Gemini Media MCP

Plan, generate, compose, and edit images and video on Google Gemini and Veo 3.1, with a cost estimate before every call.

What it does

• Plan: plan_generation ranks tool and model options for an intent with costs, and generates nothing.
• Generate: images with Gemini, video with Veo 3.1, fast video with Omni.
• Compose: storyboards, multi-beat reels, transitions between stills, bridges between clips.
• Edit and extend: conversational video edits, loop and extend.
• Cost-aware: any call runs dry_run for a quote; real runs report metered cost and its pricing source.

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 + video, easier to set up) or Vertex AI (images + video, adds GCS output and Vertex-only features).
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 with a live check (constructs a Google GenAI client and lists models to confirm the key/credentials actually authenticate). Validation failures are non-fatal — you can continue anyway.
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 images and video with the simplest setup: a Gemini API key (setup instructions). Veo 3.1 video works on the paid Gemini API tier, and Veo 3.1 Lite is served exclusively through the Gemini API.
• For images and video with GCS output and Vertex-only features (e.g. controllable audio: include_audio is only honoured on Vertex, where it maps to Veo's generate_audio config; on the Gemini API Veo 3.1 always produces audio): a Google Cloud project with the Vertex AI API enabled and a service account with Vertex AI permissions (setup instructions)

Environment Variables

For Vertex AI (images + video, GCS output, Vertex-only features):

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 the Gemini API (images + video, including Veo 3.1 on the paid tier):

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

Other variables the server reads:

Variable	Description
DATA_FOLDER	Where generated media is written (default data). Required when running in a container
VIDEO_GCS_BUCKET	Default bucket for large video output; also seeds the GCS_ALLOWED_BUCKETS allowlist
GOOGLE_SERVICE_ACCOUNT_JSON	Service account key as inline JSON instead of a file path (Vertex mode only). Written by setup; the server materialises it into a temp file. GOOGLE_APPLICATION_CREDENTIALS also accepts inline JSON
RUNNING_IN_CONTAINER	Set to true by the Docker image. Makes DATA_FOLDER mandatory and switches the sse/streamable-http bind address to 0.0.0.0 (127.0.0.1 otherwise). Presence of /.dockerenv has the same effect
FASTMCP_HOST	Bind address for the sse/streamable-http transports; --host wins over it

CLI flags

gemini-media-mcp [--log-level LEVEL] [--host HOST] [--port PORT] [--mount-path PATH] [stdio|sse|streamable-http]

• --log-level: DEBUG, INFO (default), WARNING, ERROR, CRITICAL
• --host / --port: bind address and port for sse / streamable-http (default port 8000)
• --mount-path: mount path for the sse transport (e.g. /custom). streamable-http ignores it and always serves /mcp.

--host, --port and --mount-path are also accepted after the transport subcommand, which is the only form a docker run entrypoint can produce. --log-level must come before it.

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

Every generation tool supports dry_run: true — it returns the cost estimate for the exact call that would run (rerouted model, snapped duration, bridges counted) and generates nothing. Real runs report the metered cost in the response and the sidecar manifest. generate_clip is the one to always price first: 3 beats at 8s is $2.40 on the fast tier and $9.60 on standard.

plan_generation

Start here when you are not sure which tool or model to use. Describe what you want in plain language and get back ranked, ready-to-call plans — which tool, which model, which parameters, why that model won, what each option costs, and which models were ruled out and for what reason.

It generates nothing, costs nothing, and is instant: pure rule-based routing over this server's capability tables, not a model call. It never replaces the explicit generate_* tools — it tells you how to drive them.

Parameters:

• intent (required): plain language, e.g. a 3-beat vertical reel about coffee, a poster with the words GRAND OPENING
• Optional overrides (these always beat what's inferred from the text): budget (cheap/balanced/best), media_kind, aspect_ratio, image_size, duration_seconds, num_beats, needs_text_rendering, needs_4k, needs_audio, needs_extension, num_reference_images, wants_gcs_output, is_draft, pinned_model

Returns: ranked routes (tool, model, ready-to-use params, score, rationale, caveats, cost), rejected models with reasons, conflicts, a suggested multi-step workflow, and notes.

It catches requests that cannot work before you pay for the failure — 4K on a 1K-only model, extension or first/last-frame on Veo Lite, GCS output on the Gemini API — and reports each as a conflict with a fix.

Capability beats budget by design. Ask for legible text on a cheap budget and it still recommends gemini-3-pro-image: a cheap image that fails the brief isn't cheap.

generate_storyboard

The missing step between an idea and generate_clip. Renders one keyframe per shot, then composes them into a real, readable storyboard — numbered panels with slug lines, prompts, camera notes and duration badges — instead of a bare list of image URLs.

