How to Use the FieldAware MCP in LlamaIndex

Q: Can LlamaIndex query FieldAware assets for troubleshooting?

Yes. Your agent can run listassets to pull the equipment list, index the results, and let technicians search for past maintenance issues using natural language queries.

Q: Does LlamaIndex prevent hallucinations when reading FieldAware invoices?

Yes, because the agent queries live data using getinvoice and listinvoices. By grounding the agent's context in real-time API responses, it only references actual, existing financial records.

Index live FieldAware jobs and customer assets into LlamaIndex to eliminate agent hallucinations.

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Connect FieldAware MCP to LlamaIndex

Create your Vinkius account to connect FieldAware 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 FieldAware with LlamaIndex

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Index live field data for RAG

This MCP server lets LlamaIndex query your live records using `list_jobs` and `list_assets` to index them directly into your vector store. Your agent bases answers on real-time field data instead of outdated spreadsheets. When a tech asks about a specific machine's history, the agent pulls the exact history using `get_job`. It combines live API data with your technical manuals to give your team accurate, context-rich answers on the spot.

Search customer history semantically

By indexing `list_customers` and `list_contacts` into LlamaIndex, your agent can locate records using natural language. It understands who the customer is even if the spelling is slightly off. Once the right account is found, the agent can call `get_customer` to pull up their full profile. This speeds up customer service response times and keeps your dispatchers from wasting time on manual searches.

Analyze financial data with LlamaIndex

By using this MCP server, your agent can pull historical billing data using `list_invoices` and `list_quotes` to see which services drive revenue. It indexes these records so you can ask complex questions about your margins. The agent can drill down into specific line items using `list_items` or check individual bills with `get_invoice`. It gives your management team a clear, searchable view of cash flow without manual export steps.

Setup guide

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

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Common questions about FieldAware MCP in LlamaIndex

Connect the MCP client to your Vinkius endpoint and convert the tools into a tool spec. This lets your agent run tools like `list_jobs` to fetch live data and index the raw JSON output for semantic search.

Yes. Your agent can run `list_assets` to pull the equipment list, index the results, and let technicians search for past maintenance issues using natural language queries.

Yes, because the agent queries live data using `get_invoice` and `list_invoices`. By grounding the agent's context in real-time API responses, it only references actual, existing financial records.

Yes, LlamaIndex allows you to pass an allowed tools filter. You can restrict a customer-facing agent to only use `list_items` while keeping financial tools completely off-limits.

Yes. Your job records and asset details are processed through this MCP server's ephemeral, zero-trust connection. Vinkius handles the authentication securely, and no data is cached or stored on the hosting platform.

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