How to Use the CrewAI Platform MCP in CrewAI

Q: How do I expose only specific CrewAI Platform MCP tools to my CrewAI agents?

You can use the toolfilter option in MCPServerHTTP. This allows you to restrict your local agents to safe read-only tools like listtasks while blocking destructive ones like listagents.

Q: How do I configure multiple agents to share access to this server?

You pass the Vinkius HTTP endpoint URL in the mcps array when defining your agents. This gives every agent in your crew shared access to the same platform tools.

Connect your local CrewAI agents to the cloud-hosted CrewAI Platform using this MCP Server.

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Connect CrewAI Platform MCP to CrewAI

Create your Vinkius account to connect CrewAI Platform 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 CrewAI Platform with CrewAI

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Perplexity

Control cloud crews from local CrewAI agents

Coordinating distributed workloads becomes straightforward when you use this MCP Server to bridge your local CrewAI framework with the hosted CrewAI Platform. Your local CrewAI supervisor agent calls `kickoff_crew` to start remote workloads on the hosted CrewAI Platform. To keep the local CrewAI crew informed of remote progress, the monitoring agent calls `get_task` to pull CrewAI Platform gateway auth arrays. This lets your local and remote CrewAI systems coordinate tasks without complex polling code.

Audit remote run metrics from your local terminal

Checking CrewAI Platform health is simple when your local CrewAI agents have direct tool access. By calling `get_run_status`, your local CrewAI agent inspects cloud logs and watches vault limits on the hosted platform. If resource constraints are detected, the local CrewAI agent can trigger `cancel_run` to clean up active processes. This keeps your CrewAI Platform bill in check during intense operational runs.

Discover active platform configurations programmatically

Managing remote CrewAI Platform resources shouldn't require clicking through a browser UI when you're running local CrewAI scripts. Your local CrewAI crew calls `list_agents` to pull active churn flags and vaporize old validations on the platform. The CrewAI crew can also run `list_webhooks` to parse hold configurations directly from the CrewAI Platform. This ensures your local CrewAI agents are always aware of how the cloud platform routes external events.

Setup guide

Set up CrewAI Platform 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 CrewAI Platform tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

This server bridges your local Python scripts with the hosted CrewAI Platform. It allows your local agents to trigger, monitor, and manage cloud-hosted crews using tools like `kickoff_crew` and `list_crews`.

You can use the `tool_filter` option in `MCPServerHTTP`. This allows you to restrict your local agents to safe read-only tools like `list_tasks` while blocking destructive ones like `list_agents`.

Yes, the integration supports stdio, SSE, and Streamable HTTP. For local development, stdio is often the fastest way to get your agents talking to the server.

You pass the Vinkius HTTP endpoint URL in the `mcps` array when defining your agents. This gives every agent in your crew shared access to the same platform tools.

Security is handled entirely at the Vinkius sandbox layer. When tools like `list_tasks` or `list_agents` execute, they do so within an isolated sandbox, and your gateway history is encrypted in transit and never stored.

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