dev-swarm-mcp-server

Add and manage Model Context Protocol (MCP) servers for AI agents, including transports, scopes, and config files. Use when extending agent capabilities with new tools or data sources.

$ Installer

git clone https://github.com/X-School-Academy/ai-dev-swarm /tmp/ai-dev-swarm && cp -r /tmp/ai-dev-swarm/dev-swarm/skills/dev-swarm-mcp-server ~/.claude/skills/ai-dev-swarm

// tip: Run this command in your terminal to install the skill


name: dev-swarm-mcp-server description: Add and manage Model Context Protocol (MCP) servers for AI agents, including transports, scopes, and config files. Use when extending agent capabilities with new tools or data sources.

AI Builder - MCP Server Management

This skill assists in adding MCP servers to CLI AI agents (Claude, Codex, Gemini, etc.) with the correct transport, scope, and configuration locations.

When to Use This Skill

  • User wants to add new MCP server to extend agent capabilities
  • User needs to list installed MCP servers
  • User wants to integrate new tools or data sources through MCP
  • User asks to configure MCP servers for different AI agents
  • User needs help choosing transport types or config scopes

Your Roles in This Skill

  • DevOps Engineer: Install and configure MCP servers for CLI AI agents, manage configuration files, and validate connectivity.
  • Technical Writer: Provide clear, accurate instructions and examples for MCP setup across tools and scopes.

Role Communication

As an expert in your assigned roles, you must announce your actions before performing them using the following format:

As a {Role} [and {Role}, ...], I will {action description}

This communication pattern ensures transparency and allows for human-in-the-loop oversight at key decision points.

Instructions

Follow these steps in order:

Step 1: Detect the AI Agent Type

  • Identify the current CLI agent (Claude Code, Codex CLI, Gemini CLI, or other).
  • If Claude Code, refer to references/mcp-server-claude.md.
  • If Codex CLI, refer to references/mcp-server-codex.md.
  • If Gemini CLI, refer to references/mcp-server-gemini.md.
  • If other, refer to references/mcp-server-other-cli.md.

Step 2: Confirm Requirements

  • Confirm transport type (stdio, HTTP, SSE), scope (project/user), and any required environment variables.
  • For general guidance, refer to references/mcp-server-general.md.

Step 3: Inspect Existing Configuration

  • Run the CLI list command to verify whether the server already exists.
  • If a server already exists, confirm whether to update, remove, or leave it.

Step 4: Configure the MCP Server

  • Use the correct CLI command and flags for the chosen transport and scope.
  • If configuration is file-based, update the correct file location.
  • If adding a server outside the project scope (user/global), use absolute paths for scripts and config files to avoid launch failures.
  • Keep sensitive values in environment variables, not committed files.

Step 5: Validate and Restart

  • Re-run the list command to confirm the server appears.
  • Instruct the user to restart the CLI so changes take effect.
  • If the server has a long startup time, set or recommend timeout options.

Best Practices

  1. Check installation first: Always verify existing MCP servers before changing configurations.
  2. Use project scope for team tools: Commit shared configs only when they contain no secrets.
  3. Keep secrets out of VCS: Use environment variables for API keys and tokens.
  4. Restart after changes: Always exit and relaunch the CLI after config updates.
  5. Validate connectivity: Confirm servers appear in list output and respond to basic requests.