HERE (Location & Maps) 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 HERE (Location & Maps) as an MCP tool provider through the 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 HERE (Location & Maps). "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in HERE (Location & Maps)?"
)
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 (Location & Maps) MCP Server
Connect your HERE Technologies account to any AI agent and take full control of cloud-native spatial analytics and location services through natural conversation.
LlamaIndex agents combine HERE (Location & Maps) tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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.
What you can do
- Geocoding & Search — Convert addresses to precise coordinates (and vice versa) and discover points of interest (POI) with advanced autosuggest directly from your agent
- Routing & Logistics — Calculate optimal routes for cars, trucks, or pedestrians, and generate complex distance matrices for efficient fleet management
- Isolines & Reachability — Visualize reachability polygons to see how far you can travel within a set time or distance limit from any origin point
- Traffic & Flow — Monitor real-time traffic speeds and congestion patterns using precise bounding box queries to optimize delivery times
- Weather & Environment — Fetch live weather observations and forecasts for any location on the globe to prepare for environmental impacts
- Place Details — Lookup rich metadata and schema for specific places using unique HERE Place IDs for deep point-of-interest analysis
The HERE (Location & Maps) 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 HERE (Location & Maps) to LlamaIndex via MCP
Follow these steps to integrate the HERE (Location & Maps) 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 HERE (Location & Maps)
Why Use LlamaIndex with the HERE (Location & Maps) MCP Server
LlamaIndex provides unique advantages when paired with HERE (Location & Maps) through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine HERE (Location & Maps) tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain HERE (Location & Maps) tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query HERE (Location & Maps), a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what HERE (Location & Maps) tools were called, what data was returned, and how it influenced the final answer
HERE (Location & Maps) + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the HERE (Location & Maps) MCP Server delivers measurable value.
Hybrid search: combine HERE (Location & Maps) real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query HERE (Location & Maps) 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 (Location & Maps) for fresh data
Analytical workflows: chain HERE (Location & Maps) queries with LlamaIndex's data connectors to build multi-source analytical reports
HERE (Location & Maps) MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect HERE (Location & Maps) to LlamaIndex via MCP:
autosuggest_query
Identify precise active arrays spanning native Location suggestions
calculate_routing_matrix
Provision a highly-available JSON Payload generating multi-node Maps
calculate_v8_isoline
router` optimizing where a user can travel within a set `time` or `distance` limit. Dispatch an automated validation check routing explicit Reachability Polygons
calculate_v8_route
Inspect deep internal arrays mitigating specific Traffic pathways
discover_places
Retrieve explicit Cloud logging tracing explicit POI categories
forward_geocode
Identify bounded routing spaces inside the Headless HERE Search limit
get_traffic_flow
json` detecting current congestion patterns via a Bounding Box limit. Retrieve the exact structural matching verifying Delivery Flow speeds
get_weather_observation
Enumerate explicitly attached structured rules exporting active Meteorology
lookup_place_id
Irreversibly vaporize explicit App nodes dropping live Place contexts
reverse_geocode
Perform structural extraction of properties driving active Pin boundaries
Example Prompts for HERE (Location & Maps) in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with HERE (Location & Maps) immediately.
"What's the best route from San Francisco to San Jose by car?"
"How far can I drive in 15 minutes from Times Square, NY?"
"What is the current weather observation for Tokyo?"
Troubleshooting HERE (Location & Maps) MCP Server with LlamaIndex
Common issues when connecting HERE (Location & Maps) to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpHERE (Location & Maps) + LlamaIndex FAQ
Common questions about integrating HERE (Location & Maps) 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 (Location & Maps) 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.
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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 (Location & Maps) to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.