Storytelling Media MCP

MCP tools for an agent-driven video creation workflow.

This server gives Codex, Claude Code, or another MCP client access to:

• Nano Banana image generation and editing through Google's GenAI SDK.

• Veo 3.1 video generation through Google's GenAI SDK.

• Local video stitching through FFmpeg.

Models

Image generation defaults to the newer Google image models:

• flash: gemini-3.1-flash-image also described by Google as Nano Banana 2.

• pro: gemini-3-pro-image also described by Google as Nano Banana Pro.

• legacy_flash: gemini-2.5-flash-image for older Nano Banana workflows.

Video generation defaults to:

• veo-3.1-generate-001

Related MCP server: Sora 2 MCP Server

Setup

python -m venv .venv
. .venv/bin/activate
pip install -e .
cp .env.template .env

FFmpeg must be installed and available on PATH for stitching.

ADC Instead of API Key

The Gemini API can also use OAuth/ADC, but the ADC login must include Google's Gemini scope:

gcloud auth application-default login \
  --scopes='https://www.googleapis.com/auth/cloud-platform,https://www.googleapis.com/auth/generative-language.retriever'
gcloud auth application-default set-quota-project "$GOOGLE_CLOUD_PROJECT"

Then run the MCP server with GOOGLE_CLOUD_PROJECT set to the project that should be used for quota and billing:

python -m storytelling_mcp

The server also accepts GOOGLE_CLOUD_QUOTA_PROJECT or GCLOUD_PROJECT. Then call the image or video tools with auth_mode="adc". If your ADC token was created without the generative-language.retriever scope, the Gemini API returns ACCESS_TOKEN_SCOPE_INSUFFICIENT.

Run

python -m storytelling_mcp

MCP Client Config

Example stdio server config using an API key:

{
  "mcpServers": {
    "storytelling-media": {
      "command": "python",
      "args": ["-m", "storytelling_mcp"],
      "env": {
        "GEMINI_API_KEY": "your_api_key"
      }
    }
  }
}

Example stdio server config using ADC/Vertex:

{
  "mcpServers": {
    "storytelling-media": {
      "command": "python",
      "args": ["-m", "storytelling_mcp"],
      "env": {
        "GOOGLE_CLOUD_PROJECT": "your-gcp-project-id",
        "GOOGLE_CLOUD_LOCATION": "us-central1"
      }
    }
  }
}

Agent Plugins

This repo includes installable plugin metadata for both Claude Code and Codex.

Claude Code:

/plugin marketplace add imyousuf/storytelling-media-mcp
/plugin install storytelling-media-mcp@storytelling-media

Codex:

codex plugin marketplace add imyousuf/storytelling-media-mcp --sparse .agents/plugins --sparse plugins

Then open /plugins in Codex and install storytelling-media-mcp from the storytelling-media marketplace.

The plugin launcher uses STORYTELLING_MEDIA_MCP_ROOT for local development. If that variable is unset, it creates a plugin-local virtual environment and installs this package from GitHub before starting the MCP server.

The plugin also includes $movie-production-pipeline, a gated multi-agent workflow for turning a director's brief into stage-approved production artifacts. It expects user feedback at each stage before moving forward.

Tools

• nano_banana_generate_image: text-to-image or text-and-image-to-image.

• veo_generate_video: text-to-video, image-to-video, interpolation, or reference-image-guided generation.

• stitch_videos: concatenate local MP4 clips with FFmpeg.

Generated files are written to paths supplied by the caller.