Mcp_servers

Mcp_servers

By alfredojrc GitHub

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mcp_servers infrastructure-management
Overview

what is Mcp_servers?

Mcp_servers is a project that provides multiple specialized MCP (Managed Control Plane) servers for managing various aspects of infrastructure, including Kubernetes deployment and VMware management.

how to use Mcp_servers?

To use Mcp_servers, set up multiple MCP servers tailored to specific components of your infrastructure, such as Kubernetes, VMware, and n8n workflows. Each server can be configured independently to manage its respective tasks.

key features of Mcp_servers?

  • Modular architecture with multiple specialized servers
  • Integration capabilities for Kubernetes, VMware, and n8n
  • Security isolation for sensitive data
  • Support for vector databases for knowledge storage and retrieval

use cases of Mcp_servers?

  1. Managing Kubernetes deployments efficiently
  2. Orchestrating workflows with n8n
  3. Storing and retrieving infrastructure knowledge using vector databases
  4. Executing infrastructure commands through a CLI MCP server

FAQ from Mcp_servers?

  • Can I use Mcp_servers for different types of infrastructure?

Yes! Mcp_servers are designed to manage various infrastructure components, including Kubernetes and VMware.

  • How do I ensure security with multiple MCP servers?

Each server can be isolated to handle specific tasks, reducing the risk of data exposure.

  • Is there support for integrating with existing tools?

Yes! Mcp_servers can be integrated with existing tools like n8n for workflow management.

Content

MCP servers for each project.

1st project: k8s_cluster_1

2nd project: n8n_project_1

3rd project: bug_bounty_1

############### MCP & Vector DB ###############

For your specific project involving an AI agent on n8n that manages VMware infrastructure and Kubernetes deployment, I'll provide more targeted advice.

Let me search for information specifically about integrating MCP with infrastructure management and n8n.

Ran tool Based on the search results and your specific use case involving an AI agent app on n8n that manages VMware infrastructure and Kubernetes deployment, I can provide more targeted advice.

MCP Server Architecture for Your Infrastructure Management Project

For your complex infrastructure management use case, I recommend using multiple specialized MCP servers rather than a single server. Here's why:

  1. Component-Specific Servers: Looking at the search results, there are dedicated MCP servers for:

  2. Integration Benefits: Each server can focus on a specific part of your infrastructure:

    • One for VMware infrastructure management
    • One for Kubernetes deployment and management
    • One for n8n workflow orchestration

  3. Maintenance Advantages: When you need to update or modify functionality for one component (e.g., Kubernetes), you only need to update that specific server without affecting others.

  4. Security Isolation: Keeping credentials and sensitive data isolated to specific servers reduces the risk surface area.

Regarding Vector DB

Yes, you should include a vector database MCP server in your architecture for the following reasons:

  1. Infrastructure Knowledge Base: A vector DB will allow your AI agent to store and retrieve information about your infrastructure (server configurations, deployment patterns, troubleshooting steps).

  2. Available Options: There are several MCP servers for vector databases already available:

  3. Semantic Search: A vector DB enables your agent to perform semantic searches across your infrastructure documentation, logs, and configurations.

  4. Memory Retention: Your agent will be able to store and retrieve previous infrastructure operations, which is crucial for maintaining state and learning from past deployments.

I recommend setting up the following MCP servers for your project:

  1. n8n MCP Server: To interact with your agent's workflows
  2. VMware MCP Server: For VMware infrastructure management
  3. Kubernetes MCP Server: For K8s deployment and management
  4. Vector DB MCP Server (LanceDB or similar): For knowledge storage and retrieval
  5. Shell/CLI MCP Server: For executing infrastructure commands

This modular approach will give you the flexibility to extend and maintain each component independently while allowing your AI agent to orchestrate across all of them.

Would you like more specific information about setting up any of these MCP servers for your infrastructure management use case?

No tools information available.
mcp_servers

Collection of MCP Servers ofr use with anthropic and other models

mcp_servers anthropic
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