Foursquare MCP. Find and analyze locations globally.
Foursquare gives you deep control over location data, letting your AI agent find, verify, and analyze any point of interest (POI) in the world. Search millions of venues using natural language; check operating hours, audit photo content, or map density within specific geographic areas like polygons or radii. It's geospatial intelligence built for conversation.
Give Claude and any AI agent real-world access
Find points of interest across the globe by executing general searches or limited queries within defined geographic areas.
Run complex searches that map to specific shapes, like polygons, or measure distance from a central point using radii.
Get structural data on a location, including its operating hours, official ratings, and full taxonomy classification.
Pull in raw text reviews and dynamic image URLs to audit the quality and social buzz of specific venues.
Get fast, accurate typeaheads by querying partial letters, helping your agent quickly narrow down intent.
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What AI agents can do with Foursquare: 10 Tools for Geospatial Intelligence
These tools let your agent perform precise location searches, extract detailed venue profiles, map density patterns, and analyze user-generated content across the globe.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Foursquare MCPAutocomplete Venues
Provides fast suggestions for venues when a user types partial names or location keywords.
List Venue Categories
Exports the entire structured classification tree (taxonomy) used by Foursquare to...
Get Place Photos
Retrieves direct media URLs for images associated with a specific location.
Get Place Details
Gathers comprehensive information on a place, including its official hours and...
Get Place Tips
Collects raw user reviews and tips left by visitors about the venue.
Match Venue Exactly
Runs a validation check to ensure that an ambiguous search query returns only one specific, confident location result.
Search Nearby Venues
Finds venues located within a specified distance (radius) from a given GPS coordinate.
Search Within Polygon
Searches for all points of interest contained entirely within a custom-drawn...
Search Within Radius
Performs rich searches by defining a precise distance scope around a target...
Search Places
Executes broad, general queries across the entire Foursquare POI graph to identify...
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
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 each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Foursquare, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Foursquare. 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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The headache of manually checking multiple local listings.
Right now, finding out everything about a spot—its hours, if it's busy, or what's around it—is a click-and-copy nightmare. You jump from Google Maps to the business site for hours, then maybe check Yelp for reviews, and finally use another tool just to map how many other competitors are nearby in that same zip code. It’s tedious, fragmented, and takes forever.
With this MCP, your agent handles it all in a single conversation. You ask: 'What's the vibe at The Corner Bistro, and is it open right now?' And you get back structured details—the hours, the rating, and even recent user tips—all synthesized instantly.
Foursquare MCP gives you total control over location data.
The process of defining a search area used to involve complex manual drawing or guessing radii. You'd spend time verifying if the boundary was right and if your query covered every corner of the target zone.
Now, you specify exact boundaries—whether it’s a custom polygon shape or a precise radius measurement around a pin—and the MCP runs the search immediately. It delivers clean, actionable data for everything within that defined space.
What Foursquare MCP does for your AI
Connecting Foursquare lets your AI client handle complex location discovery without manual searches. Instead of clicking through dozens of tabs to verify a store’s details or check surrounding businesses, you just ask. You can run deep queries, finding what exists near a specific GPS pin, or mapping density across an entire neighborhood using custom boundaries.
It retrieves rich data like operating hours and user ratings instantly. When you combine this with the Vinkius catalog, your agent gets access to one of the industry's deepest sets of location tools. You can even automatically predict search terms as you type, making any conversation about a physical place feel precise and immediate.
019d759e-7755-7000-9dae-20c7096db0e9 How to set up Foursquare MCP
The bottom line is you get deep access to Foursquare's full suite of place discovery data directly through conversation.
Subscribe to the Foursquare MCP and enter your unique API key in the Vinkius developer console.
Connect this MCP to any compatible client (like Claude or Cursor).
Instruct your agent with natural language prompts, and it executes complex location searches and data retrieval using the tools.
Who uses Foursquare MCP
This MCP is essential for anyone whose job relies on physical location data. Think urban planners, logistics managers, and app developers who need precise, real-time information about the world's venues without relying on manual web scraping.
