How to Use the Gelato MCP in CrewAI

Q: How to filter Gelato tools in CrewAI?

Use the toolfilter parameter in your agent setup. This restricts agents to only the tools they need for their specific role.

Run autonomous print-on-demand operations with a specialized CrewAI agent team.

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Connect Gelato MCP to CrewAI

Create your Vinkius account to connect Gelato 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 Gelato with CrewAI

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Claude

Perplexity

Role-based order management

Assign an agent to use `list_print_orders` and another to call `cancel_print_order`. This separates the monitoring and action-taking responsibilities. You create a team that acts on your behalf. Each agent focuses on one part of the fulfillment lifecycle, reducing errors.

Synchronized product research

Have your research agent pull data via `get_product_details`. The team uses this info to inform decisions on what items to stock or order. Your crew shares memory of these catalogs. This allows for faster decision-making when the team faces new product requests.

Connection verification for crews

Include `verify_api_connection` as a startup task for your agents. This ensures the entire crew is ready to process print jobs before they start. It prevents runtime errors during mission-critical tasks. You get immediate confirmation that your crew can reach the Gelato API.

Setup guide

Set up Gelato 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 Gelato tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Gelato 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 Gelato. 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.

Why Choose Vinkius

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Common questions about Gelato MCP in CrewAI

Pass the server URL into your Agent configuration. CrewAI handles the integration, making the tools available to your agents.

Yes. You can organize agents into layers where a manager agent oversees the execution of print-on-demand tasks.

They share context and memory. One agent can fetch a shipping quote and pass it to another for approval.

Use the tool_filter parameter in your agent setup. This restricts agents to only the tools they need for their specific role.

The server operates in a sandboxed environment. Your print order details never leak outside your configured agent sessions.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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Pydantic AI sdk-python

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