storytelling-media-mcp
Provides tools for agent-driven video creation, including image generation via Google's GenAI, video generation, and local video stitching with FFmpeg.
README
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-imagealso described by Google as Nano Banana 2.pro:gemini-3-pro-imagealso described by Google as Nano Banana Pro.legacy_flash:gemini-2.5-flash-imagefor older Nano Banana workflows.
Video generation defaults to:
veo-3.1-generate-001
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.
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