Two artifacts come back, because MCP clients render inline images but do not execute HTML:

1. A composited contact-sheet PNG — written full-resolution to disk (sheet_url) and returned inline as a downscaled preview. The preview is the thing you look at in chat; open sheet_url when a panel needs a closer read. It is downscaled because the full board runs past a megabyte from about a dozen shots up, and an MCP client drops a result that large outright.
2. A self-contained HTML page written to disk (file:// URL) with full-size frames, complete prompt text and cumulative timecode. Fully offline: images embedded as data URIs, no external requests.

Parameters:

• shots (required): ordered specs — {prompt, caption?, duration_seconds?, notes?}. caption is a slug line, notes are camera/lighting notes. Capped at 24 shots per call, because every shot is a billed image
• title, subtitle: drawn on the board
• model, aspect_ratio, image_size: keyframe generation settings (9:16 gives vertical panels)
• theme: dark (default) or light
• dry_run: price the whole board without generating

A failed shot does not abort the board — it renders as a clearly marked panel showing the actual error, so a partial storyboard stays reviewable, and it isn't billed. The shots list is designed to be fed straight into generate_clip as beats once the board reads well.

generate_image

Generate images using Gemini image models.

Parameters:

• prompt (required): Text description of the image

• model (required — there is no default; name one explicitly): Pick by use case. GA (stable) — preferred in production:

  • gemini-3.1-flash-image (Nano Banana 2) — the general-purpose choice; fast, up to 4K output, up to 14 reference images
  • gemini-3-pro-image (Nano Banana Pro) — 4K, reasoning, thought_signature for multi-turn editing
  • gemini-3.1-flash-lite-image — cheapest, but 1K output only (2K/4K are unsupported)

  Retired IDs are rerouted, not failed. The models below no longer exist (or are about to). Requesting one still returns an image: the server substitutes the replacement Google published rather than letting the call 404. They are accepted only as compatibility aliases — request a GA model directly.

  Retired ID	Gone since	Served by
  gemini-3-pro-image-preview	2026-06-25	gemini-3-pro-image
  gemini-3.1-flash-image-preview	2026-06-25	gemini-3.1-flash-image
  imagen-3.0-generate-002	2025-11-10	gemini-3.1-flash-image
  imagen-3.0-capability-001, imagen-3.0-capability-002, imagen-3.0-fast-generate-001, imagen-3.0-generate-001, imagen-4.0-fast-generate-001, imagen-4.0-generate-001	2026-08-17	gemini-3.1-flash-image
  imagen-4.0-ultra-generate-001	2026-08-17	gemini-3-pro-image
  gemini-2.5-flash-image	2026-10-02 (scheduled)	gemini-3.1-flash-image

  Imagen Ultra is the top Imagen tier, so it reroutes to the top Gemini image model rather than dropping to flash — gemini-3-pro-image is billed at a materially higher rate than gemini-3.1-flash-image. Price the call with dry_run before running it.

  Every substitution is announced on three channels so it cannot go unnoticed: a warnings entry in the response JSON, an MCP warning-level log notification to the client, and a WARNING record in the server log.

  If you hold Provisioned Throughput on a discontinued Imagen model, move that order yourself — Google does not stop it automatically at retirement.

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

• image_base64: Base64 encoded input image

• aspect_ratio: Output aspect ratio (e.g. 1:1, 16:9, 9:16)

• person_generation: Policy for generating people — dont_allow, allow_adult, or allow_all (some regions restrict these values)

• dry_run: Return only the cost estimate and the resolved model/parameters — generates nothing, free and instant

Every real run reports usage (the token counts the API metered) and cost derived from them, and writes both into the sidecar manifest. A dry run prices the call that would actually be issued: ask for imagen-4.0-generate-001 at 4K and it quotes gemini-3.1-flash-image; ask gemini-3.1-flash-lite-image for 4K and it quotes its 1K default and tells you why.

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

• 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. gemini-3.1-flash-lite-image supports 1K only; asking it for 2K/4K drops the parameter and returns a warning rather than failing the request.
• media_resolution: Input image processing quality (MEDIA_RESOLUTION_LOW, MEDIA_RESOLUTION_MEDIUM, MEDIA_RESOLUTION_HIGH)
• thought_signature_url: For multi-turn editing workflows — pass back the thought_signature_url from a previous response to continue editing the same image. (The parameter is the file URL; passing a thought_signature key is silently ignored by MCP.)

generate_video

Generate videos using VEO models. Video works on both credential modes: Veo 3.1 runs on the paid Gemini API tier as well as on Vertex AI. Vertex AI additionally provides GCS output and some Vertex-only features (e.g. include_audio, which is only honoured on Vertex). Veo 3.1 Lite is served exclusively through the Gemini API.

