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.

SafeGraph MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes

Name: SafeGraph
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 10 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect SafeGraph through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="SafeGraph Assistant",
            instructions=(
                "You help users interact with SafeGraph. "
                "You have access to 10 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from SafeGraph"
        )
        print(result.final_output)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About SafeGraph MCP Server

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.

The OpenAI Agents SDK auto-discovers all 10 tools from SafeGraph through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries SafeGraph, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.

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).

The SafeGraph MCP Server exposes 10 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect SafeGraph to OpenAI Agents SDK via MCP

Follow these steps to integrate the SafeGraph MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 10 tools from SafeGraph

Why Use OpenAI Agents SDK with the SafeGraph MCP Server

OpenAI Agents SDK provides unique advantages when paired with SafeGraph through the Model Context Protocol.

Native MCP integration via `MCPServerSse` — pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

SafeGraph + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the SafeGraph MCP Server delivers measurable value.

Automated workflows: build agents that query SafeGraph, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents — one queries SafeGraph, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through SafeGraph tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query SafeGraph to resolve tickets, look up records, and update statuses without human intervention

SafeGraph MCP Tools for OpenAI Agents SDK (10)

These 10 tools become available when you connect SafeGraph to OpenAI Agents SDK via MCP:

batch_lookup_placekeys

Provide them as a JSON array. Performs multiple Placekey lookups in a single request

graphql_raw_query

Provide the query string and optional variables. Executes a raw GraphQL query against the SafeGraph API

lookup_building_geometry

Retrieves the building footprint (polygon) for a specific Placekey

lookup_parent_polygon

Identifies the parent Placekey for a location (e.g., mall or airport)

lookup_place_patterns

Retrieves historical foot traffic patterns for a specific Placekey

lookup_placekey

Retrieves detailed attributes for a specific location by its Placekey

search_brand_places

g., "Starbucks") in a specific city. Searches for locations of a specific brand in a city

search_distance_radius

Specify lat, lon, and radius in meters. Searches for places within a specific radius from a point

search_industry_naics

Searches for places by NAICS industry code and region

search_wkt_polygon

Finds all places within a specific geometric polygon (WKT)

Example Prompts for SafeGraph in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with SafeGraph immediately.

"Search for all the Starbucks branches strictly inside the city of Seattle, WA."

"Check what the detailed building geometry polygon is for Placekey '22m-xyz-1234'."

"Can you gather the historical pedestrian traffic patterns evaluating typical visit frequencies around Placekey '123-abc-987'?"

Troubleshooting SafeGraph MCP Server with OpenAI Agents SDK

Common issues when connecting SafeGraph to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

SafeGraph + OpenAI Agents SDK FAQ

Common questions about integrating SafeGraph MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.