How to Use the Codefresh MCP in CrewAI

Deploy specialized CrewAI agents to monitor your delivery clusters and manage Codefresh pipelines.

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Connect Codefresh MCP to CrewAI

Create your Vinkius account to connect Codefresh 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 Codefresh with CrewAI

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Coordinate agents with Codefresh

Assign a monitoring agent to call `list_delivery_clusters` while a separate executor agent handles `trigger_codefresh_build`. Your agents work together to ensure your infrastructure stays healthy. This divides the labor among specialized crew members. One watches the state, the other takes the action.

Get pipeline insights via CrewAI

Use `get_pipeline_configuration` to feed your agents the exact requirements for a deployment. They can check these against your current settings to find discrepancies. Your agents act like a second set of eyes on your config files. They catch mistakes before they hit production.

Verify user profiles in CrewAI

The `get_my_codefresh_profile` tool lets your agents verify who is running the task. This adds a layer of accountability to your autonomous operations. It ensures that every action is linked to an authorized account. Your crew knows exactly who is in charge of the session.

Setup guide

Set up Codefresh 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 Codefresh tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Pass the server URL into the agent's MCP list. Once connected, your specialized agents gain the ability to call the tools directly.

Yes, an agent can poll the delivery clusters tool at regular intervals. It will alert the rest of your crew if it detects a cluster issue.

Multiple agents can share the same server connection. This allows your team of agents to coordinate complex tasks like pipeline audits and deployment triggers.

Use the tool filter in your agent definition. This limits which specific functions each agent can access, keeping your operations scoped correctly.

The server transmits only the essential profile data to your agents. This information is contained within your ephemeral session and never stored outside the sandbox.

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