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HERE Maps MCP Server

MCP Server

Enable LLMs to query HERE Maps services via a unified protocol

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Updated Jul 22, 2025

About

A Model Context Protocol server that exposes HERE Maps Platform APIs—geocoding, reverse geocoding, places search, routing, traffic, and map rendering—as tools for language models, enabling seamless spatial queries and navigation tasks.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

HERE Maps MCP Server

The HERE Maps MCP Server bridges the gap between large language models and real‑world geospatial data by exposing a rich set of HERE Maps Platform APIs as standardized MCP tools. By converting map‑related tasks into simple, declarative calls, the server allows LLMs to perform location lookups, route planning, traffic monitoring, and visual map rendering without leaving the conversational context. This eliminates the need for developers to write custom adapters or handle authentication logic, enabling rapid prototyping of location‑aware assistants.

At its core the server implements six distinct tools that mirror key HERE services. Geocoding and reverse geocoding translate addresses to coordinates and vice versa, feeding spatial data into downstream logic. Places search lets a model discover points of interest around a given coordinate, returning structured information such as name, address, and category. Routing provides turn‑by‑turn directions between two points for multiple transport modes, complete with polyline data and instruction summaries. Traffic incidents surface real‑time road events within a user‑defined radius, allowing assistants to warn users of delays or hazards. Finally, display map renders a static image for visual output, supporting multiple styles and zoom levels.

These capabilities are valuable for developers building AI assistants that need to answer location‑based queries, plan trips, or provide situational awareness. For example, a travel chatbot can geocode user input, search nearby restaurants, and then generate a route with real‑time traffic considerations—all through MCP calls. In logistics or delivery scenarios, the routing tool can compute optimal paths for vehicles while respecting transport mode constraints. The traffic tool enables dynamic updates, letting assistants notify drivers of incidents that may affect their journey.

Integration into AI workflows is straightforward. An LLM receives a user request, selects the appropriate tool via its intent or prompt, and passes the required parameters. The MCP server authenticates with HERE APIs using standard credentials, performs the request, and returns structured JSON. The model can then incorporate the response into its next utterance or trigger additional tool calls, creating a seamless loop of data retrieval and reasoning.

What sets this server apart is its unified MCP interface combined with the breadth of HERE’s geospatial ecosystem. Developers benefit from a single, well‑documented endpoint that covers everything from basic address lookup to advanced routing and traffic analytics. The server’s design encourages composability—models can chain multiple tools in a single conversation, enabling complex, context‑aware interactions without bespoke integration work.