SafeGraph MCP Server
Integrate SafeGraph's premier geospatial dataset into your AI. Discover detailed POIs, analyze foot traffic patterns, and process precise building geometries seamlessly from conversational prompts.
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What is the SafeGraph GraphQL API MCP Server?
The SafeGraph GraphQL API MCP Server gives AI agents like Claude, ChatGPT, and Cursor direct access to SafeGraph GraphQL API via 10 tools. Integrate SafeGraph's premier geospatial dataset into your AI. Discover detailed POIs, analyze foot traffic patterns, and process precise building geometries seamlessly from conversational prompts. Powered by the Vinkius - no API keys, no infrastructure, connect in under 2 minutes.
Built-in capabilities (10)
Tools for your AI Agents to operate SafeGraph GraphQL API
Ask your AI agent "Search for all the Starbucks branches strictly inside the city of Seattle, WA." and get the answer without opening a single dashboard. With 10 tools connected to real SafeGraph GraphQL API data, your agents reason over live information, cross-reference it with other MCP servers, and deliver insights you would spend hours assembling manually.
Works with Claude, ChatGPT, Cursor, and any MCP-compatible client. Powered by the Vinkius - your credentials never touch the AI model, every request is auditable. Connect in under two minutes.
Why teams choose Vinkius
One subscription gives you access to thousands of MCP servers - and you can deploy your own to the Vinkius Edge. Your AI agents only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure and security, zero maintenance.
Build your own MCP Server with our secure development framework →Vinkius works with every AI agent you already use
…and any MCP-compatible client
SafeGraph MCP Server capabilities
10 toolsProvide them as a JSON array. Performs multiple Placekey lookups in a single request
Provide the query string and optional variables. Executes a raw GraphQL query against the SafeGraph API
Retrieves the building footprint (polygon) for a specific Placekey
Identifies the parent Placekey for a location (e.g., mall or airport)
Retrieves historical foot traffic patterns for a specific Placekey
Retrieves detailed attributes for a specific location by its Placekey
g., "Starbucks") in a specific city. Searches for locations of a specific brand in a city
Specify lat, lon, and radius in meters. Searches for places within a specific radius from a point
Searches for places by NAICS industry code and region
Finds all places within a specific geometric polygon (WKT)
What the SafeGraph MCP Server unlocks
Empower your AI with direct connectivity to SafeGraph, the foundational geospatial and mobility dataset trusted by top analytics and enterprise organizations globally. This robust integration converts your AI into an expert geographical analyst capable of retrieving precise intelligence surrounding global structures, Points of Interest (POIs), and detailed patterns—all without touching complex database pipelines.
What you can do
- Rich Context on POIs — Fetch exhaustive lists of businesses or brands within targeted radii (
search_distance_radius,search_brand_places). You can also slice the results according to their designated NAICS industry codes region-to-region (search_industry_naics). - Deep Geospatial Footprints — Look up exact WKT polygons for targeted individual buildings (
lookup_building_geometry) or identify everything bounded inside designated custom city borders (search_wkt_polygon). Understand structural hierarchies immediately by querying parent containers like malls or industrial complexes (lookup_parent_polygon). - Pedestrian and Mobility Insights — Audit recent visit metrics, dwell times, and absolute foot traffic measurements attached to individual structures leveraging historical aggregation points (
lookup_place_patterns). - Native GraphQL Exploration — Pass perfectly structured GraphQL queries straight to the root mapping infrastructure for fully-unlocked edge cases (
graphql_raw_query). Request and resolve bulk Placekeys efficiently on demand (batch_lookup_placekeys).
How it works
1. Install this SafeGraph mapping block into your AI workspace.
2. Sign into the SafeGraph Dashboard environment.
3. Request or generate a valid GraphQL API Key within your workspace settings.
4. Input that key securely. Chat instantly: "Find all coffee shop POIs located within a 500-meter radius around longitude -122.33, latitude 47.60."
Frequently asked questions about the SafeGraph MCP Server
Can I manipulate or delete existing POIs present inside the global SafeGraph spatial indexes?
No. The AI interacts safely with the GraphQL API strictly on a 'read-only' query-bound basis. It has absolutely no inherent capability to corrupt or perform unauthorized destructive operations such as erasing core places or overwriting coordinates in your environment.
Are geometric polygons always provided for queried structures automatically?
No, they must be explicitly queried utilizing the lookup_building_geometry functionality along with a verified Placekey, or structured thoroughly using the standard GraphQL command when available. Otherwise most basic list operations only return textual descriptors and simple pinpoint latitude/longitude figures.
Does the AI download huge databases directly into my storage limit when filtering large geographical boundary ranges (WKT)?
The integration employs a managed response methodology natively implemented through GraphQL constraints. The output responses are strictly paginated securely filtering hundreds of points effectively rather than attempting to sync gigabytes directly to the chatbot at once.
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Connect SafeGraph with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
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Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Give your AI agents the power of SafeGraph GraphQL API MCP Server
Production-grade SafeGraph MCP Server. Verified, monitored, and maintained by Vinkius. Ready for your AI agents — connect and start using immediately.