Can I use this with the Gemini CLI?

Yes, the skill is specifically designed to integrate with Gemini CLI, offering symlink utilities to sync configurations and using it as the primary high-speed execution method.

How does this skill handle multiple MCP servers?

It uses a centralized configuration file located at .claude/.mcp.json and provides scripts to aggregate and route commands to multiple servers simultaneously.

Why does it save tools to assets/tools.json?

Saving to a local JSON file allows for near-instant tool lookup, offline browsing, and version control of available capabilities without needing to query active servers every time.

What is the benefit of using the mcp-manager subagent?

The mcp-manager subagent handles the heavy lifting of tool discovery and analysis, preventing the main agent's context window from being cluttered with large tool definitions and schemas.

MCP Management & Orchestration

Name: MCP Management & Orchestration
Author: Activer007

byActiver007

개발자 도구

Orchestrates Model Context Protocol (MCP) servers to discover and execute tools while maintaining optimal context window efficiency.

소개

This skill enables Claude to seamlessly interface with the Model Context Protocol (MCP), providing a robust framework for discovering and executing external capabilities without overwhelming the main context window. It centralizes MCP server configuration, automates tool discovery by persisting a local catalog, and utilizes an intelligent execution hierarchy—prioritizing the Gemini CLI for speed and falling back to a dedicated subagent for complex orchestration. Whether you are building custom MCP clients or integrating disparate data sources, this skill ensures efficient context management and high-reliability tool execution across multiple servers.

주요 기능

Multi-server management via centralized configuration and symlink support
Seamless Gemini CLI integration for high-performance, natural language tool execution
Automated MCP tool, prompt, and resource discovery with local JSON persistence
Context-efficient subagent delegation to prevent main context window pollution
0 GitHub stars
Intelligent LLM-driven tool selection and intent-based parameter mapping

사용 사례

Maintaining a lean main context window by offloading heavy tool discovery tasks to specialized subagents
Discovering and indexing capabilities across multiple configured MCP servers for fast reference
Executing complex MCP tools programmatically with automated error handling and retries

소개

주요 기능

Multi-server management via centralized configuration and symlink support
Seamless Gemini CLI integration for high-performance, natural language tool execution
Automated MCP tool, prompt, and resource discovery with local JSON persistence
Context-efficient subagent delegation to prevent main context window pollution
0 GitHub stars
Intelligent LLM-driven tool selection and intent-based parameter mapping

사용 사례

Maintaining a lean main context window by offloading heavy tool discovery tasks to specialized subagents
Discovering and indexing capabilities across multiple configured MCP servers for fast reference
Executing complex MCP tools programmatically with automated error handling and retries