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mcp-management

Manage MCP servers to discover, analyze, and execute tools and resources.

Updated Apr 18, 2026
Search Tags:#mcp#ai integration#multi-server#tool management#execution engine
One-click install
npx skills add https://github.com/lengo0951/pms --skill mcp-management-lengo0951
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: mcp-management
Source: https://github.com/lengo0951/pms/tree/main/.claude/skills/mcp-management
Command: npx skills add https://github.com/lengo0951/pms --skill mcp-management-lengo0951

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill provides an interface for discovering, analyzing, and executing tools from Model Context Protocol (MCP) servers, simplifying AI integration and managing external capabilities.

Core Features & Use Cases

  • Multi-Server Management: Connect to multiple MCP servers with a single configuration.
  • Intelligent Tool Discovery: Analyze which tools are relevant for specific tasks.
  • Progressive Disclosure: Load only necessary tool definitions when needed.
  • Execution Engine: Call MCP tools with proper parameter handling.
  • Context Efficiency: Delegate MCP operations to a subagent to keep the main context clean.

Quick Start

Run the mcp-management skill to list available tools and save to assets/tools.json: npx tsx scripts/cli.ts 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 in a single configuration?▼

MCP server management allows you to connect to multiple MCP servers through a single configuration interface, enabling unified discovery and execution of tools across your AI integration infrastructure.

How do I discover available tools from an MCP server?▼

Tool discovery from MCP servers is performed by running the provided command-line interface to list available tools, analyzing tool definitions, and saving the relevant capabilities to a local JSON file for execution.

Can I use Gemini CLI to interact with Model Context Protocol servers?▼

Gemini CLI integration is supported for interacting with MCP servers, allowing you to manage configurations, discover tool capabilities, and execute commands directly through the command-line interface.

How does progressive disclosure work for MCP tool definitions?▼

Progressive disclosure for MCP tools works by loading only the necessary tool definitions when needed, delegating operations to a subagent to keep the main AI context clean and efficient.

What is the best way to execute tools from an MCP server with proper parameters?▼

Executing MCP tools with proper parameter handling is best achieved using the built-in execution engine, which manages parameter inputs and invokes the correct tool definitions for reliable AI operations.

Do I need the Model Context Protocol SDK to manage MCP servers?▼

The Model Context Protocol SDK is required as a core dependency to manage MCP servers, providing the foundational protocols needed for discovering, analyzing, and executing tools within your environment.

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