How to Use the Bitbucket MCP in CrewAI

Deploy autonomous Bitbucket agent crews that collaborate to manage your codebases.

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Connect Bitbucket MCP to CrewAI

Create your Vinkius account to connect Bitbucket 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 Bitbucket with CrewAI

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Perplexity

Collaborative Bitbucket crews in CrewAI

Assign one agent to `list_commits` while another handles `list_pull_requests`. They share memory to finish the task. Your crew works in sequence to keep your repository history organized.

Autonomous monitoring via Bitbucket MCP Server

Let your CrewAI team watch for new issues or failed builds. They take action when they spot a problem. You define the role for each agent and watch them execute the plan.

Hierarchical Bitbucket task execution

Structure your agents so a manager monitors the output of workers using `get_repository` data. This keeps the crew focused. Your complex operations run without you needing to intervene.

Setup guide

Set up Bitbucket 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 Bitbucket tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Bitbucket 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 Bitbucket. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

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Real-time monitoring

Live

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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

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Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Bitbucket MCP in CrewAI

Yes. Add the server to your agent definition and let it poll for changes using the provided tools.

The framework uses shared memory. Once one agent fetches data, the rest of the crew can access it.

The server supports high-concurrency requests. Your agents can query multiple endpoints at once without collision.

You can filter tools at the agent level. Only give the crew the specific operations they need to do their job.

We enforce strict sandbox boundaries. Your repository configuration stays isolated from other users.

Use it with your favorite AI tools

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