Build with AI agents
AI and LLMs can significantly accelerate development with Amazon Location Service by providing intelligent assistance for API usage, code generation, and troubleshooting. By configuring your LLM client with the right MCP servers and context, you can create a powerful development assistant that understands AWS services and Amazon Location Service specifics. Using a minimal context and MCP configuration as recommended on this page can ensure your LLM model of choice has enough context to lead to correct results without overwhelming the context window. This can reduce hallucinations and increase result accuracy. This configuration also ensures that model knowledge cutoff does not impact the quality of the results. The Amazon Location Service agent context package provides ready-to-use integrations for popular AI coding assistants, guiding AI agents through adding maps, places search, geocoding, routing, and other geospatial features, including authentication setup, SDK integration, and best practices. Choose the installation method that matches your development environment.
For Kiro users
Kiro
Once installed, Amazon Location Service activates automatically when you mention keywords like "location", "maps", "geocoding", "routing", "places", "geofencing", or "tracking" in your prompts.
For Claude Code and Cursor users
For Claude Code and Cursor users, install the amazon-location-service plugin from the respective official marketplaces. The plugin includes MCP configuration automatically.
For other AI coding agents
For AI coding agents that support the Agent Skills
npx skills add aws-geospatial/amazon-location-agent-context
The CLI guides you through selecting which agent to install the skill for and at what scope (project or user level):
$ npx skills add aws-geospatial/amazon-location-agent-context ? Select an agent: (Use arrow keys) › Claude Code Cursor GitHub Copilot OpenCode Codex Antigravity ? Select a scope: (Use arrow keys) › Project — install in current directory (committed with your project) Global — install globally for all projects
You can also install for a specific agent directly:
GitHub Copilot:
npx skills add aws-geospatial/amazon-location-agent-context -a github-copilot
OpenCode:
npx skills add aws-geospatial/amazon-location-agent-context -a opencode
Codex:
npx skills add aws-geospatial/amazon-location-agent-context -a codex
Once installed, the skill activates automatically when your task involves location, maps, geocoding, routing, or other Amazon Location Service topics.
Note
For Claude Code and Cursor users, we recommend the For Claude Code and Cursor users for the best experience, as it includes MCP configuration automatically.
For direct context usage
If you are not using Kiro, Claude Code/Cursor plugins, or one of the agents supported by Agent Skills, you can load the context files directly into your LLM:
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Start with
context/amazon-location.mdfrom the amazon-location-agent-contextrepository for the service overview. -
Add specific files from
context/additional/as needed for your task, or allow the LLM client to read them on demand.
MCP Servers
The Kiro IDE (Power) and For Claude Code and Cursor users installations include MCP configuration automatically. If you are using the Kiro CLI, For other AI coding agents, or For direct context usage, configure the following server manually for full functionality:
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AWS MCP Server – AWS API exploration, execution, and documentation access. For setup instructions, see Getting started with the AWS MCP Server.