How to Use the Atlassian Crowd MCP in Google ADK

Q: How do I restrict the agent from modifying Crowd groups via this MCP tool?

You apply the optional toolnames list parameter during toolset initialization. By omitting write tools like createnewuser, you restrict the agent to read-only directory lookups.

Connect Atlassian Crowd directories to your enterprise Gemini agents built with the Google ADK.

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Connect Atlassian Crowd MCP to Google ADK

Create your Vinkius account to connect Atlassian Crowd to Google ADK 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 Google ADK

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Sync Crowd directories with BigQuery via Google ADK

This MCP server exposes identity status tools like `list_active_users` and `list_inactive_users` to your Gemini agents. Gemini queries the active status of thousands of users and cross-references them with your BigQuery data warehouse. Thanks to the 1M+ token context window of Gemini, the agent analyzes massive user dumps in a single prompt. It spots discrepancies between active Cloud Platform IAM roles and Crowd directory statuses without pagination headaches.

Audit directory memberships at scale

This MCP Server exposes membership verification tools like `list_group_members` and `get_group_details`. Your agent reads your current organizational hierarchy from Google Cloud and updates Crowd to match. You control which tools the agent has access to by applying a tool_names filter in your McpToolset configuration. This restriction prevents an agent from accidentally modifying groups when it should only be reading them.

Filter enterprise directories with complex queries

The server executes fast directory searches using `search_users_by_attribute` and `search_users_by_name`. Our enterprise agent translates plain language requests into structured queries to find specific employee profiles. Running this on Google Cloud infrastructure means you pipe these search results directly into downstream Vertex AI pipelines. Your system turns raw identity metadata into structured, actionable context for your enterprise agents.

Setup guide

Set up Atlassian Crowd MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Atlassian Crowd tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Atlassian Crowd_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Atlassian Crowd tools via MCP.",
    tools=mcp_tools,
)

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 Google ADK

You initialize the McpToolset class with your Vinkius HTTP transport parameters. Pass that toolset object directly into your LlmAgent instance to expose the directory management functions.

Yes, Gemini handles massive directory payloads easily. The long-context models digest large outputs from list_active_users in a single pass without timing out.

Yes, the ADK supports both transport protocols. Since Vinkius hosts and manages the server, you will use the streamable HTTP server parameters to connect.

You apply the optional tool_names list parameter during toolset initialization. By omitting write tools like create_new_user, you restrict the agent to read-only directory lookups.

All user profiles and directory metadata are processed locally in a zero-trust sandbox. The server establishes direct communication with your Crowd API endpoint without routing your directory credentials to external databases. Your enterprise security policies remain fully intact.

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