Parameters:

• prompt (required): Text description of the video
• model (required — there is no default; name one explicitly):
  • veo-3.1-generate-001: 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; text-to-video and image-to-video only (no extension, reference images, first/last-frame, or 4K). Served via the Gemini API only; Vertex AI projects may return 404 for this model.
• aspect_ratio: 16:9 (default) or 9:16
• resolution: Output resolution, 720p, 1080p, or 4K (4K not supported on Veo 3.1 Lite)
• duration_seconds: Video duration (4/6/8s), default 8.0 — the longest and most expensive option. Omitting it on veo-3.1-generate-001 bills a full 8s render (from $3.20 at 720p/1080p); pass 4 explicitly when a short beat will do.
• include_audio (default false): Enable audio generation (Vertex only; on the Gemini API Veo 3.1 always produces audio)
• person_generation: Policy for generating people — allow_adult or allow_all (some regions restrict these values)
• 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
• draft (default false): When true, routes the request to gemini-omni-flash-preview for a fast 720p draft instead of Veo. Iterate fast, then re-run with draft=false to finalize on Veo (note: omni is $0.10136/s — marginally above Veo Fast's $0.10/s, so draft buys speed, not savings). See Fast drafts vs. high-fidelity.

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

generate_video_omni

Fast conversational video generation via Google's gemini-omni-flash-preview (Interactions API). This is the fast path — ideal for drafts and rapid iteration. It is not the cheap path: $0.10136/s, a hair above Veo Fast's $0.10/s. The high-fidelity Veo tools remain the path for final renders (1080p/4K, seeds, first/last frame). See Fast drafts vs. high-fidelity.

Parameters:

• prompt (required): Text description of the video
• image_uris: List of image URIs to condition on (optional; at most 8 — more is rejected, since each is buffered in memory)
• input_video_uri: A video to edit (optional)
• aspect_ratio: 16:9 (default) or 9:16 — not sent when the request is an edit (an input_video_uri or a previous_interaction_id makes it one); the API rejects it on an edit task
• duration_seconds: Video duration, 3–10 (default 6) — likewise not sent on an edit, and the rendered length is then chosen by the service: a measured 3s source edited with duration_seconds=4 came back at 10.01s. On an edit the response reports duration_seconds: null and the quote uses omni's 10s maximum as an upper bound
• previous_interaction_id: Continue editing a prior omni result (optional)
• timeout_seconds: Overall deadline for create + polling (default 600). A render typically takes over a minute; raise it for long queues

Notes:

• 720p only, 24fps
• No seed or negative_prompt support
• The response includes an interaction_id for multi-turn editing (pass it to edit_video or back into previous_interaction_id)

edit_video

Conversational edit of a previously omni-generated video. Because omni holds the video context server-side (background interactions are retained ~14 days on Vertex AI; longer on the paid Gemini API), you describe only the change — no need to re-supply the source video.

Parameters:

• previous_interaction_id (required): The interaction_id from a prior generate_video_omni response
• prompt (required): The edit instruction (e.g. "make the sky stormy")
• aspect_ratio: accepted but never sent — the API rejects it on an edit task, so it does not change the output
• duration_seconds: accepted but never sent, and it does not set the output length. The service picks the rendered length, and it is predictable from neither this value nor the source video: a measured 3s source edited with duration_seconds=4 rendered 10.01s. The response reports duration_seconds: null; a real run bills the length measured from the rendered file, and dry_run quotes omni's 10s maximum so a pre-flight never under-states
• timeout_seconds: Overall deadline for the edit render (default 600)

loop_extend

Convenience wrapper that extends a Veo-generated video multiple times in one call. Each Veo extension adds ~7s, and can be chained up to 20 times.

Parameters:

• video_uri (required): The Veo-generated video to extend
• prompt: What the video continues with (default: "continue the action")
• times: Number of ~7s extensions to apply, 1-20 (default: 1)
• model: Veo model to use (default veo-3.1-generate-001; Lite is not supported)
• aspect_ratio: 16:9 (default) or 9:16 — must match the source video
• include_audio: Generate audio on the extended sections (default true; Vertex only)
• output_gcs_uri: GCS URI for output (optional; required on Vertex)

Notes:

• Veo 3.1 / Veo 3.1 Fast only (not Lite)
• 720p

generate_clip

Generate a multi-beat short clip — the building block for a reel or short. Each beat is rendered in order, and the tool returns an ordered manifest a cutting MCP (e.g. vfx-mcp) can splice into a finished clip.

