Osm Tagging Schema MCP
This is a server based on the Model Context Protocol (MCP), specifically designed to provide an access interface to the OpenStreetMap tagging knowledge base for AI agents and LLM applications, supporting functions such as tag query, preset discovery, and validation.
rating : 2.5 points
downloads : 0
What is the OpenStreetMap Tagging Schema MCP Server?
This is a knowledge base server specifically designed for AI assistants (such as Claude, ChatGPT, etc.). It provides a complete knowledge base of the OpenStreetMap (OSM) map tagging system, enabling AI to query and understand the correct tags and attributes of various places (such as restaurants, parks, schools, etc.) in OSM maps.How to use this service?
You don't need to use this server directly. It needs to be integrated into an AI assistant to function. When you ask the AI a question about OSM map tags, the AI will automatically call this server to obtain accurate information.Applicable scenarios
This service is particularly useful when you need to know the correct tags for various places in OpenStreetMap maps. For example: querying what tags should be used for a restaurant, what attributes can be set for a park, and verifying whether the tags you set are correct, etc.Main features
Tag query
Query detailed information and possible values of OSM tags to help you understand the specific uses of each tag
Tag search
Search for relevant OSM tags by keywords to quickly find the tags you need
Preset configuration discovery
Explore the predefined configuration combinations (presets) in OSM, which contain recommended combinations of relevant tags
Tag validation
Check whether the tags you provide are correct and valid to avoid using incorrect or outdated tags
Outdated tag check
Identify and warn about outdated or non - recommended tags and suggest better alternatives
Improvement suggestions
Provide optimization suggestions for your tags to make them more in line with the best practices of the OSM community
Advantages
Authoritative and accurate: Based on the official OSM tag specification library to ensure the accuracy of information
Real - time update: Regularly synchronize the latest changes in the OSM tag specification
Easy to integrate: Supports multiple AI assistant platforms, including Claude Code and Claude Desktop
Comprehensive coverage: Includes all tags and preset configurations recognized by the OSM community
Limitations
Requires an AI assistant: Cannot be used directly and must be accessed through an AI assistant
Technical dependence: Requires certain technical knowledge for configuration and integration
Network requirement: An online service requires a stable network connection
How to use
Confirm that your AI assistant supports MCP
Currently, AI assistants that support the MCP protocol include Claude Code and Claude Desktop. Make sure you are using one of these tools.
Configure the AI assistant
Add the configuration of this MCP server to the configuration file of the AI assistant. The configuration methods of different AI assistants vary slightly.
Start using
After the configuration is completed, restart the AI assistant. Now you can ask the AI questions about OSM tags, and the AI will automatically use this server to obtain accurate information.
Usage examples
Case 1: Query restaurant tags
When you want to know what tags should be used for restaurants in OpenStreetMap
Case 2: Verify tag correctness
When you are not sure whether the OSM tags you set are correct
Case 3: Search for relevant tags
When you need to find all tags related to a specific type of place
Frequently Asked Questions
What software do I need to install to use this service?
Is this service free?
On which AI assistants can I use this service?
Is the data of this service up - to - date?
What should I do if I encounter a problem?
Related resources
GitHub project homepage
View source code, submit issues, and participate in contributions
Official documentation
Detailed usage guide, API reference, and deployment instructions
OpenStreetMap official website
Learn about the OpenStreetMap project and community
MCP protocol official website
Learn about the technical specifications of the Model Context Protocol

Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
29.5K
5 points

Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
58.7K
4.3 points

Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
20.1K
4.3 points

Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
17.6K
4.5 points

Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
53.6K
4.5 points

Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
26.0K
5 points

Gmail MCP Server
A Gmail automatic authentication MCP server designed for Claude Desktop, supporting Gmail management through natural language interaction, including complete functions such as sending emails, label management, and batch operations.
TypeScript
18.5K
4.5 points

Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
81.2K
4.7 points


