Axle 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 Axle 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 Axle. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Axle?"
)
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 Axle MCP Server
Empower your AI agent to orchestrate your entire logistics operation with Axle, the comprehensive fleet management platform. By connecting Axle to your agent, you transform complex supply chain monitoring into a natural conversation. Your agent can instantly track real-time vehicle locations, audit driver duty statuses, monitor shipment progress, and retrieve essential shipping documents without you ever touching a heavy transportation dashboard. Whether you're managing a local delivery crew or a national trucking network, your agent acts as a real-time dispatch coordinator, ensuring your fleet is always moving and compliant.
LlamaIndex agents combine Axle 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.
What you can do
- Vehicle Tracking — List all vehicles in your fleet and retrieve real-time GPS locations and technical health details.
- Driver Management — Audit driver profiles, monitor current duty statuses (On Duty, Driving, etc.), and check available Hours of Service (HOS).
- Load Orchestration — Monitor shipment progress, list active loads, and update shipment details dynamically via natural language.
- Document Retrieval — Access scanned shipping documents and paperwork associated with specific loads for instant auditing.
- System Health — Quickly verify connection status and logistics network integrity directly from your chat interface.
The Axle 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 Axle to LlamaIndex via MCP
Follow these steps to integrate the Axle 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 Axle
Why Use LlamaIndex with the Axle MCP Server
LlamaIndex provides unique advantages when paired with Axle through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Axle tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Axle tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Axle, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Axle tools were called, what data was returned, and how it influenced the final answer
Axle + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Axle MCP Server delivers measurable value.
Hybrid search: combine Axle real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Axle 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 Axle for fresh data
Analytical workflows: chain Axle queries with LlamaIndex's data connectors to build multi-source analytical reports
Axle MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect Axle to LlamaIndex via MCP:
get_account_check
Verify Axle connection and system health
get_driver
Get specific profile details for a driver
get_driver_availability
Check a driver remaining hours of service (HOS)
get_load
Get details for a specific load
get_vehicle
Get specific details for a single vehicle
get_vehicle_location
Get the last known GPS location of a vehicle
list_documents
Retrieve scanned shipping documents associated with shipments
list_drivers
List all drivers in the system
list_loads
List all shipments/loads
list_vehicles
List all vehicles in the fleet
update_driver_status
Update a driver current duty status
update_load
Update a load/shipment details
Example Prompts for Axle in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Axle immediately.
"Where is vehicle ID 'TRUCK-101' right now?"
"List all active loads and their current status."
"Check the available Hours of Service (HOS) for driver 'John Doe'."
Troubleshooting Axle MCP Server with LlamaIndex
Common issues when connecting Axle to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpAxle + LlamaIndex FAQ
Common questions about integrating Axle 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 Axle 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 Axle to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.