How to Use the MaintainX MCP in LlamaIndex
Index your maintenance history using LlamaIndex for grounded, data-backed repair insights.
Works with every AI agent you already use
…and any MCP-compatible client
Connect MaintainX MCP to LlamaIndex
Create your Vinkius account to connect MaintainX 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.
Index maintenance logs with LlamaIndex
Convert your historical `list_maintenance_orders` data into a vector index. LlamaIndex queries this knowledge base to answer technical questions about past equipment performance. Ground your AI responses in actual work history. When a technician asks about a recurring issue, the agent retrieves the exact work order details from the index.
Searchable asset metadata
Push `get_asset_details` results into your LlamaIndex knowledge graph. Your agents now understand the relationship between asset history and current maintenance requirements. Stop guessing about equipment age or service intervals. Your index provides a semantic layer over the raw MaintainX data, making it easy to find specific hardware status.
Contextual maintenance reasoning
Use `list_maintenance_assets` to populate your RAG pipeline with live data. LlamaIndex combines this with your existing documents to provide a complete view of your site. Your agents answer questions based on current reality, not stale records. If an asset status changes, the index updates, ensuring your AI stays perfectly aligned with the floor.
Set up MaintainX 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 MaintainX 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 MaintainX tools.",
)
response = await agent.run("List recent MaintainX data") Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by MaintainX. 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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60%
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Common questions about MaintainX MCP in LlamaIndex
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