode tool provides geographic estimates based on IP address ranges, typically pinpointing the country or general region, not an exact street address.
How many points can calculate_routing_matrix handle? +
It is designed to compare multiple origins and destinations simultaneously. Check the specific documentation for supported input limits, but it handles complex network comparisons far better than single-call tools.
If I use `forward_geocode` with an ambiguous or incomplete address, should I run `validate_address` first? +
Yes. Running validate_address cleans and structures the input data before you call forward_geocode. This ensures that the coordinates returned are based on a properly formatted and confirmed location.
Are there rate limits if I use `autocomplete` frequently in one session? +
The Vinkius Marketplace handles standard throttling for basic usage. If your application requires very high call volumes, you'll need to review the official Radar documentation regarding enterprise-level rate caps.
What types of information does `get_location_context` actually retrieve? +
get_location_context pulls more than just basic weather data. It retrieves defined geofence parameters and other relevant, context-specific local intelligence for the exact coordinates provided.
Where do I find my Radar API key? +
Log into your Radar dashboard. Under 'Project Settings' or the dedicated API keys section, look for your 'Publishable Key'. This is the standard read-only key used for client integrations and MCP operations.
Should I use the Publishable Key or the Secret Key? +
Always use the Publishable Key for this MCP server instance if possible, as the operations (geocoding, routing, lookup) are typically safe read-only spatial actions.
Can it calculate multi-stop routes like a delivery app? +
Yes, but indirectly through distance comparisons. The basic routing API fetches times from Point A to Point B. The AI can chain these requests together to establish an estimated schedule contextually in your chat.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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