How to Use the Flow MCP in CrewAI

Deploy a specialized crew of agents in CrewAI to manage Flow projects, automating everything from research to task execution.

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Connect Flow MCP to CrewAI

Create your Vinkius account to connect Flow 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 Flow with CrewAI

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Perplexity

Collaborative agent crews

Assign research agents to use `list_projects` while executive agents use `create_task` to act on findings. Your crew shares memory, allowing them to coordinate complex project changes. Each agent has a specific role. By filtering which tools each agent can access, you prevent overlap and keep the workspace organized.

Autonomous project monitoring

Set up a monitor agent to watch for updates using `list_tasks`. If a deadline approaches, the agent can automatically flag it or update the priority level. This keeps your team focused on high-value work. The agent handles the routine checks, only involving humans when necessary for sign-off.

Role-based task management

Restrict access so only the appropriate agent can `update_task`. This gives you fine-grained control over which parts of the project your agents can modify. Use this to enforce your internal processes. You define the hierarchy, and the MCP Server ensures the agents follow the rules you set at the start.

Setup guide

Set up Flow 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 Flow tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

You pass the server URL directly into your agent configuration. The framework handles the connection, and the agents start working immediately.

It does. You can give multiple agents access to the same tools, allowing them to share data through the Flow workspace.

We use encrypted endpoints for all communication. Your data is isolated, and only your authorized agents can interact with your records.

You should. Using tool filters ensures that each agent only has the permissions it needs, which keeps your workspace data safe.

It accesses your task lists, project names, and member information. We ensure the server only touches the data required for your specific crew's tasks.

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