Overview
A Model Context Protocol (MCP) server that integrates with the Uberall API, enabling AI assistants to seamlessly manage business listings, locations, and social media presence across multiple platforms. The Uberall MCP Server acts as a bridge between AI agents and the Uberall platform, allowing MCP-compatible tools such as Claude Desktop, Cursor, and VS Code Copilot to access and manipulate Uberall data through a consistent, protocol-driven interface. It exposes a set of MCP-powered tools for core workflows: find_businesses to locate accessible businesses; find_locations to retrieve and filter locations; create_social_post to publish posts to supported social networks; and search_social_posts to monitor and filter existing posts. The server is designed to be fast and lightweight, built with Kotlin coroutines, and can run as a pre-built JAR, in Docker, or be built from source with Gradle. It requires Java 17+ and environment variables UBERALL_URL and UBERALL_ACCESS_TOKEN for authentication. The documentation includes setup examples for Claude Desktop and other MCP clients, as well as error handling guidance and troubleshooting tips.
Features
MCP Protocol Compliant
Works with any MCP-compatible AI assistant to enable external tool access.
Business Management
Find and manage business listings reachable by the user.
Location Management
Access and manage location data across businesses.
Social Media Integration
Create posts across multiple platforms (Google, Facebook, etc.).
Advanced Search
Filter businesses, locations, and social posts with refined queries.
Docker Ready
Pre-built multi-platform Docker images for easy deployment.
Fast & Lightweight
Built with Kotlin coroutines for efficient, responsive performance.
Who Is This For?
- AI developers:Build or integrate MCP-enabled assistants with Uberall to manage business data across platforms.
- MCP clients and integrators:Configure MCP servers in Claude Desktop, Cursor, VS Code, and other MCP-compatible tools to access Uberall data.
