How to Use the Atlassian Crowd MCP in CrewAI

Q: Can I restrict which Atlassian Crowd tools a specific CrewAI agent uses?

Yes. Import MCPServerHTTP and use the toolfilter parameter. You might give your auditor agent access to read functions while blocking it from creating users.

Deploy specialized CrewAI agents to audit and manage Atlassian Crowd directories autonomously.

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Connect Atlassian Crowd MCP to CrewAI

Create your Vinkius account to connect Atlassian Crowd 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 Atlassian Crowd with CrewAI

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Perplexity

Multi-Agent Directory Audits with an MCP Server

Stop running manual access reviews. You assign a Researcher agent to pull data using `list_active_users` and hand it off to an Analyst agent. The Analyst cross-references those active profiles against HR records to spot discrepancies. A third Manager agent takes the final report and decides what to do next. It triggers `get_user_details` for any suspicious accounts to gather more context. The crew works together to clean up your directory without you lifting a finger.

Autonomous Group Provisioning

IT tickets for group access pile up fast. You build a crew where an Intake agent reads the request and a Provisioner agent executes it. The Provisioner calls `list_all_groups` to verify the target team exists before making any changes. If the team is missing, the agent escalates the issue to a human. Otherwise, it checks `list_group_members` to ensure the user is not already in the group. This hierarchical execution prevents duplicate entries and keeps the directory clean.

Security Incident Response

Speed matters when an account gets compromised. Your Monitor agent watches system logs and immediately isolates threats. It uses `search_users_by_name` to pinpoint the specific profile tied to the alert. The crew then checks `list_user_memberships` to see exactly what internal tools the compromised account could reach. They compile an incident report and disable the user in minutes. You get a Slack message summarizing the autonomous response.

Setup guide

Set up Atlassian Crowd 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 Atlassian Crowd tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Pass your Vinkius URL directly into the mcps array when defining your agent. The framework automatically discovers the available directory tools. No complex configuration required.

Yes. Import MCPServerHTTP and use the tool_filter parameter. You might give your auditor agent access to read functions while blocking it from creating users.

The crew maintains shared context during the task execution. If Agent A finds a user ID, Agent B knows about it and uses it for the next API call. They do not repeat work.

The system supports standard input/output, SSE, and HTTP. We recommend Streamable HTTP for remote connections.

Every connection runs in an isolated, temporary environment. Your agents read user statuses, group IDs, and profile attributes to do their jobs. The infrastructure destroys the execution container instantly upon completion, leaving zero trace of your directory.

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