gemini-media-mcp 0.1.7

MCP server for Gemini media generation

Gemini Media MCP

MCP server for generating images and videos using Google Gemini and VEO models.

Quick start

uvx gemini-media-mcp setup

The setup wizard walks you through the whole onboarding flow end-to-end:

1. Pick a credential mode: Gemini API (images only, easier) or Vertex AI (images + video).
2. Enter your API key, or your Google Cloud project plus a service account JSON (file path or inline paste).
3. Choose where generated media should be written (defaults to ~/gemini-media).
4. Optionally set a VIDEO_GCS_BUCKET for large video output, and auto-populate GCS_ALLOWED_BUCKETS.
5. Validate your credentials by constructing a Google GenAI client.
6. Print a ready-to-paste Claude Desktop JSON block. On macOS, the wizard can also merge the block directly into ~/Library/Application Support/Claude/claude_desktop_config.json (existing servers are preserved and the prior file is backed up to .bak).

For scripted use, all prompts can be supplied via flags:

uvx gemini-media-mcp setup --non-interactive --mode=gemini --api-key=AIzaSy...

If you prefer to configure everything by hand, the manual steps are below.

Setup

Prerequisites

• For video generation (VEO): Google Cloud project with Vertex AI API enabled and a service account with Vertex AI permissions (setup instructions)
• For image generation only: Gemini API key (setup instructions)

Environment Variables

For Vertex AI (required for VEO video generation):

export GOOGLE_GENAI_USE_VERTEXAI=true
export GOOGLE_CLOUD_PROJECT=your-project-id
export GOOGLE_CLOUD_LOCATION=us-central1
export GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account.json

→ See Vertex AI Setup for detailed instructions

Alternatively, for Gemini API (image generation only):

export GEMINI_API_KEY=your-api-key

→ See Gemini API Setup for detailed instructions

Optional security hardening:

# Restrict gs:// fetches and output_gcs_uri to specific buckets.
# If unset and VIDEO_GCS_BUCKET is not set, gs:// fetches log a warning.
export GCS_ALLOWED_BUCKETS=bucket-a,bucket-b

Local file:// and bare-path inputs are always restricted to DATA_FOLDER. HTTP(S) fetches reject hosts that resolve to private, loopback, link-local, or metadata IPs, and downloads are capped at 50 MB.

Claude Desktop Configuration

Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "gemini-media": {
      "command": "uvx",
      "args": ["gemini-media-mcp"],
      "env": {
        "GOOGLE_GENAI_USE_VERTEXAI": "true",
        "GOOGLE_CLOUD_PROJECT": "your-project-id",
        "GOOGLE_CLOUD_LOCATION": "us-central1",
        "GOOGLE_APPLICATION_CREDENTIALS": "/path/to/service-account.json"
      }
    }
  }
}

Or using Docker (note: DATA_FOLDER must be set to the host path, with matching volume mount):

{
  "mcpServers": {
    "gemini-media": {
      "command": "docker",
      "args": [
        "run", "--rm", "-i",
        "-e", "GOOGLE_GENAI_USE_VERTEXAI=true",
        "-e", "GOOGLE_CLOUD_PROJECT=your-project-id",
        "-e", "GOOGLE_CLOUD_LOCATION=us-central1",
        "-e", "GOOGLE_APPLICATION_CREDENTIALS=/credentials.json",
        "-e", "DATA_FOLDER=/Users/yourusername/gemini-output",
        "-v", "/path/to/service-account.json:/credentials.json:ro",
        "-v", "/Users/yourusername/gemini-output:/Users/yourusername/gemini-output",
        "cxoagi/gemini-media-mcp"
      ]
    }
  }
}

This writes files to your host path and returns paths like /Users/yourusername/gemini-output/images/abc.png that Claude Desktop can open directly. The DATA_FOLDER directory will contain images/ and videos/ subdirectories.

Available Tools

generate_image

Generate images using Gemini or Imagen models.

Parameters:

• prompt (required): Text description of the image

• model: Pick by use case. GA (stable) — preferred in production:

  • gemini-2.5-flash-image (Nano Banana) — default; fastest, cheapest, great for conversational editing
  • imagen-4.0-fast-generate-001 — cheapest photoreal
  • imagen-4.0-generate-001 — balanced photoreal
  • imagen-4.0-ultra-generate-001 — highest-fidelity photoreal, precise text rendering
  • imagen-3.0-generate-002 — legacy, kept for compatibility

  Preview — newest capabilities, may change without notice:

  • gemini-3.1-flash-image-preview (Nano Banana 2) — 4K output, up to 14 reference images, fast
  • gemini-3-pro-image-preview (Nano Banana Pro) — 4K, reasoning, thought_signature for multi-turn editing

• image_uri: Input image URI for image-to-image generation

• image_base64: Base64 encoded input image

Gemini 3.x Image Parameters (for gemini-3-pro-image-preview and gemini-3.1-flash-image-preview):

• reference_image_uris: List of up to 14 reference image URIs for multi-image composition
  • Up to 6 object images for high-fidelity inclusion
  • Up to 5 human images for character consistency across scenes
• image_size: Output resolution (1K, 2K, 4K) - must use uppercase K
• thinking_level: Reasoning depth (low for fast, high for complex generation)
• media_resolution: Input image processing quality (MEDIA_RESOLUTION_LOW, MEDIA_RESOLUTION_MEDIUM, MEDIA_RESOLUTION_HIGH)
• thought_signature: For multi-turn editing workflows - pass back the signature from previous responses

generate_video

Generate videos using VEO models (requires Vertex AI).

