FieldAware MCP Server for LlamaIndex 12 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add FieldAware 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 FieldAware. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in FieldAware?"
)
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 FieldAware MCP Server
FieldAware is a comprehensive field service management platform. This MCP server allows your AI agent to interact with your FieldAware account flawlessly.
LlamaIndex agents combine FieldAware tool responses with indexed documents for comprehensive, grounded answers. Connect 12 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.
Key Features
- Job Orchestration — List all active jobs and fetch detailed metadata for specific work orders natively.
- Customer Intelligence — Access customer profiles and contact details to personalize service interactions flawlessly.
- Invoice Management — Retrieve and inspect invoices to stay updated on billing and payments synchronously.
- Asset Tracking — List managed assets and equipment to ensure your field team has the right context natively.
- Quote & Item Access — Query active quotes and your product/service catalog flawlessly through the agent.
- Identity Verification — Verify the authorized user and permissions for the current API key flawlessly.
The FieldAware MCP Server exposes 12 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 FieldAware to LlamaIndex via MCP
Follow these steps to integrate the FieldAware 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 12 tools from FieldAware
Why Use LlamaIndex with the FieldAware MCP Server
LlamaIndex provides unique advantages when paired with FieldAware through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine FieldAware tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain FieldAware tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query FieldAware, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what FieldAware tools were called, what data was returned, and how it influenced the final answer
FieldAware + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the FieldAware MCP Server delivers measurable value.
Hybrid search: combine FieldAware real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query FieldAware 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 FieldAware for fresh data
Analytical workflows: chain FieldAware queries with LlamaIndex's data connectors to build multi-source analytical reports
FieldAware MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect FieldAware to LlamaIndex via MCP:
create_job
Create a new job
get_customer
Get details for a specific customer
get_invoice
Get details for a specific invoice
get_job
Get details for a specific job
get_whoami
Identify the user associated with the current API key
list_assets
List all assets
list_contacts
List all contacts
list_customers
List all customers
list_invoices
List all invoices
list_items
List all items (products/services)
list_jobs
List all jobs
list_quotes
List all quotes
Example Prompts for FieldAware in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with FieldAware immediately.
"List all my active jobs in FieldAware."
"Show me the contact info for customer ID 12345."
"Check if there are any unpaid invoices."
Troubleshooting FieldAware MCP Server with LlamaIndex
Common issues when connecting FieldAware to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpFieldAware + LlamaIndex FAQ
Common questions about integrating FieldAware 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 FieldAware 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 FieldAware to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.