HERE Mobility MCP Server for LlamaIndex 8 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add HERE Mobility as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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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 HERE Mobility. "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in HERE Mobility?"
)
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 HERE Mobility MCP Server
What you can do
Connect AI agents to the HERE Transit API for comprehensive public transportation planning:
LlamaIndex agents combine HERE Mobility tool responses with indexed documents for comprehensive, grounded answers. Connect 8 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.
- Discover transit trips between any two locations with bus, train, subway, tram, and ferry
- Find nearby stations by GPS coordinates or name search
- Get detailed route information with step-by-step transit instructions and transfers
- Check departure/arrival schedules for any station in real-time
- Plan multimodal journeys combining transit, walking, cycling, and scooter
- Get station details including accessibility, amenities, and serving lines
- Search trips with specific transport modes for customized travel preferences
The HERE Mobility MCP Server exposes 8 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 HERE Mobility to LlamaIndex via MCP
Follow these steps to integrate the HERE Mobility 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 8 tools from HERE Mobility
Why Use LlamaIndex with the HERE Mobility MCP Server
LlamaIndex provides unique advantages when paired with HERE Mobility through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine HERE Mobility tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain HERE Mobility tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query HERE Mobility, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what HERE Mobility tools were called, what data was returned, and how it influenced the final answer
HERE Mobility + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the HERE Mobility MCP Server delivers measurable value.
Hybrid search: combine HERE Mobility real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query HERE Mobility 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 HERE Mobility for fresh data
Analytical workflows: chain HERE Mobility queries with LlamaIndex's data connectors to build multi-source analytical reports
HERE Mobility MCP Tools for LlamaIndex (8)
These 8 tools become available when you connect HERE Mobility to LlamaIndex via MCP:
discover_trips
Returns trip details including departure/arrival times, duration, number of transfers, and transport modes. Use origin and destination in lat,lng format. Optionally specify departure or arrival time in ISO 8601 format. Best for planning multimodal journeys. Discover public transit trips between origin and destination using HERE Transit API
get_nearby_stations
More precise than get_stations with customizable radius. Returns station IDs, names, distances, coordinates, and available lines. Use this for comprehensive station discovery in an area. Find all transit stations within a specific radius of coordinates
get_route_details
Requires the trip ID from a discover_trips result plus original origin/destination and departure time. Use this to review full route before traveling. Get detailed route information for a specific transit trip
get_schedule
Useful for checking when the next bus, train, or subway arrives. Requires station ID from get_stations result. Optionally filter by direction (e.g., "northbound", "downtown"). Get departure/arrival schedule for a specific transit station
get_station_details
Requires station ID from station search results. Use this to review station facilities before planning trips. Get detailed information about a specific transit station
get_stations
Returns station IDs, names, coordinates, and available transport lines. Use this to find stations before planning trips. Find transit stations near a GPS coordinate
get_stations_by_name
g., "Central Station", "Times Square"). Returns matching stations with IDs, names, coordinates, and available transport lines. Use this when you know the station name but not exact coordinates. Find transit stations by name
search_multimodal_trips
Modes can include: transit (bus/train/subway/tram/ferry), walk, bicycle, scooter, taxi. Returns multimodal route options with time breakdown per mode. Use this when user wants to combine walking or cycling with public transit for optimal journey. Search trips combining multiple transport modes (transit, walk, bike, scooter)
Example Prompts for HERE Mobility in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with HERE Mobility immediately.
"Find me the best public transit route from Brandenburg Gate to Berlin Central Station departing at 8am tomorrow"
"What buses and trains depart from Times Square in the next 30 minutes?"
"Plan a multimodal trip from my location combining subway and bike sharing"
Troubleshooting HERE Mobility MCP Server with LlamaIndex
Common issues when connecting HERE Mobility to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpHERE Mobility + LlamaIndex FAQ
Common questions about integrating HERE Mobility 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 HERE Mobility 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 HERE Mobility to LlamaIndex
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.