How to Use the GrowthBook MCP in CrewAI

Q: Can I restrict which tools CrewAI uses for GrowthBook?

Yes, use the toolfilter option to limit your agents to read-only access. This is a great way to let agents analyze getfeature without changing anything.

Deploy a specialized crew of agents to manage your GrowthBook experiments autonomously.

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Connect GrowthBook MCP to CrewAI

Create your Vinkius account to connect GrowthBook 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 GrowthBook with CrewAI

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Autonomous feature management with CrewAI

Assign a dedicated agent to monitor and adjust flags using `list_features` and `toggle_feature`. Your crew handles the adjustments while you watch the results. It removes the manual effort of updating flags for every test. The agents work together to ensure your production environment stays in sync.

Collaborative project design in CrewAI

Let your research agent use `list_projects` to identify gaps in your current experiments. A separate acting agent then uses `create_project` to initialize new ones. This role-based approach keeps your GrowthBook structure organized. You define the strategy, and the crew executes the infrastructure changes.

Environment control for CrewAI

Use `list_environments` and `update_environment` to keep your staging and production zones aligned. Your agents perform these checks on a schedule. They can even run `delete_environment` when a test cycle finishes. It keeps your workspace clean and reduces technical bloat.

Setup guide

Set up GrowthBook 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 GrowthBook tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Pass the server URL to your agent's MCP configuration. Once connected, your agents can start calling `list_features` and other tools immediately.

Yes, use the tool_filter option to limit your agents to read-only access. This is a great way to let agents analyze `get_feature` without changing anything.

Yes, because the agents share the same MCP connection. If one agent uses `update_feature`, the others see the state change in the next pass.

The server returns standard error codes. You can configure your agents to interpret these and take corrective actions, like retrying a `toggle_feature` call.

Your credentials are kept isolated. The agent only interacts with the GrowthBook API to manage feature flags and project settings based on your instructions.

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