You use this to audit commercial density or check venue quality across a large neighborhood polygon before advising a client.
You verify the operational hours and nearest POIs for multiple warehouses or delivery points in a specific radius.
You test location-based search parameters, ensuring your app can handle ambiguous inputs by forcing single venue matches.
Benefits of connecting Foursquare MCP
Check operating hours instantly. Instead of visiting a website to find out if 'The Corner Bistro' is open right now, your agent uses get_place_details to confirm its status immediately.
Map neighborhood density. Use search_within_polygon or search_nearby_venues to audit how many similar venues exist in a specific commercial zone for market analysis.
Understand user buzz. Running get_place_tips pulls in raw visitor reviews, helping you gauge the public sentiment and quality of any location beyond just the star rating.
Validate data precision. If an address is ambiguous, use match_venue_exactly. This forces Foursquare to narrow down results so your agent can confidently deliver one single answer.
Build smart autocomplete. The autocomplete_venues tool predicts what you're looking for as you type, making complex location searches feel natural and fast.
Foursquare MCP use cases
Verifying a market area for expansion
A city analyst needs to know if there are enough competing coffee shops in the new district. They use search_within_polygon to draw the exact boundaries and then run general searches across all found venues to assess POI density.
Checking event logistics
A planner needs to confirm if a pop-up shop will be accessible. They prompt for details near a target pin, using search_nearby_venues and then checking the specific hours with get_place_details.
Debugging location search forms
A developer needs to ensure their app doesn't return multiple results for one vague input. They use match_venue_exactly to validate that the system forces a single, correct venue node.
Foursquare MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Treating location data like static text.
Trying to find out if 'The Coffee Spot' is open on Sunday using only basic search queries. These often return general results without current status or hours.
You must use get_place_details for specific venues. This tool retrieves the necessary structural data, giving you real-time operating hours instead of just listing the name.
Overlooking geographic boundaries.
Assuming a nearby location is actually within your target zone when it's slightly outside the intended area.
Don't trust general searches. You need to use search_within_polygon or search_within_radius to enforce hard, defined physical boundaries around your search.
Ignoring user context in research.
Just listing a venue's address without knowing if customers liked it. This gives you zero insight into local appeal or quality.
Always use get_place_tips to pull in raw, human-written reviews and recommendations alongside the official data for a complete picture.
When to use Foursquare MCP
Use this MCP if your problem is fundamentally about physical location: 'Is X near Y?' or 'What's happening inside this specific boundary?'. You need to know if a place exists, what its hours are, or how many similar places crowd an area. Don't use it if you simply need general knowledge (like historical facts) or complex calculations that don't involve geography. If your goal is to analyze the internal structure of data types—for example, classifying everything in the world using Foursquare’s system—then list_venue_categories gives you that master list. But if you just need to search for a product category (like 'coffee'), use general searches; this MCP adds the crucial layer of geospatial precision.
Frequently asked questions about Foursquare MCP
How do I find places near a specific coordinate using Foursquare MCP? +
You use search_nearby_venues or search_within_radius. You just provide the coordinates and the desired search scope (the radius), and the agent finds all relevant POIs.
Can I check if a business is open using Foursquare MCP? +
Yes, run get_place_details on the venue. This tool pulls in structured information that includes current operational hours and status for verification.
What does 'polygon' mean when I use Foursquare MCP? +
A polygon is a custom, multi-sided shape used to define an exact geographic area. Using search_within_polygon lets you analyze only what falls inside your drawn boundaries.
Is there a way to predict what I want to search for with Foursquare MCP? +
Yes, use the autocomplete_venues tool. It provides fast typeaheads by querying partial letters and predicting user intent as you talk to your agent.
How do I get all the possible categories for a venue search using Foursquare MCP? +
You use list_venue_categories. This tool exports the entire official taxonomy, letting you see every classification rule available in the system.