
Geo
MCP-Geo is an MCP server based on GeoPY, providing geocoding and reverse geocoding services and supporting multiple geocoding providers.
Python
8.2K
2.5 points

MCP Server Proj
The MCP Server project implements the coordinate system conversion function, supports EPSG, WKT, and Proj formats, and provides coordinate conversion and coordinate system list tools
Python
5.4K
2 points
O
Opencage Geocoding MCP
An MCP server based on the OpenCage Geocoding API, providing a two - way conversion function between addresses and geographical coordinates, including forward geocoding (address to coordinates), reverse geocoding (coordinates to address), and API status monitoring.
TypeScript
6.8K
2.5 points
Featured MCP Services

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.
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Notion Api MCP
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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.
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Duckduckgo MCP Server
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The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
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Gitlab MCP Server
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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.
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Unity
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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.
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Minimax MCP Server
The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.
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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.
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