How to Use the HID Origo MCP in LlamaIndex
Index your physical security data. LlamaIndex turns your HID Origo MCP Server into a searchable knowledge base.
Works with every AI agent you already use
…and any MCP-compatible client
Connect HID Origo MCP to LlamaIndex
Create your Vinkius account to connect HID Origo 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.
Query access logs with LlamaIndex
The `get_audit_log_events` tool pulls your administrative and access history straight into your vector store. LlamaIndex embeds these records so you ask natural language questions about recent door reads. You stop digging through raw JSON and just ask the agent what happened. When you query the index, the agent retrieves the exact timestamp and user ID from the API. It grounds its answers in real historical data rather than guessing. You build RAG pipelines that actually know who entered the building yesterday.
Map your organizational hardware
Executing `list_access_readers` feeds your index a complete list of IoT door controllers. The framework maps your physical infrastructure into searchable documents. You instantly find which controllers belong to specific identity groups. The agent pairs this with `get_organization_info` to understand the tenant configuration. That context feeds your RAG application the exact parameters it needs to answer complex security questions. The MCP Server keeps the connection secure while LlamaIndex builds the map.
Track mobile identity issuance
Calling `list_identity_invitations` and `list_mobile_identities` pulls the active state of every digital card into your knowledge base. You track who received an invite and who actually activated it. The agent indexes this status alongside your standard HR documents. If a user asks why their access failed, the agent searches the index and finds their pending invitation. It cross-references `get_user_details` to confirm the account exists. You get instant, grounded answers about credential states without opening a dashboard.
Set up HID Origo MCP in LlamaIndex
Prerequisites
- Python 3.10+ installed
-
llama-index-tools-mcppackage - 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 providesBasicMCPClientandMcpToolSpec. - 2
Connect with BasicMCPClient
Point
BasicMCPClientto 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 HID Origo MCP tools into nativeFunctionToolobjects that any LlamaIndex agent can use. - 4
Run with any LLM
Create a
FunctionAgentwith the tools and your preferred LLM. SwapOpenAIforAnthropic,Gemini, or any LlamaIndex-supported provider.
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 HID Origo tools.",
)
response = await agent.run("List recent HID Origo data") Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by HID Origo. 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
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Common questions about HID Origo MCP in LlamaIndex
Use it with your favorite AI tools
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