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mordor-forge/gemini-media-mcp

by Various

Unified Go MCP server for AI media generation via Google Gemini API and Vertex AI

M

MCP

mordor-forge/gemini-media-mcp

Added 1 June 2026

Overview

A Go-based MCP server that provides a unified interface for generating images, audio, and video using Google Gemini API and Vertex AI. It acts as a bridge between AI agents and Gemini's media generation capabilities through the Model Context Protocol.

Best for

Best for
Developers building AI agent workflows that need to generate images, audio, or video through Google's Gemini models.

Use cases

  • Generate images and audio with an AI agent via Gemini
  • Integrate Vertex AI media generation into MCP-compatible tools
  • Build custom AI workflows that create multimedia content programmatically

How to use

Install

go install github.com/mordor-forge/gemini-media-mcp/cmd/gemini-media-mcp@latest

Tools exposed

  • generate_image
  • edit_image
  • compose_images
  • generate_video
  • animate_image
  • extend_video
  • video_status
  • download_video
  • generate_audio
  • generate_music
  • list_models
  • get_config

Tested with

Claude Code

Example client config

{\n  "mcpServers": {\n    "gemini-media": {\n      "command": "gemini-media-mcp",\n      "env": {\n        "GOOGLE_API_KEY": "your-api-key",\n        "MEDIA_OUTPUT_DIR": "/path/to/output"\n      }\n    }\n  }\n}

Notes

A Go-based MCP server that provides a unified interface for generating images, audio, and video using Google Gemini API and Vertex AI. It acts as a bridge between AI agents and Gemini’s media generation capabilities through the Model Context Protocol.

5 stars on GitHub. Last updated 2026-04-15. Licensed Apache-2.0.

Use cases

  • Generate images and audio with an AI agent via Gemini
  • Integrate Vertex AI media generation into MCP-compatible tools
  • Build custom AI workflows that create multimedia content programmatically

Pros

  • Written in Go for efficient performance
  • Supports both Gemini API and Vertex AI for flexibility
  • Unified single server for multiple media types

Cons

  • Limited to Google Gemini ecosystem, no support for other model providers
  • Small community with only 5 GitHub stars may mean limited support
  • Requires separate Google Cloud credentials for Vertex AI access

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Written in Go for efficient performance
  • Supports both Gemini API and Vertex AI for flexibility
  • Unified single server for multiple media types

Cons

  • Limited to Google Gemini ecosystem, no support for other model providers
  • Small community with only 5 GitHub stars may mean limited support
  • Requires separate Google Cloud credentials for Vertex AI access
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