How to Use the CARTO MCP in CrewAI

Q: How do I monitor CARTO jobs in CrewAI?

Your monitor agent calls getimportstatus periodically. It handles the polling logic and reports back to you when the data is ready.

Deploy a specialized crew of agents to handle spatial analysis and logistics planning using CARTO and CrewAI.

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Connect CARTO MCP to CrewAI

Create your Vinkius account to connect CARTO 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 CARTO with CrewAI

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Perplexity

CrewAI agents executing spatial analysis

Assign a dedicated agent to run `calculate_isoline` for service area planning. The agent generates the reachability polygon and passes it to the next agent for further review. This allows your team of agents to collaborate on complex spatial problems. One agent computes the zone, another interprets the business impact.

Automated logistics with CARTO tools

Use `calculate_route` to let your agents optimize delivery paths based on real-time constraints. The agents share memory to keep track of previous routes and durations. Your crew handles the entire pathfinding process. They compare durations and select the most efficient route for your logistics operations.

Data discovery for your crew

Allow your agents to audit available layers using `list_map_datasets`. This helps them identify which tables are fresh and relevant before running any analysis. Your agents become self-sufficient. They find the data they need, verify its status, and perform the work without human intervention.

Setup guide

Set up CARTO 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 CARTO tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent CARTO 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="CARTO Analyst",
        goal="Access and analyze CARTO data via MCP.",
        backstory="Expert analyst with direct CARTO access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent CARTO 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 CARTO. 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 CARTO MCP in CrewAI

Pass the server URL in your agent's MCP list. You can use a tool filter if you want to limit specific agents to only certain CARTO capabilities.

Yes, shared memory lets your agents pass tool results between them. The research agent can fetch data and the moderator agent can act on it.

Your monitor agent calls `get_import_status` periodically. It handles the polling logic and reports back to you when the data is ready.

You can. Each agent gets its own tool access, allowing for hierarchical execution where one agent manages the others' tool usage.

We isolate your data requests within a zero-trust environment. Only the specific coordinates and addresses necessary for the current task are ever accessed by the agents.

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