Kisi MCP Server for LlamaIndex 9 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Kisi as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Kisi. "
"You have 9 tools available."
),
)
response = await agent.run(
"What tools are available in Kisi?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Kisi MCP Server
Connect your Kisi account to any AI agent to automate your physical access control and security workflows. This MCP server enables your agent to interact with locks (doors), manage users, and trigger remote unlocks directly from natural language interfaces.
LlamaIndex agents combine Kisi tool responses with indexed documents for comprehensive, grounded answers. Connect 9 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Remote Unlocking — Trigger remote unlock commands for any managed door instantly
- Device Oversight — List all locks and retrieve real-time status (online/offline, locked/unlocked)
- User Management — List organization users and retrieve complete profile information
- Access Control Audit — Query groups, places, and role assignments to monitor permissions
- Location Tracking — List and inspect physical places configured in your Kisi environment
The Kisi MCP Server exposes 9 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Kisi to LlamaIndex via MCP
Follow these steps to integrate the Kisi MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 9 tools from Kisi
Why Use LlamaIndex with the Kisi MCP Server
LlamaIndex provides unique advantages when paired with Kisi through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Kisi tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Kisi tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Kisi, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Kisi tools were called, what data was returned, and how it influenced the final answer
Kisi + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Kisi MCP Server delivers measurable value.
Hybrid search: combine Kisi real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Kisi to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Kisi for fresh data
Analytical workflows: chain Kisi queries with LlamaIndex's data connectors to build multi-source analytical reports
Kisi MCP Tools for LlamaIndex (9)
These 9 tools become available when you connect Kisi to LlamaIndex via MCP:
get_lock_details
Get details for a specific lock
get_my_profile
Get the current authenticated user profile
get_place_details
Get details for a specific place
list_access_groups
List all access groups
list_locks
List all locks (doors)
list_places
List all physical places (locations)
list_role_assignments
List all role assignments
list_users
Use this to identify user IDs. List all users in the Kisi organization
unlock_door
Unlock a specific door (lock)
Example Prompts for Kisi in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Kisi immediately.
"Unlock the 'Main Entrance' door (ID: '12345') in Kisi."
"List all locks that are currently offline."
"Show me the details for the place 'Headquarters'."
Troubleshooting Kisi MCP Server with LlamaIndex
Common issues when connecting Kisi to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpKisi + LlamaIndex FAQ
Common questions about integrating Kisi MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Kisi with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Kisi to LlamaIndex
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.
