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MCP Servers

by alfredojrc

This repository outlines a multi-MCP server architecture for managing complex infrastructure projects, particularly those involving AI agents and n8n workflows. It recommends a modular approach with specialized servers for different components like Kubernetes, VMware, and vector databases.

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What is MCP Servers?

This is a recommended architecture for using multiple MCP (Micro Control Plane) servers to manage different aspects of a complex infrastructure project. It advocates for specialized servers for components like Kubernetes, VMware, n8n workflows, and vector databases to improve maintainability, security, and scalability.

How to use MCP Servers?

The recommended approach is to set up individual MCP servers for each component of your infrastructure. This involves configuring servers for n8n workflows, VMware infrastructure management, Kubernetes deployment and management, a vector database (like LanceDB), and a shell/CLI server for executing infrastructure commands. Each server would be configured to interact with its specific component.

Key features of MCP Servers

  • Modular architecture

  • Component-specific servers

  • Improved maintainability

  • Enhanced security isolation

  • Scalability

  • Integration with AI agents and n8n workflows

  • Vector database integration for knowledge storage and retrieval

Use cases of MCP Servers

  • Managing Kubernetes deployments

  • Managing VMware infrastructure

  • Orchestrating n8n workflows

  • Storing and retrieving infrastructure knowledge using a vector database

  • Executing infrastructure commands via a shell/CLI server

  • Integrating AI agents with infrastructure management

FAQ from MCP Servers

Why use multiple MCP servers instead of one?

Multiple specialized servers offer better maintainability, security isolation, and scalability compared to a single monolithic server.

What is an MCP server?

An MCP server (Micro Control Plane) is a lightweight server designed to manage a specific aspect of an infrastructure or application.

Which vector database should I use?

LanceDB is recommended, but other vector databases can be used depending on your specific requirements.

How do I integrate the MCP servers with my AI agent?

Each MCP server should expose an API that your AI agent can interact with to manage the corresponding infrastructure component.

What are the benefits of using a vector database in this architecture?

A vector database allows your AI agent to store and retrieve information about your infrastructure, enabling semantic search and memory retention for improved decision-making.