kubectl
Enables natural language interaction with Kubernetes resources, allowing developers to manage cluste...
Locate Your kubeconfig File
- Your Kubernetes configuration file (
kubeconfig) is typically located at~/.kube/configon most systems. - If you have a custom config location, make sure to note its path.
- Your Kubernetes configuration file (
(Optional) Prepare Additional Environment Variables
- You may specify additional settings for debugging or logging:
MCP_LOG_FILE: Path to a log file if you want to capture debug logs.MCP_DEBUG: Set to1to enable verbose logging.KUBECTL_MCP_LOG_LEVEL: Set as needed (e.g.,"DEBUG","INFO").
- You may specify additional settings for debugging or logging:
Install the Kubectl MCP Server
- Make sure you have Python 3.9+ and
kubectlinstalled and configured. - Install the server with:
pip install kubectl-mcp-tool - Or with Docker (with your
.kubedirectory mounted):docker run -p <your-port>:8000 -v $HOME/.kube:/root/.kube rohitghumare64/kubectl-mcp-server:latest
- Make sure you have Python 3.9+ and
Open the FastMCP Connection Interface
- Use your "Install Now" button to add a new MCP server connection.
Fill in the ENV Values in FastMCP
- When prompted in the FastMCP interface, fill in the following key environment variable:
KUBECONFIGwith the path to your Kubernetes config file (e.g.,/home/youruser/.kube/configor%USERPROFILE%\.kube\configon Windows).
- (Optionally) Add and fill:
MCP_LOG_FILE(if you want to store logs)MCP_DEBUG(set to1for debug mode)KUBECTL_MCP_LOG_LEVEL(as needed)
- When prompted in the FastMCP interface, fill in the following key environment variable:
Save and Connect
- Complete the connection setup as prompted by FastMCP.
- The Kubectl MCP server should now be able to authenticate with your Kubernetes cluster using the provided configuration.
Note:
You only need your valid Kubernetes kubeconfig file as the main credential. No API keys or cloud tokens are needed unless your cluster requires a specific setup not covered by a standard kubeconfig.
Quick Start
Choose Connection Type for
Authentication Required
Please sign in to use FastMCP hosted connections
Configure Environment Variables for
Please provide values for the following environment variables:
started!
The MCP server should open in . If it doesn't open automatically, please check that you have the application installed.
Copy and run this command in your terminal:
Make sure Gemini CLI is installed:
Visit Gemini CLI documentation for installation instructions.
Make sure Claude Code is installed:
Visit Claude Code documentation for installation instructions.
Installation Steps:
Configuration
Installation Failed
More for Cloud Platforms
View All →Salesforce
Unlock powerful Salesforce org management with the Salesforce DX MCP Server, designed for seamless interaction between large language models and Salesforce environments. This developer preview offers secure, direct access to Salesforce resources without exposing secrets, using TypeScript libraries and granular org allowlisting. Its modular toolsets cover org administration, data queries, user permissions, metadata deployment, and testing. Easily extendable and compatible with various clients like VS Code, Cursor, and more, it empowers developers to perform complex tasks with natural language commands while maintaining robust security. The MCP Server streamlines Salesforce DX workflows through an efficient, secure, and flexible protocol.
Netlify
Control your Netlify projects effortlessly using natural language through AI agents with Netlify MCP Server. This server follows the Model Context Protocol to enable code agents to create, deploy, and manage sites, configure access controls, handle environment variables, and more—all via simple prompts. It acts as a bridge between AI clients and Netlify’s API and CLI, empowering seamless automation and resource management. Whether retrieving team data or managing forms and extensions, Netlify MCP Server streamlines your workflow by integrating powerful AI-driven project control in an accessible, standardized way.
Azure All
Supercharge AI agents with seamless access to Azure services using Azure MCP Server. This project enables powerful automation and management of Azure resources with tools for databases, storage, monitoring, security, and best practices. Easily interact with services like Cosmos DB, SQL, Key Vault, Service Bus, and more—all within compatible AI platforms. Azure MCP Server is in Public Preview and rapidly evolving, making it a versatile solution for both developers and enterprise environments looking to integrate Azure functionality.
More for Monitoring
View All →Dual-Cycle Reasoner
Provides dual-cycle metacognitive reasoning framework that detects when autonomous agents get stuck in repetitive behaviors through statistical anomaly detection and semantic analysis, then automatically diagnoses failure causes and generates recovery strategies using case-based learning.
