HyperTrack 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 HyperTrack 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 HyperTrack. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in HyperTrack?"
)
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 HyperTrack MCP Server
Empower your AI agents to manage your logistics and field operations with HyperTrack. This MCP server allows you to list tracked devices, monitor active trips, manage geofences, track field workers, and view order statuses directly through the HyperTrack API. Ideal for automating last-mile delivery and field service management.
LlamaIndex agents combine HyperTrack 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.
The HyperTrack 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 HyperTrack to LlamaIndex via MCP
Follow these steps to integrate the HyperTrack 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 HyperTrack
Why Use LlamaIndex with the HyperTrack MCP Server
LlamaIndex provides unique advantages when paired with HyperTrack through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine HyperTrack tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain HyperTrack tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query HyperTrack, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what HyperTrack tools were called, what data was returned, and how it influenced the final answer
HyperTrack + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the HyperTrack MCP Server delivers measurable value.
Hybrid search: combine HyperTrack real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query HyperTrack 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 HyperTrack for fresh data
Analytical workflows: chain HyperTrack queries with LlamaIndex's data connectors to build multi-source analytical reports
HyperTrack MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect HyperTrack to LlamaIndex via MCP:
get_device
Retrieves details for a specific device
get_geofence
Retrieves details for a specific geofence
get_order
Retrieves details for a specific order
get_trip
Retrieves details for a specific trip
get_worker
Retrieves details for a specific worker
list_devices
Lists all registered devices
list_geofences
Lists all geofences
list_orders
Lists all orders
list_trips
Lists all trips
list_workers
Lists all workers
Example Prompts for HyperTrack in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with HyperTrack immediately.
"List all devices currently being tracked in HyperTrack."
"Show me the details for trip ID 'abc-123'."
"Check for any active geofences in the system."
Troubleshooting HyperTrack MCP Server with LlamaIndex
Common issues when connecting HyperTrack to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpHyperTrack + LlamaIndex FAQ
Common questions about integrating HyperTrack 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 HyperTrack 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 HyperTrack to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.