SafeGraph MCP. Analyze global location and foot traffic patterns.
SafeGraph lets you analyze complex geographic data using natural language. It connects your AI to a massive dataset of Points of Interest (POIs), building geometries, and historical foot traffic patterns worldwide. You can query specific brands, find all locations within a radius, or map the precise footprint of any structure simply by asking questions.
Give Claude and any AI agent real-world access
Search for all locations belonging to a particular brand or industry within defined geographical boundaries.
Retrieve the precise geometric polygon for an individual building, or search for all places contained inside a custom-drawn city border.
Get metrics on foot traffic volume, typical visit frequency, and how long people stay at specific locations over time.
Perform broad searches for places based on NAICS industry codes or by passing a custom geographic polygon (WKT).
Ask an AI about this
Waiting for input…
What AI agents can do with SafeGraph MCP with 10 Tools
Use these specialized tools to filter, sort, segment location data, map precise footprints, analyze pedestrian flow, and retrieve deep geographic intelligence.
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 SafeGraph MCPBatch Lookup Placekeys
Performs multiple Placekey lookups efficiently using a single JSON array input.
Graphql Raw Query
Executes any raw GraphQL query against the SafeGraph API for complex data retrieval.
Lookup Building Geometry
Retrieves the exact polygon coordinates defining a specific building's physical...
Lookup Parent Polygon
Identifies and maps the encompassing parent location, such as an airport or mall...
Lookup Place Patterns
Retrieves historical data showing pedestrian foot traffic volumes and average dwell...
Lookup Placekey
Gets detailed attribute information for any known location using its unique Placekey ID.
Search Brand Places
Searches for all locations belonging to a specific brand within a defined city boundary.
Search Distance Radius
Finds places that fall within a specified radius from given latitude and longitude...
Search Industry Naics
Searches for locations using specific NAICS industry codes combined with a regional...
Search Wkt Polygon
Finds all places contained within an area defined by a custom geometric polygon (WKT...
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 SafeGraph, 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 SafeGraph GraphQL API. 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.
VINKIUS CLOUD
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on each call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
Tracking physical locations used to be a painful, multi-tab process.
Today, mapping out a market means jumping between five different dashboards: one for demographics, one for competitor addresses, another for historical traffic data, and finally, a GIS tool just to draw the custom polygon boundaries. You spend hours copying coordinates from one spreadsheet into another, constantly verifying if the raw address corresponds to the actual physical footprint.
With this MCP connection, you describe the problem in plain language. Your agent handles the entire process—it pulls the required polygons using `lookup_building_geometry` and combines that with foot traffic data via `lookup_place_patterns`. You get a single, actionable report without ever leaving your chat window.
SafeGraph MCP gives you precise insights into location patterns.
You no longer need to run separate queries just to confirm boundaries. The tool allows you to identify the parent container—the mall or complex—and then drill down immediately using `lookup_parent_polygon` and `lookup_building_geometry` for every store inside.
The difference is that your AI client doesn't just give you a list; it gives you quantifiable, geometrically accurate data about *how* people use the space. It’s the difference between guessing and knowing.
What SafeGraph MCP does for your AI
Need to know what's physically happening in an area? This connection gives your AI expert-level geographic analysis without ever touching complex database queries. It turns general questions into highly detailed location intelligence. You can find every coffee shop within a half-mile radius or map the exact polygon of a building using its Placekey.
Furthermore, you gain access to historical data, letting you check foot traffic volumes and average visitor dwell times for any structure over time. This deep capability is available instantly via Vinkius, making it one of the most powerful geospatial datasets in the catalog. It’s pure analytical power, giving your agent the ability to act like a professional urban planner or retail analyst.
019d7601-50eb-7305-8f5d-f4dbe44f9234 How to set up SafeGraph MCP
The bottom line is you stop writing SQL queries and start asking questions about the physical world.
Install the SafeGraph mapping block into your AI workspace and input your API key.
Your agent processes your natural language request, identifying the necessary location parameters (lat/lon, radius, brand name).
The MCP executes the correct geographical query against the SafeGraph dataset and returns structured data, like polygons or lists of POIs.
Who uses SafeGraph MCP
Retail analysts who need to justify lease decisions, urban planners mapping infrastructure flow, or market researchers needing precise demographic data. This tool helps people move from 'I think' to 'Here is the data.'
