Development MCP Servers (dev-mcp-servers)

This repository provides high-quality Model Context Protocol (MCP) servers for third-party AI services:

• ElevenLabs MCP Server (elevenlabs): Text-to-speech, sound effect generation, listing available voices, and user character usage limits.

• Meshy.ai MCP Server (meshy): Text-to-3D preview & refine, Text-to-Image concept art, Image-to-3D, Rigging, Animation, Animation Library browsing (list_animation_library), and Model downloading.

• Gemini MCP Server (gemini): Image generation and editing (generate_image, via Gemini's image model), text generation (generate_text), and model listing (list_models).

• Codex Delegation MCP Server (codex): Delegating bounded tasks to local Codex CLI agents in isolated git worktrees with structured handoffs, originally developed for Thera (Craft-Realm) refactoring.

Features

Request Preview Mode (Dry-Run / Token Cost Prevention)

All tools support Request Preview Mode so you can inspect the precise HTTP target URL, method, headers, request payload, or CLI delegation commands without triggering remote API calls, spawning workers, or burning credits/tokens.

Request Preview mode can be activated in two ways:

1. Tool Argument: Pass "preview": true in the tool input arguments when invoking any tool.

2. Environment Variable: Set REQUEST_PREVIEW=1 (or PREVIEW_MODE=1 / DRY_RUN=1) in your environment.

When active, the tool response returns a structured JSON summary of the request instead of executing the remote call or spawning subprocesses.

Related MCP server: ElevenLabs MCP Server

Setup & Installation

git clone /home/gemini/repos/dev-mcp-servers
cd dev-mcp-servers
npm install

Running Tests

Run the full test suite using Node's native test runner:

npm test

Or test individual MCP servers:

npm run test:elevenlabs
npm run test:meshy
npm run test:gemini
npm run test:codex

Antigravity Integration

In ~/.gemini/config/mcp_config.json:

{
  "mcpServers": {
    "elevenlabs": {
      "command": "node",
      "args": ["/home/gemini/repos/dev-mcp-servers/elevenlabs/server.js"],
      "env": {
        "ELEVENLABS_API_KEY": "your_api_key_here"
      }
    },
    "meshy": {
      "command": "node",
      "args": ["/home/gemini/repos/dev-mcp-servers/meshy/server.js"],
      "env": {
        "MESHY_API_KEY": "your_api_key_here"
      }
    },
    "gemini": {
      "command": "node",
      "args": ["/home/gemini/repos/dev-mcp-servers/gemini/server.js"],
      "env": {
        "GEMINI_API_KEY": "your_api_key_here"
      }
    },
    "codex": {
      "command": "node",
      "args": ["/home/gemini/repos/dev-mcp-servers/codex/server.js"]
    }
  }
}

Codex CLI Integration

In ~/.codex/config.toml or <project-root>/.codex/config.toml:

[mcp_servers.codex]
command = "node"
args = ["/home/gemini/repos/dev-mcp-servers/codex/server.js"]

Prompting the AI to use generate_image

Antigravity/Gemini clients pass each tool's name, description, and inputSchema to the model when deciding which tool to call — there's no separate "hint" channel. The generate_image tool's description explicitly says it is "the primary image-generation tool of this server" and should be preferred for AI image generation/editing requests, which is normally enough for the model to pick it up automatically when a user asks for an image. If you want to force it, you can also just say "use the generate_image tool" in your prompt.