Placer.ai MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Placer.ai through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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="Placer.ai Assistant",
instructions=(
"You help users interact with Placer.ai. "
"You have access to 10 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Placer.ai"
)
print(result.final_output)
asyncio.run(main())
* 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 Placer.ai MCP Server
Connect your AI agents to Placer.ai, the leading location intelligence platform. This MCP provides 10 tools to retrieve accurate foot traffic analytics, visitor demographics, and market rankings for millions of locations.
The OpenAI Agents SDK auto-discovers all 10 tools from Placer.ai through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries Placer.ai, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.
What you can do
- Visitation Metrics — Retrieve estimated visits and trends for specific venues and brands with historical context
- Demographic Profiles — Understand visitor characteristics, including population estimates and trade area data
- Competitive Benchmarking — Access location rankings to compare performance against industry peers and category leaders
- Trade Area Analysis — Identify the True Trade Area (TTA) polygon for any point of interest to see where visitors come from
The Placer.ai 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 Placer.ai to OpenAI Agents SDK via MCP
Follow these steps to integrate the Placer.ai 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 Placer.ai
Why Use OpenAI Agents SDK with the Placer.ai MCP Server
OpenAI Agents SDK provides unique advantages when paired with Placer.ai 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
Placer.ai + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Placer.ai MCP Server delivers measurable value.
Automated workflows: build agents that query Placer.ai, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents — one queries Placer.ai, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Placer.ai tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Placer.ai to resolve tickets, look up records, and update statuses without human intervention
Placer.ai MCP Tools for OpenAI Agents SDK (10)
These 10 tools become available when you connect Placer.ai to OpenAI Agents SDK via MCP:
get_api_status
Check Placer.ai API operational status
get_demographics
Get visitor demographics estimates
get_poi_details
Get complete details for a specific POI
get_rankings
Get location performance rankings
get_same_store_visits
Retrieve same-store foot traffic metrics
get_trade_area
Get True Trade Area (TTA) coordinates
get_trends
Get visit trends over time
get_visits
Retrieve foot traffic visit counts
list_properties
ai account. List properties associated with your account
search_poi
Search for specific locations or brands
Example Prompts for Placer.ai in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Placer.ai immediately.
"Get the foot traffic trends for POI ID 'poi_123' for the last month."
"Search Placer.ai for 'Walmart' locations in Miami and show their IDs."
"What is the demographic profile for the visitors of POI 'poi_abc'?"
Troubleshooting Placer.ai MCP Server with OpenAI Agents SDK
Common issues when connecting Placer.ai to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Placer.ai + OpenAI Agents SDK FAQ
Common questions about integrating Placer.ai MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect Placer.ai 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.
TypeScript-native agent framework for modern web stacks.
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.
Connect Placer.ai to OpenAI Agents SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.