Determining if a new store location has adequate foot traffic and proximity to key competitors before signing a lease.
Mapping the flow of people or identifying which structural elements (like malls or industrial complexes) serve as parent containers for smaller developments.
Checking if a specific brand's footprint is concentrated in one neighborhood, or analyzing market density by NAICS code across regions.
Benefits of connecting SafeGraph MCP
You gain the ability to analyze specific brand concentrations. Instead of manually cross-referencing store maps, you can ask your agent to find all 'Starbucks' locations within Seattle instantly using search_brand_places.
The process of mapping structures becomes trivial. You don't need CAD software; just give your AI a Placekey and use lookup_building_geometry to pull the exact polygon coordinates for that site.
Understand human behavior, not just addresses. Using lookup_place_patterns, you can get historical data showing if a location has high foot traffic and what the typical dwell time is—critical intel for retail.
Complex geographic searches are handled in plain language. Need to know everything within 500 meters of a point? Use search_distance_radius and let your agent handle the math.
You can search by industry or custom boundaries using search_industry_naics or search_wkt_polygon. This lets you segment data that was previously siloed in different database tables.
SafeGraph MCP use cases
Checking Competitor Density
A retail client needs to know where all their major competitors are located in a potential new market. They ask the agent, 'Find all locations for Best Buy and Target within 1 mile of this intersection.' The agent uses search_distance_radius and returns both lists, allowing immediate competitive mapping.
Analyzing Site Potential
An urban planner needs to understand the structural relationships in a large commercial district. They ask the agent about a major shopping center's container structure. The agent runs lookup_parent_polygon and confirms the overall boundaries, helping map development.
Understanding Customer Behavior
A museum director wants to gauge visitor interest in specific exhibits. They ask the agent for historical foot traffic data on a certain hall's Placekey. The agent runs lookup_place_patterns and reports low average dwell times, signaling a need for exhibit redesign.
Bulk Location Data Retrieval
A data scientist has 50 unique location IDs they want to analyze quickly. Instead of running 50 separate queries, the agent uses batch_lookup_placekeys in one call to retrieve all necessary attributes simultaneously.
SafeGraph MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Manual Radius Searches
Attempting to manually calculate the coordinates and radius for every potential site on a spreadsheet.
Use search_distance_radius in your agent. You just provide the starting point (lat, lon) and the desired radius in meters; the MCP handles the complex math.
Over-reliance on Basic Search
Using only general search tools that return vague results without specifying industry or geometry.
For precise segmentation, combine methods. First use search_industry_naics to narrow the sector, then run search_wkt_polygon using a custom boundary for maximum accuracy.
Querying Structure Separately
Needing both the overall mall boundary and the individual store geometry in multiple steps.
Start by identifying the parent container with lookup_parent_polygon. Then, for specific stores within that area, use lookup_building_geometry to get their precise footprint.
When to use SafeGraph MCP
Use this MCP if your job requires knowing exactly where things are—structurally, commercially, or historically. If you need to know the polygon of a building, the traffic volume at a corner store, or every coffee shop within a 1-mile radius, this is what you use. Don't use it if you just need general business directory listing data; for simple lookups by name and city, a basic mapping API might suffice. However, if your analysis needs to factor in historical foot traffic (using lookup_place_patterns) or segment results based on complex industry codes (search_industry_naics), this SafeGraph MCP is essential because it provides the deep geospatial context that general APIs lack.
Frequently asked questions about SafeGraph MCP
How do I find all locations for a specific brand using SafeGraph MCP? +
You run search_brand_places. You just tell your agent the brand name (like Starbucks) and the city, and it returns every matching location in that area.
Can I analyze foot traffic with SafeGraph MCP? +
Yes. Use lookup_place_patterns to retrieve historical data on how many people visited a place and what their average time spent there was.
What is the difference between using search_distance_radius and search_wkt_polygon? +
search_distance_radius finds everything in a circle around one point. search_wkt_polygon lets you draw an irregular shape, like a specific neighborhood boundary, to find everything inside that custom area.
Does SafeGraph MCP handle complex queries? +
It does. For ultimate flexibility, use the graphql_raw_query tool, which lets you pass any complex query directly to the API root structure.