How to Use the Artsy MCP in CrewAI

Q: How do I restrict which CrewAI agents can use Artsy tools?

You use the MCPServerHTTP class and apply a toolfilter. This lets you expose listartworks to your researcher agent while keeping curation tools hidden from your writer agent.

Run multi-agent research crews to analyze global art trends using CrewAI and the Artsy MCP Server.

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Connect Artsy MCP to CrewAI

Create your Vinkius account to connect Artsy 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 Artsy with CrewAI

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Artsy MCP Server Research Crews

The `search_artsy` tool acts as the primary search engine for your research crew. You can assign a specialized Art Historian agent to search for movements while an Art Critic agent analyzes the results. By passing your Vinkius URL to the `mcps` parameter, the entire crew gets access to the tools. The agents share memory, allowing the critic to read what the historian found without repeating the search.

Curate Virtual Exhibitions Autonomously

The `list_artworks` tool lets your curation agent gather a list of potential pieces for a virtual exhibition. A separate coordinator agent then uses `get_artwork_details` to verify the historical accuracy of the selection. This works via sequential execution where the output of the first agent is fed directly into the second. You can restrict tools using a filter so only the coordinator can access sensitive details.

Monitor Global Art Shows and Fairs

The `list_shows` tool enables your monitoring agent to track active gallery exhibitions around the world. At the same time, an escalation agent uses `list_fairs` to cross-reference these shows with major international art fairs. You set up this background monitoring using `MCPServerHTTP`. The agents run autonomously, compiling reports and flagging high-profile events without requiring any manual developer intervention.

Setup guide

Set up Artsy 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 Artsy tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

You use the `MCPServerHTTP` class and apply a `tool_filter`. This lets you expose `list_artworks` to your researcher agent while keeping curation tools hidden from your writer agent.

Yes. CrewAI's shared memory system allows one agent to store the results of `search_artsy` and pass that context to another agent, preventing redundant API calls.

You pass your Vinkius endpoint URL directly into the agent's `mcps` list. The framework automatically handles the underlying HTTP transport and registers the tools for the crew.

Yes. You can set up a manager agent that delegates tasks to subordinate agents, instructing them to fetch artist details or list active shows based on a high-level research plan.

Yes. The Artsy MCP server routes all tool executions through isolated, single-use V8 runtimes. Your queries, artist lookups, and exhibition data are processed in-memory and never cached or logged to persistent storage.

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