Claude-Code-MCP-Manager

🥈Silver

@qdhenry

A comprehensive tool to manage Model Context Protocol (MCP) configurations for Claude code

2400Updated 2d ago

Intermediate30min to implementautomation

Saves ~210 min per use

Quick InstallView Source

git clone https://github.com/qdhenry/Claude-Code-MCP-Manager.git

Works with:

Claude

Overview

About This Skill

A comprehensive tool to manage Model Context Protocol (MCP) configurations for Claude code

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/qdhenry/Claude-Code-MCP-Manager

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Act as an expert MCP configuration manager for Claude code. I need to [TASK] for my [COMPANY] in the [INDUSTRY] sector. Here is the [DATA] I have available. Provide a detailed MCP configuration plan with the following requirements: [REQUIREMENTS].

Example Output

# MCP Configuration Plan for [COMPANY]

## Overview
The following MCP configuration plan is designed to optimize Claude code performance for [COMPANY] in the [INDUSTRY] sector. The plan addresses the specific requirements of [REQUIREMENTS] and leverages the provided [DATA].

## Configuration Details
- **Context Window Size**: 128 tokens
- **Memory Retention**: 7 days
- **Data Sensitivity**: High
- **Response Format**: JSON

## Implementation Steps
1. **Initial Setup**: Configure the MCP settings in the Claude code environment.
2. **Data Integration**: Import the provided [DATA] into the system.
3. **Testing**: Run initial tests to ensure the configuration meets the requirements.
4. **Optimization**: Adjust settings based on test results for optimal performance.
5. **Deployment**: Roll out the configuration across the [COMPANY] systems.

## Expected Outcomes
- Improved code performance and accuracy.
- Enhanced data handling and security.
- Streamlined workflows for [COMPANY] in the [INDUSTRY] sector.