Kaseya MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Kaseya 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 Kaseya. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Kaseya?"
)
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 Kaseya MCP Server
Connect your Kaseya VSA 10 instance to your AI agent for comprehensive IT management and remote monitoring. This MCP server enables your agent to interact with devices, scripts, and automation workflows across your managed environments.
LlamaIndex agents combine Kaseya tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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
- Device Visibility — List all managed agents and drill down into hardware/software details
- Inventory Tracking — Query organizations, groups, and assets to maintain a clear picture of your IT estate
- Automation Management — List and inspect scripts and automation workflows ready for deployment
- Security Monitoring — Access audit logs and active alarms to stay on top of system health and threats
- Operational Insights — Retrieve system information and health metadata for your VSA 10 instance
The Kaseya MCP Server exposes 10 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 Kaseya to LlamaIndex via MCP
Follow these steps to integrate the Kaseya 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 10 tools from Kaseya
Why Use LlamaIndex with the Kaseya MCP Server
LlamaIndex provides unique advantages when paired with Kaseya through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Kaseya tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Kaseya tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Kaseya, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Kaseya tools were called, what data was returned, and how it influenced the final answer
Kaseya + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Kaseya MCP Server delivers measurable value.
Hybrid search: combine Kaseya real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Kaseya 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 Kaseya for fresh data
Analytical workflows: chain Kaseya queries with LlamaIndex's data connectors to build multi-source analytical reports
Kaseya MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Kaseya to LlamaIndex via MCP:
get_agent_details
Get detailed information for a specific agent
get_system_info
Get VSA 10 system information
list_agents
Use this to check device availability and status. List all managed agents (devices) in Kaseya
list_alarms
List active system alarms
list_assets
List managed assets
list_audit_logs
List recent audit logs
list_groups
List all machine groups
list_organizations
List all organizations in Kaseya
list_scripts
List agent scripts
list_workflows
List automation workflows
Example Prompts for Kaseya in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Kaseya immediately.
"List all agents that are currently offline in Kaseya."
"Show me the recent audit logs for my VSA instance."
"List all machine groups in the organization."
Troubleshooting Kaseya MCP Server with LlamaIndex
Common issues when connecting Kaseya to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpKaseya + LlamaIndex FAQ
Common questions about integrating Kaseya 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 Kaseya 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 Kaseya to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.