The makes it faster and easier to build with ¶¶Òõ¶ÌÊÓÆµ by equipping natural language AI coding tools with access to the ¶¶Òõ¶ÌÊÓÆµ platform. From designing maps to managing data, generating API tokens, formatting GeoJSON, and more, the ¶¶Òõ¶ÌÊÓÆµ MCP DevKit provides an interface to help AI assistants like Copilot, Cursor, and Claude Code to understand and streamline the ¶¶Òõ¶ÌÊÓÆµ development environment. ¶¶Òõ¶ÌÊÓÆµ is the first location platform to offer a specialized MCP server, designed to support AI coding tools and enhance the developer experience when building with ¶¶Òõ¶ÌÊÓÆµ.
Goodbye, repetitive tasks ¨C Hello, more fun with maps!
AI coding assistants are transforming the way that developers work. These tools are becoming increasingly smarter, capable of understanding complex tasks and automating key aspects of the development process to improve efficiency.?
Building with the ¶¶Òõ¶ÌÊÓÆµ platform is no different: What used to be tedious or repetitive tasks (like converting coordinates between reference systems) can now be handled swiftly by a coding assistant, provided it can access and understand the ¶¶Òõ¶ÌÊÓÆµ platform. No more jumping between tools, combing through documentation, or writing boilerplate just to test something.
The ¶¶Òõ¶ÌÊÓÆµ MCP DevKit currently supports three core tool categories designed to speed up everyday development work:
Token tools: Quickly generate, list, or retrieve public tokens without needing to visit your ¶¶Òõ¶ÌÊÓÆµ account dashboard.
Style tools: Create, update, and modify ¶¶Òõ¶ÌÊÓÆµ map styles with simple, natural-language commands.
Utility tools: Preview styles, visualize GeoJSON data in geojson.io, generate bounding boxes for countries or data files, and convert coordinates between WGS84 and Web Mercator (EPSG:3857) projections, no scripts required.
Focus on dev decisions that matter most
Let¡¯s consider the case of a developer who wants to build a Halloween-themed map with custom points for a candy crawl. Up to now, even experienced developers would need to go through several manual steps to create this map. They need to open ¶¶Òõ¶ÌÊÓÆµ Studio in a browser window to access the style editor, fetch and manage access tokens and style IDs, and create style preview links. If using a set of custom locations, such as houses participating in a Halloween candy crawl, they would likely first need to convert the data into GeoJSON, just to visualize and validate it. These steps slow down the process and pull focus away from higher-value development work on app logic and user experience.
Now, imagine a developer working with an AI assistant equipped with the ¶¶Òõ¶ÌÊÓÆµ Devkit server. The assistant understands the intent (¡°create a Halloween-themed map¡±) and can perform the sequence of actions required to complete the task. Using the Devkit server, the assistant can:
Automatically fetch a ¶¶Òõ¶ÌÊÓÆµ token and replace placeholder text with a token as needed for secure API access.
Generate a custom base style based on a natural language prompt like ¡°Create a Halloween-themed map. Make it look spooky and fun for Halloween.¡±
Create and open a live preview link in the developer¡¯s browser of choice, with no manual setup.
Convert a provided list of candy crawl locations into valid GeoJSON data, ready for visualization.?
What once took multiple tools and numerous manual steps can now be done with a single conversation bringing developing time down from hours to minutes. With the assistant handling repetitive tasks, developers are free to focus on the business logic and creative decisions that make their app stand out. This short video demonstrates how a developer can create style and edit a map using an AI assistant equipped with the ¶¶Òõ¶ÌÊÓÆµ MCP DevKit:
Create, format, and use geospatial data more efficiently?
Need a bounding box of Finland? Just ask. Want to convert coordinates from WGS84 to Web Mercator? Say the word. Tasks that once took multiple steps can now be handled in seconds by your AI coding assistant. Equipped with the ¶¶Òõ¶ÌÊÓÆµ MCP DevKit, an assistant can understand what is needed and use tools like FormatGeoJSON, ReprojectCoordinates, and GetBoundingBox to complete the tasks accurately.
The ¶¶Òõ¶ÌÊÓÆµ MCP DevKit vs. MCP Server
¶¶Òõ¶ÌÊÓÆµ offers two distinct MCP Servers:
The ¶¶Òõ¶ÌÊÓÆµ MCP Server, built to equip Agents with the geospatial expertise and spatial awareness needed to answer location-based questions like ¡°What¡¯s the best route to X?¡± or ¡°Where would be a strategic location to open a pet grooming business in Austin?¡±.
The , designed for developers building with ¶¶Òõ¶ÌÊÓÆµ, enhancing the engineering experience by enabling AI coding assistants to connect directly with the ¶¶Òõ¶ÌÊÓÆµ platform.
The two MCP tools are distinct yet complementary ¡ª the DevKit helps developers build any ¶¶Òõ¶ÌÊÓÆµ-powered application, while the MCP Server is purpose-built for agentic workflows, equipping those agents with the spatial intelligence to answer user queries.
Add the DevKit to your workflow
The ¶¶Òõ¶ÌÊÓÆµ MCP DevKit is and available to all ¶¶Òõ¶ÌÊÓÆµ accounts. Install it into a local environment, IDE, or CLI and enhance AI coding tools with ¶¶Òõ¶ÌÊÓÆµ access.
The ¶¶Òõ¶ÌÊÓÆµ Location AI team is actively adding new capabilities to the DevKit and other tools based on developer feedback. Share ideas and requests in the .
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