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Inoyu Apache Unomi MCP Server

An implementation of Anthropic's Model Context Protocol for the Apache Unomi CDP

Created by sergehuber2025/03/27
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What is Inoyu Apache Unomi MCP Server?

what is Inoyu Apache Unomi MCP Server? The Inoyu Apache Unomi MCP Server is an implementation of the Model Context Protocol (MCP) designed to enable user context management through the Apache Unomi customer data platform (CDP), facilitating applications like Claude to maintain user profiles and context. how to use Inoyu Apache Unomi MCP Server? To use the server, install it alongside the Claude Desktop application by configuring the required environment variables for profile management and connecting to your Unomi server. You will also need to add specific server configuration in claude_desktop_config.json. key features of Inoyu Apache Unomi MCP Server? Email-based profile creation and retrieval Automatic session and scope management Support for retrieving and updating user profile properties in JSON format Basic tools for profile searching and scope creation use cases of Inoyu Apache Unomi MCP Server? Maintaining user preferences over multiple interactions in a conversational AI application. Managing user profiles for personalized experiences in applications utilizing Claude. Enabling comprehensive user context tracking via email and profile ID. FAQ from Inoyu Apache Unomi MCP Server? How does the server identify users? It uses either email lookup for matching profiles or a fallback ID from the environment variables. Is this implementation ready for production use? No, this is an early implementation intended for demonstration and experimentation purposes only. What environment variables are required? The server needs several variables like UNOMI_BASE_URL, UNOMI_USERNAME, UNOMI_PASSWORD, UNOMI_PROFILE_ID, and other relevant credentials.

As an MCP (Model Context Protocol) server, Inoyu Apache Unomi MCP Server enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.

How to use Inoyu Apache Unomi MCP Server

To use the server, install it alongside the Claude Desktop application by configuring the required environment variables for profile management and connecting to your Unomi server. You will also need to add specific server configuration in claude_desktop_config.json. key features of Inoyu Apache Unomi MCP Server? Email-based profile creation and retrieval Automatic session and scope management Support for retrieving and updating user profile properties in JSON format Basic tools for profile searching and scope creation use cases of Inoyu Apache Unomi MCP Server? Maintaining user preferences over multiple interactions in a conversational AI application. Managing user profiles for personalized experiences in applications utilizing Claude. Enabling comprehensive user context tracking via email and profile ID. FAQ from Inoyu Apache Unomi MCP Server? How does the server identify users? It uses either email lookup for matching profiles or a fallback ID from the environment variables. Is this implementation ready for production use? No, this is an early implementation intended for demonstration and experimentation purposes only. What environment variables are required? The server needs several variables like UNOMI_BASE_URL, UNOMI_USERNAME, UNOMI_PASSWORD, UNOMI_PROFILE_ID, and other relevant credentials.

Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.

Use Cases for this MCP Server

  • No use cases specified.

MCP servers like Inoyu Apache Unomi MCP Server can be used with various AI models including Claude and other language models to extend their capabilities through the Model Context Protocol.

About Model Context Protocol (MCP)

The Model Context Protocol (MCP) is a standardized way for AI agents to communicate with various services and tools. MCP servers like Inoyu Apache Unomi MCP Server provide specific capabilities that can be accessed through a consistent interface, making it easier to build powerful AI applications with complex workflows.

Browse the MCP Directory to discover more servers and clients that can enhance your AI agents' capabilities.