How to Use the Atlassian Crowd MCP in LlamaIndex

Q: Can I use CQL-like queries within my index lookups?

Yes, you can. The agent can use searchusersbyattribute to pull filtered lists from Crowd, then index only those specific profiles into your LlamaIndex vector database.

Index your Atlassian Crowd directory into LlamaIndex to build search pipelines grounded in real-time user profiles.

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Connect Atlassian Crowd MCP to LlamaIndex

Create your Vinkius account to connect Atlassian Crowd to LlamaIndex 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 LlamaIndex

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Query Crowd Directories via LlamaIndex MCP Server

Turn your user directory into a searchable vector store. LlamaIndex pulls active profiles using `list_active_users` and indexes the raw text, letting your search pipeline query permissions and team structures semantically. This eliminates outdated directory exports. Your agent queries the index to find who belongs where, pulling fresh records with `get_user_details` to resolve user lookups without relying on stale spreadsheets.

Semantic Search Over Group Memberships

Stop writing complex SQL or LDAP queries to find who has access to what. By indexing the output of `list_all_groups` and `list_group_members`, LlamaIndex lets you search for team permissions using natural language queries. The agent uses `get_group_details` to verify the retrieved index matches the current state. This keeps your authorization audits grounded in actual, real-time Crowd directory data.

Avoid Hallucinations in User Audits

Ensure your agent only references real accounts. When generating access reports, LlamaIndex cross-references its vector index against live data retrieved via `list_inactive_users` and `search_users_by_name`. This prevents the agent from guessing usernames or group associations. If a user profile isn't found by `search_users_by_attribute`, the index marks the record as missing rather than hallucinating a profile.

Setup guide

Set up Atlassian Crowd MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Atlassian Crowd MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Atlassian Crowd tools.",
)
response = await agent.run("List recent Atlassian Crowd data")

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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 LlamaIndex

Install llama-index-tools-mcp and initialize the client with your endpoint. Use McpToolSpec to load the tools and feed outputs from list_active_users directly into your indexing pipeline.

It can do both. While LlamaIndex is great for indexing data, your agent can also run write operations like create_new_user if you include that tool in your active tool spec.

You can filter the tools passed to your agent. By excluding list_group_members or get_group_details from the tool spec, you ensure the indexing pipeline never accesses sensitive group lists.

Yes, you can. The agent can use search_users_by_attribute to pull filtered lists from Crowd, then index only those specific profiles into your LlamaIndex vector database.

Your user profiles and group memberships are processed entirely within a secured, single-tenant V8 sandbox. No directory credentials or raw search queries are ever stored on Vinkius servers, ensuring complete operational privacy.

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