Can I use multiple MCP servers?

Yes, this skill supports multi-server orchestration, allowing you to route commands to different servers from a single configuration file.

The Model Context Protocol (MCP) is an open standard that enables AI agents to connect to external tools, databases, and services.

Do I need Gemini CLI?

While Gemini CLI is the recommended primary execution method for speed, the skill also provides direct TypeScript scripts as a fallback.

Where are tool definitions stored?

Discovered tools are persisted in an assets/tools.json file, which allows the LLM to analyze capabilities without re-scanning servers every time.

How does this skill save context?

It uses subagents and external scripts to handle tool discovery and execution, preventing the main conversation from being cluttered with technical tool definitions.

MCP Management

Name: MCP Management
Author: mrgoonie

bymrgoonie

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1,395

Developer Tools

Streamlines Model Context Protocol (MCP) operations by discovering, analyzing, and executing tools from multiple servers with minimal context footprint.

About

MCP Management is a specialized skill designed to interface with Model Context Protocol (MCP) servers, allowing Claude to seamlessly discover and execute external tools, prompts, and resources. It solves the problem of context window pollution by delegating discovery and execution to subagents or CLI utilities, only bringing the necessary data into the main conversation. With support for multi-server configurations, intelligent tool selection via LLM analysis, and integration with the Gemini CLI, it provides a robust infrastructure for building highly capable AI agents that can interact with virtually any external data source or API.

Key Features

1,395 GitHub stars
Intelligent capability discovery for tools, prompts, and resources
Subagent delegation to prevent main context window bloat
Seamless integration with Gemini CLI for natural language tool execution
Automated tool catalog persistence to local JSON for fast reference
Multi-server management via unified JSON configuration

Use Cases

Executing complex MCP tool sequences without manual parameter mapping
Discovering and listing capabilities across multiple local or remote MCP servers
Building and debugging custom MCP client implementations within Claude

About

Key Features

1,395 GitHub stars
Intelligent capability discovery for tools, prompts, and resources
Subagent delegation to prevent main context window bloat
Seamless integration with Gemini CLI for natural language tool execution
Automated tool catalog persistence to local JSON for fast reference
Multi-server management via unified JSON configuration

Use Cases

Executing complex MCP tool sequences without manual parameter mapping
Discovering and listing capabilities across multiple local or remote MCP servers
Building and debugging custom MCP client implementations within Claude