How to Use the Clever Cloud (Developer PaaS API) MCP in CrewAI

Q: How do I add the Clever Cloud (Developer PaaS API) to my CrewAI setup?

Pass the Vinkius endpoint URL directly into the mcps array when defining your CrewAI agent. The framework handles the MCP setup and exposes all fourteen tools to that specific agent.

Q: Can a CrewAI agent read Clever Cloud (Developer PaaS API) logs?

Yes, you can configure an agent to execute getapplicationlogs. The agent reads the text output and stores the relevant error messages in the crew's shared memory for other agents to analyze.

Q: How do I restrict a CrewAI agent from using Clever Cloud (Developer PaaS API) delete tools?

Use the MCPServerHTTP class from crewai.mcp and apply a toolfilter. You can explicitly block deleteapplication while allowing the agent to use read-only tools like listapplications.

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Connect Clever Cloud (Developer PaaS API) MCP to CrewAI

Create your Vinkius account to connect Clever Cloud (Developer PaaS API) 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 Clever Cloud (Developer PaaS API) with CrewAI

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Autonomous Infrastructure Monitoring

Relying on humans to watch dashboards is a waste of time. You can assign a CrewAI monitor agent to continuously pull data using `list_instances` and watch for crashed nodes. The agent lives in the background, checking the pulse of your production environment. When something breaks, the monitor doesn't just send an alert. It immediately grabs the output from `get_application_logs` and passes that raw data into the crew's shared memory. The next agent in the sequence already has the context needed to start debugging.

Multi-Agent Incident Response

Fixing a downed service requires coordinated action. Once the monitor identifies the problem, a dedicated responder agent takes over. This agent reviews the logs and decides if it needs to execute `trigger_deployment` to roll back to a stable build. The entire process happens without you lifting a finger. If the rollback requires a fresh database connection, the responder can call `get_addon` to verify the credentials. Your crew handles the entire escalation path autonomously.

Provision Clever Cloud via MCP Server

Spinning up a new testing environment involves multiple steps that usually require a checklist. You can build a deployment crew where Agent A creates the base project using `create_application`. Agent B then steps in to attach the required services. Separation of duties keeps the process clean. While one agent handles the app, another calls `create_organization` to isolate the billing, and a third runs `provision_addon` for the caching layer. They collaborate to build the entire stack from scratch.

Setup guide

Set up Clever Cloud (Developer PaaS API) 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 Clever Cloud (Developer PaaS API) tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Clever Cloud (Developer PaaS API) 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 Clever Cloud. 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 Clever Cloud (Developer PaaS API) MCP in CrewAI

Pass the Vinkius endpoint URL directly into the `mcps` array when defining your CrewAI agent. The framework handles the MCP setup and exposes all fourteen tools to that specific agent.

Yes, you can configure an agent to execute `get_application_logs`. The agent reads the text output and stores the relevant error messages in the crew's shared memory for other agents to analyze.

Use the `MCPServerHTTP` class from `crewai.mcp` and apply a `tool_filter`. You can explicitly block `delete_application` while allowing the agent to use read-only tools like `list_applications`.

Each agent maintains its own role and toolset. You should assign specific tools to specific agents based on their job description to prevent them from stepping on each other during execution.

The Vinkius managed platform processes your deployment triggers and application IDs within an isolated sandbox. We do not inspect your infrastructure payloads, and the MCP connection drops the moment the CrewAI session terminates.

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