How to Use the ConfigCat MCP in CrewAI

Q: How do I restrict which tools a CrewAI agent can access?

You can use the MCPServerHTTP class from crewai.mcp and apply a toolfilter to only expose safe tools like read-only gets, blocking destructive deletes.

Deploy autonomous teams to manage, audit, and toggle ConfigCat feature flags using CrewAI.

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Connect ConfigCat MCP to CrewAI

Create your Vinkius account to connect ConfigCat 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 ConfigCat with CrewAI

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Multi-agent feature auditing with CrewAI

The `list_settings` and `get_setting_value` tools allow your specialized CrewAI agents to collaborate on ConfigCat system audits. One researcher agent pulls the list of active ConfigCat flags, while a CrewAI analyst agent compares them against production logs to find dead code. This goes beyond basic scripting. Because CrewAI uses shared memory, the analyst agent remembers past ConfigCat flag states, helping it make smarter decisions about which flags are safe to archive.

Autonomous incident response via ConfigCat MCP Server

The `update_setting_value` and `get_setting` tools give your CrewAI response crew the ability to mitigate production outages by updating ConfigCat flags. A monitoring CrewAI agent detects an error spike, passes the incident log to a coordinator agent, and a responder agent flips the ConfigCat kill switch flag to disable the broken feature. This setup slashes your mean time to resolution. Your CrewAI crew executes the ConfigCat rollback in seconds, then drafts a post-mortem report detailing exactly which flag was modified and why.

Hierarchical environment setup for new rollouts

The `create_config`, `create_environment`, and `create_setting` tools let a structured CrewAI crew set up ConfigCat feature flags for upcoming releases. A CrewAI manager agent receives the product requirements, delegates the ConfigCat environment creation to a developer agent, and verifies the final configuration. This structure ensures zero configuration drift across your ConfigCat environments. The CrewAI manager agent cross-checks every created setting against your spec sheet, ensuring your production flags match your staging keys perfectly.

Setup guide

Set up ConfigCat 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 ConfigCat tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

You pass the Vinkius endpoint URL directly into the agent's `mcps` parameter during initialization. CrewAI automatically discovers and configures all 18 tools for that agent's use via this MCP Server.

Yes, agents share the same MCP connection. One agent can run `list_environments` while another runs `get_setting_value` to cross-reference configuration states in parallel.

Yes, a manager agent can orchestrate the process, assigning tools like `create_setting` to subordinate agents based on the specific rollout phase.

You can use the `MCPServerHTTP` class from `crewai.mcp` and apply a `tool_filter` to only expose safe tools like read-only gets, blocking destructive deletes.

Your environment configuration and API tokens are stored securely in Vinkius's zero-trust vault. This MCP Server only sends the direct output of tool calls to your CrewAI environment, keeping your raw credentials hidden from the agent execution environment.

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