mcp-management

Discover, analyze, and orchestrate MCP tools across multiple servers via CLI.

Updated Mar 19, 2026

Search Tags:#automation #cli #mcp #management #multi-server #context-management #tool-discovery

Ready to run

npx skills add https://github.com/congthang12312/Sentinel-AI-test --skill mcp-management-congthang12312

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: mcp-management
Source: https://github.com/congthang12312/Sentinel-AI-test/tree/main/.agent/skills/mcp-management
Command: npx skills add https://github.com/congthang12312/Sentinel-AI-test --skill mcp-management-congthang12312

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires @modelcontextprotocol/sdk, and includes scripts (resource) and references (resource) components.

What problem does it solve?

MCP integration and management across multiple servers is complex, noisy, and prone to context leakage; this skill centralizes discovery, analysis, and execution to keep the main context lean and efficient.

Core Features & Use Cases

Multi-server management: connect to and orchestrate several MCP servers from a single config.
Intelligent tool discovery: dynamically select relevant tools/prompts/resources based on the task requirements.
Context-efficient execution: delegate MCP operations to subagents and return concise results.
Persistent catalog: automatically save discovered tools to a JSON catalog for fast reference.
Use case: debug and integrate MCP setups by listing capabilities and executing chosen tools across servers.

Quick Start

Install dependencies, configure your MCP servers in .claude/.mcp.json, and run the MCP management CLI to list tools.

Frequently Asked Questions about mcp-management

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I manage multiple MCP servers without polluting the main context window?▼

You can manage multiple MCP servers by loading configurations from a central .claude/.mcp.json file and delegating operations to subagents. This approach executes MCP tools on-demand and returns concise, structured results to keep your main context clean and efficient.

What is MCP tool discovery and how does it work across diverse environments?▼

MCP tool discovery dynamically selects relevant tools, prompts, and resources based on your task requirements. It connects to servers via a TypeScript client over stdio transports, automatically saving discovered capabilities to a persistent JSON catalog for fast future reference.

How to list and call MCP tools using a CLI?▼

To list and call MCP tools, configure your servers in .claude/.mcp.json and run the provided CLI commands. The skill exposes commands for listing available tools, prompts, and resources, and handles executing chosen tools across your connected servers.

Can I use a TypeScript client to orchestrate MCP servers over stdio transports?▼

Yes, you can orchestrate MCP servers using a TypeScript client that communicates over stdio transports. It requires installing the @modelcontextprotocol/sdk dependency and allows you to connect to, analyze, and execute commands across several servers from a single config.

Does MCP multi-server management require a specific configuration file format?▼

Yes, multi-server management requires a .claude/.mcp.json configuration file to define your servers. This file acts as the central source for the TypeScript client to connect and orchestrate capabilities across your specified environments.

Why does MCP integration cause context leakage and how can I prevent it?▼

MCP integration causes context leakage when raw execution details flood the main window, but you can prevent it by centralizing discovery and execution. Delegating operations to subagents ensures only concise, structured results are returned to the primary context.