This is the highest-leverage tool in the server: one call produces a whole sequence instead of N round-trips.

Parameters:

• beats (required): Ordered list of beat specs. Each accepts {prompt, duration_seconds?, seed?, first_frame_uri?, negative_prompt?, audio_prompt?}
• aspect_ratio: Default 9:16 for vertical social clips
• model: VEO model applied to every beat (default veo-3.1-fast-generate-001)
• include_audio (default true): Audio per beat (Vertex only)
• beats are capped at 20 per call — each is a billed Veo render, and add_bridges nearly doubles that. Split longer sequences into several clips
• add_bridges: Generate a transition between consecutive beats using the last frame of beat N and the first frame of beat N+1. Requires local (file://) beat outputs
• animatic: Render every beat with gemini-omni-flash-preview (fast 720p) for a storyboard preview of the whole reel before committing to full Veo renders. Bridges and Veo-only controls (seed, negative_prompt) are ignored in this mode
• output_gcs_uri: GCS URI for all outputs

Partial failure is non-fatal. A failed beat is recorded in the manifest's errors list and the run continues; bridges that would have used the failed beat are skipped.

Returns: a clip manifest — {kind, aspect_ratio, segments[], total_duration_seconds, errors[]}.

Suggested flow: run once with animatic: true to preview the whole sequence fast, then re-run with animatic: false once the beats read well.

generate_transition

Generate a transition video between two still frames using Veo 3.1's first+last-frame mode. Pair with a cutting MCP that extracts the last frame of clip A and the first frame of clip B.

Parameters:

• first_frame_uri (required): Starting still (gs://, https://, file://)
• last_frame_uri (required): Ending still
• prompt: Transition motion and style (default: smooth cinematic transition between the two frames)
• model: Veo model — default veo-3.1-fast-generate-001. Lite does not support first/last-frame mode and cannot be used
• duration_seconds: 4/6/8s, snapped to nearest
• aspect_ratio, include_audio, audio_prompt, negative_prompt, seed, output_gcs_uri

generate_bridge

Same primitive as generate_transition, but takes two clips instead of two stills: it decodes the last frame of from_clip_uri and the first frame of to_clip_uri for you, so no frame extraction step is needed.

Parameters:

• from_clip_uri (required): Clip whose last frame starts the bridge
• to_clip_uri (required): Clip whose first frame ends the bridge
• prompt: Transition motion and style (default: smooth cinematic cut between the two clips)
• model, duration_seconds, aspect_ratio, include_audio, audio_prompt, negative_prompt, seed, output_gcs_uri — as above

Returns: JSON with video_url, sidecar_url, and the source clip URIs.

Fast drafts vs. high-fidelity

There are two video paths, and you choose based on where you are in the workflow:

• gemini-omni-flash-preview (fastest turnaround) — 720p, 24fps, conversational multi-turn editing. Great for drafts, storyboards, and iteration. No seeds, no negative prompts, no first/last-frame control. Reached via generate_video_omni, edit_video, generate_video(draft=true), and generate_clip(animatic=true).
• Veo 3.1 / Fast / Lite (high-fidelity) — up to 1080p/4K, seeds for reproducibility, first/last-frame control, reference images, and extension. The path for final renders. Reached via generate_video (default) and loop_extend.

Typical workflows:

• draft → finalize: run generate_video(draft=true) to preview quickly on omni, then re-run the same prompt with draft=false to render the final on Veo.
• animatic → final: run generate_clip(animatic=true) to render each beat via gemini-omni-flash-preview as a fast storyboard preview of the whole reel, then re-run with animatic=false (the default) to commit to full Veo renders.

Note: generate_clip's new animatic parameter (default false) renders each beat through gemini-omni-flash-preview instead of Veo, so you can preview an entire reel quickly before committing to full Veo renders (price parity with the fast tier; the saving is real only against the standard tier).

Google Vertex AI and Gemini Access

Vertex AI Setup

Vertex AI gives you images and video plus GCS output and Vertex-only features. If you only need images and video without those extras, the Gemini API is simpler to set up.

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

The simplest way to generate both images and video:

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 supports Veo 3.1 video generation on the paid tier, and Veo 3.1 Lite is available only through the Gemini API. Vertex AI adds GCS output and some Vertex-only features (e.g. controllable audio — include_audio only takes effect on Vertex), but is not required for video.

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