Introduction: What is the Model Context Protocol (MCP)?

To make it easier for AI assistants to communicate with databases and various external systems, the Model Context Protocol (MCP) was created – a kind of API for AI that describes how to use a given service.

MCP works a bit like Swagger / OpenAPI for developers: it precisely specifies which “tools” are available, what parameters they accept, and what responses they return, so that an AI assistant knows how to query a given server correctly. The difference is that MCP is designed exclusively for AI, not for humans – it does not provide a traditional user interface, only a contract that a language model can use.

This post is therefore mainly aimed at developers of AI applications and assistants: it describes a new tool they can integrate into their projects to work more effectively with OpenStreetMap tagging data.

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A few months ago, I worked on a new project: the OSM Tagging Schema MCP — a Model Context Protocol (MCP) server built for AI assistants and LLM applications that interact with OpenStreetMap tagging data.

It serves as a bridge between AI systems and the official OpenStreetMap tagging schema, allowing agents to validate tags, query values, search presets, and suggest improvements using the structured knowledge from the @openstreetmap/id-tagging-schema library.

The current 3.x release is technically stable — all tools and endpoints work reliably without errors — but it should still be considered experimental. Active development on version 3 has ended; for now, I only maintain it through dependency updates.

The next major step will be version 4, a complete rewrite developed with AI-assisted coding, focusing on a cleaner architecture, long-term maintainability, and deeper MCP integration.

You can try the service live here: mcp.gander.tools/osm-tagging

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I started working on a helper for OSM because I use several community-made tools, and it’s not very convenient to copy and paste links, nodes, or IDs into these tools. So, I decided to write my own userscript. This script will detect what the user is currently viewing and attach the appropriate links already prepared for the tool.

It’s a very simple script, and anyone can create something like this. However, I plan to use AI to help with tagging in the future. It began with a simple rule I used for tagging points, which made me realize I could automate it more. This will be implemented in the helper.

The helper will use Vue.js to control the interface view. In future I plan to release an extension for Chrome and Firefox.

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I would appreciate any suggestions or links to web applications that might be useful.

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Current releases