How to Use the Kisi MCP in LlamaIndex

Q: How do I index live Kisi lock states into LlamaIndex?

You run a query using listkisilocks and load the resulting documents into your LlamaIndex vector store. This creates a searchable index of all physical entry points and their current configurations.

Q: Can I query Kisi user access groups using natural language in LlamaIndex?

Absolutely, as the LlamaIndex agent calls listkisigroups to retrieve the active permission groups and matches them against your query to find the right access level.

Index your physical building security data using this MCP Server directly into LlamaIndex to query real-time office access.

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Connect Kisi MCP to LlamaIndex

Create your Vinkius account to connect Kisi 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 Kisi with LlamaIndex

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Index Physical Security Logs in LlamaIndex

This MCP Server lets your agent pull active user lists using `list_kisi_users` and save that state directly into a LlamaIndex vector store. It turns physical security parameters into searchable knowledge. Instead of searching through raw JSON files, you query your LlamaIndex to find out who has access to specific rooms. The agent uses `list_kisi_groups` to map permissions and keep your semantic store up to date.

Ground Agent Answers in Live Lock States

Your agent queries `get_kisi_lock` to check the current state of any lock, combining this live data with your indexed facility policies in LlamaIndex. This stops guessing if a door is secure. If a user asks who can access the server room, the LlamaIndex agent pulls the physical status using `get_kisi_place` to verify the location before answering. This prevents hallucinations about your building's physical security setup.

Automated Facility Auditing

Discovering all locations is straightforward when your agent calls `list_kisi_places` via the MCP Server. It maps out your entire facility network for fast semantic retrieval inside LlamaIndex. When you need to verify a specific user's access, the LlamaIndex agent matches their profile using `get_kisi_user` against your indexed company directory. It flags discrepancies between your database records and actual physical permissions.

Setup guide

Set up Kisi 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 Kisi 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 Kisi tools.",
)
response = await agent.run("List recent Kisi data")

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Common questions about Kisi MCP in LlamaIndex

You run a query using `list_kisi_locks` and load the resulting documents into your LlamaIndex vector store. This creates a searchable index of all physical entry points and their current configurations.

Yes, if your LlamaIndex query engine determines a security policy has been breached. The agent can route the decision to call `lockdown_kisi_lock` on the specific door identified in your index.

The client manages connection pooling, but you should space out your LlamaIndex index updates. Check `check_kisi_status` before running large batch updates of your physical access groups.

Absolutely, as the LlamaIndex agent calls `list_kisi_groups` to retrieve the active permission groups and matches them against your query to find the right access level.

Your API tokens and user access lists are never written to disk during the LlamaIndex indexing process. We process the active lock states and directory metadata entirely in memory, using ephemeral sessions that leave zero trace behind.

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