Parameters:

• prompt (required): Text description of the video
• model: Model to use:
  • veo-3.1-generate-001 (default): Highest quality, 4/6/8s duration, audio support
  • veo-3.1-fast-generate-001: Faster generation with audio support
  • veo-3.1-lite-generate-preview: Most cost-effective, 4/6/8s, audio; no video extension or 4K. Currently served via the Gemini API; Vertex AI projects may return 404 until Google publishes the model on Vertex.
• aspect_ratio: 16:9 (default) or 9:16
• duration_seconds: Video duration (4/6/8s)
• include_audio: Enable audio generation
• audio_prompt: Audio description
• negative_prompt: Things to avoid in the video
• seed: Random seed for reproducibility
• image_uri: First frame image URI for image-to-video generation

Additional Parameters:

• last_frame_uri: Last frame image URI for first+last frame control
  • When combined with image_uri, generates smooth transitions between frames
• reference_image_uris: List of up to 3 reference image URIs for subject preservation
  • Preserves the appearance of a person, character, or product in the output video
  • Note: Only supports 8-second duration (automatically enforced)
  • Cannot be used together with first/last frame inputs
• extend_video_uri: URI of existing VEO-generated video to extend
  • Extends the final second of the video and continues the action
  • Can be chained multiple times for longer videos (up to ~148s total)
  • Note: Cannot be used together with other image inputs

Generation Modes (automatically selected based on inputs):

• text_to_video: Text-only prompt
• image_to_video: First frame image input
• first_last_frame: First and last frame control
• reference_to_video: Reference images for subject preservation (8s only)
• extend_video: Extend existing video

Google Vertex AI and Gemini Access

Vertex AI Setup (Required for VEO Video Generation)

Step 1: Create a Google Cloud Project

1. Go to the Google Cloud Console
2. Click the project dropdown at the top of the page
3. Click "New Project"
4. Enter a project name and click "Create"
5. Note your Project ID (you'll need this later)

Step 2: Enable Vertex AI API

1. In the Cloud Console, go to "APIs & Services" > "Library" (or visit API Library)
2. Search for "Vertex AI API"
3. Click on "Vertex AI API" in the results
4. Click the "Enable" button
5. Wait for the API to be enabled (this may take a minute)

Step 3: Create a Service Account

1. Go to "IAM & Admin" > "Service Accounts" (or visit Service Accounts)
2. Click "Create Service Account" at the top
3. Enter a name (e.g., "gemini-media-mcp") and description
4. Click "Create and Continue"
5. In the "Grant this service account access to project" section:
   • Click the "Select a role" dropdown
   • Search for "Vertex AI User"
   • Select "Vertex AI User" role
   • Click "Continue"
6. Click "Done" (you can skip the optional "Grant users access" section)

Step 4: Download Service Account Key

1. In the Service Accounts list, find the account you just created
2. Click the three dots (⋮) in the "Actions" column
3. Select "Manage keys"
4. Click "Add Key" > "Create new key"
5. Select "JSON" as the key type
6. Click "Create"
7. The JSON key file will automatically download to your computer
8. Important: Move this file to a secure location and note the path (e.g., ~/credentials/gemini-media-service-account.json)
9. Security Note: Never commit this file to version control or share it publicly

Step 5: Update Configuration

Use the following values in your configuration:

• GOOGLE_CLOUD_PROJECT: Your Project ID from Step 1
• GOOGLE_CLOUD_LOCATION: us-central1 (or your preferred region)
• GOOGLE_APPLICATION_CREDENTIALS: Full path to the JSON key file from Step 4

Gemini API Setup (Image Generation Only)

For simpler image generation without video capabilities:

1. Visit Google AI Studio
2. Sign in with your Google account
3. Click "Create API Key"
4. Copy your key (starts with AIzaSy...)
5. Set the environment variable: export GEMINI_API_KEY=your-api-key

Note: The Gemini API does not support VEO video generation. For video capabilities, you must use Vertex AI.

Contributing

Development Setup

uv sync

Running Tests

uv run pytest

Code Quality

# Type checking
uv run basedpyright src/ tests/

# Linting and formatting
uv run ruff check src/ tests/
uv run ruff format src/ tests/

# Pre-commit hooks
uv run prek

Building Docker Image

docker build -t gemini-media-mcp .

# With specific version
docker build --build-arg VERSION=1.0.0 -t gemini-media-mcp:1.0.0 .

License

MIT