How to Use the Foursquare MCP in CrewAI

Q: How is the geographic coordinate data handled by this server?

Latitude and longitude coordinates sent to tools like searchwithinradius are transmitted directly to Foursquare to return matching venues. Vinkius processes these values in memory and immediately discards them when the execution completes.

Deploy specialized agent crews using CrewAI and this Foursquare MCP Server to run autonomous local research and analysis.

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Connect Foursquare MCP to CrewAI

Create your Vinkius account to connect Foursquare to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Foursquare with CrewAI

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Coordinate local research with a CrewAI MCP Server

Set up a multi-agent team where each agent has a specific job. One agent can use `search_places` to build a list of venues, while another agent uses `get_place_tips` to extract customer reviews. This division of labor keeps your operations organized. The agents share context dynamically, so the analyst agent knows exactly which venues the researcher agent discovered.

Spatial intelligence for autonomous agents

Give your agents the ability to understand boundaries. An agent can define a search area and use `search_within_polygon` to find businesses inside a specific neighborhood. If the boundary is circular, the agent can use `search_within_radius` instead. This is handy for logistics crews that need to find drop-off points near a fleet vehicle.

Automated venue categorization and tagging

Sorting through thousands of local businesses is tedious. You can assign an agent to query `list_venue_categories` to build a clean taxonomic map of your target market. The agent can then use `autocomplete_venues` to double-check spelling and location names before exporting the final structured data to your database.

Setup guide

Set up Foursquare MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Foursquare tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Foursquare Analyst",
    goal="Access and analyze Foursquare data via MCP.",
    backstory="Expert analyst with direct Foursquare access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Foursquare transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Foursquare Analyst",
        goal="Access and analyze Foursquare data via MCP.",
        backstory="Expert analyst with direct Foursquare access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Foursquare transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

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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Common questions about Foursquare MCP in CrewAI

You can configure the agent with the mcps parameter pointing to the Vinkius MCP URL. The framework automatically discovers and registers all Foursquare tools for that agent.

Yes. CrewAI supports parallel execution, meaning your research agent can run `search_nearby_venues` while your media agent fetches images via `get_place_photos`.

Use the MCPServerHTTP class from the CrewAI MCP module and specify a tool_filter to only expose the exact tools that the agent needs.

You should set max iterations on your CrewAI agents. This prevents them from calling `autocomplete_venues` repeatedly if they encounter ambiguous search terms.

Latitude and longitude coordinates sent to tools like `search_within_radius` are transmitted directly to Foursquare to return matching venues. Vinkius processes these values in memory and immediately discards them when the execution completes.

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