3 Essential MCP Servers for Personalized Local AI

Local LLMs are becoming increasingly popular, but they often lack personalization and utility due to their reliance on cloud services. That’s where three essential MCP servers come in – SearXNG-MCP, Spotify-MCP, and MCP-Obsidian.

These servers can be used with OpenWebUI or LM Studio to fill the gaps of what cloud-based LLMs can do. They work by abstracting data from APIs and providing a local interface for your model to access information. This ensures that your personal data remains private and secure.

Here’s how each server works:

– SearXNG-MCP: Provides search capabilities, allowing you to query the web directly from your local LLM.
– Spotify-MCP: Allows you to control Spotify and fetch music details, making recommendations based on your current listening history.
– MCP-Obsidian: Links your model directly with your Obsidian vault, enabling you to query and update knowledge base.

By chaining these servers together or using them individually, you can create a personalized AI system that’s connected to your personal world. This setup is not only more secure but also provides a better experience than cloud-based models.

Start by setting up SearXNG-MCP for web searches alone. The other two servers are optional but highly recommended for their utility and personalization capabilities.

Source: https://www.xda-developers.com/mcp-servers-changed-local-llm-better-than-cloud