Gemini Media

gemini-media-mcp

An MCP server for Google's generative media models: images (Nano Banana 2.1 / Pro), video (Veo 3.1 and Gemini Omni Flash), speech (Gemini 3.8 TTS) and music (Lyria 3.5). It ships as a single Go binary, speaks stdio and Streamable HTTP (MCP 2026-07-28), works with the Gemini API or Vertex AI, and comes with agent skills that teach agents the whole workflow, plus plugin packaging for Claude Code, Codex, Gemini CLI, VS Code/Copilot, Cursor and more.

https://github.com/user-attachments/assets/f46970b3-82a6-4364-a40a-922103dbbc70

*An agent using the server one tool at a time: images and edits, a video clip and its claymation restyle, a 768 px portrait tiled up to 8K, and an extended shot. The footage, the narration and the music all came from the server.*

• Current models, updated without a release. A built-in catalog records IDs, aliases, lifecycle, parameters and prices. Retired models redirect to their replacement, and new model IDs work before the catalog knows them. You can override or extend the catalog with a hot-reloaded YAML file.
• Cost-aware. Every result reports its estimated cost, and estimate_cost compares options before you spend. Spend is recorded in a ledger, capped by session, daily and monthly budgets, and calls above a threshold need explicit approval.
• Agent-friendly. Each tool matches a workflow, and errors come back as [kind] message + Hint. Image results include inline previews, and outputs can be chained by URI. Video runs as async jobs with long-polling and progress notifications.
• Skills included. Six agent skills cover each medium, multi-asset productions and upscaling past 4K. The upscale skill re-renders a photo tile by tile and stitches the tiles into an 8K image.
• Robust. Backend and credentials are detected the way the Google SDKs do it. Vertex locations are chosen per model, retries and timeouts are built in, files are written atomically with provenance, and HTTP mode ships with security defaults.

Upgrading from v0? The tools changed. See the migration table. The review also covers what was broken, why, and the design of v1.

Quick start

1. Get credentials. Either:

• an API key from Google AI Studio (GEMINI_API_KEY), or
• a Google Cloud project with Vertex AI enabled (GOOGLE_CLOUD_PROJECT plus gcloud auth application-default login).

1. Install the binary. On macOS or Linux:

   mkdir -p ~/.local/bin   # must be on your PATH

os=$(uname -s | tr '[:upper:]' '[:lower:]'); arch=$(uname -m | sed 's/x86_64/x64/; s/aarch64/arm64/') curl -fsSL "https://github.com/mordor-forge/gemini-media-mcp/releases/latest/download/$os.$arch.gemini-media-mcp.tar.gz" \ | tar -xz -C ~/.local/bin gemini-media-mcp gemini-media-mcp version

   On Windows, download the `windows` zip from the [latest release](https://github.com/mordor-forge/gemini-media-mcp/releases/latest) and put `gemini-media-mcp.exe` on your PATH. With Go 1.26+: `go install github.com/mordor-forge/gemini-media-mcp/cmd/gemini-media-mcp@latest`.

The Gemini CLI extension, the Claude Desktop bundle and the Docker image include the binary, so they skip this step.

1. Add the server to your agent. Every config below runs gemini-media-mcp from your PATH.

Claude Code (plugin: server plus skills), from the shared mordor-forge marketplace:

   /plugin marketplace add mordor-forge/claude-plugins

/plugin install gemini-media@mordor-forge

   If you added `mordor-forge` from this repository before, switch with `/plugin marketplace remove mordor-forge` first. Your installed plugin keeps working either way.

or just the server: claude mcp add gemini-media -e GEMINI_API_KEY=... -- gemini-media-mcp

Codex (~/.codex/config.toml):

   [mcp_servers.gemini-media]

command = "gemini-media-mcp" env_vars = ["GEMINI_API_KEY", "GOOGLE_API_KEY", "GOOGLE_CLOUD_PROJECT", "GOOGLE_CLOUD_LOCATION"] tool_timeout_sec = 300 # 4K images and video polls can exceed the 60 s default

Gemini CLI (paid API keys, Vertex AI and Gemini Code Assist only, since June 2026): gemini extensions install https://github.com/mordor-forge/gemini-media-mcp

Antigravity CLI: add the server to ~/.gemini/config/mcp_config.json, as shown in the install snippets.

Claude Desktop: download gemini-media-mcp- .mcpb from the latest release and open it.

VS Code / Copilot: code --add-mcp '{"name":"gemini-media","command":"gemini-media-mcp"}'

Cursor, Windsurf and other `mcpServers`-style clients (Zed, OpenCode and Goose use their own formats, see below):

   { "mcpServers": { "gemini-media": { "command": "gemini-media-mcp", "env": { "GEMINI_API_KEY": "..." } } } }

If a desktop app reports that gemini-media-mcp was not found, it doesn't see your shell's PATH: use the full path from command -v gemini-media-mcp. Every client, plus Docker and the skills installer, is covered in packaging/INSTALL-SNIPPETS.md.

1. If your agent doesn't forward environment variables (plugins often don't), store the key once:

   echo "$GEMINI_API_KEY" | gemini-media-mcp configure --api-key-stdin

gemini-media-mcp doctor # checks credentials, backend and model availability

To run it in Docker instead: docker run -i --rm --user "$(id -u):$(id -g)" -e GEMINI_API_KEY -v "$PWD/media:/output" -v gemini-media-state:/state ghcr.io/mordor-forge/gemini-media-mcp (--user makes the generated files yours on Linux; the named /state volume keeps spend accounting and video jobs between runs).

Tools

Every result includes the saved file's path, a gemini-media://files/ URI and its cost. You can pass the URI as an input to another tool. Clients that can't read the server's disk (for example over HTTP) can fetch the file with resources/read, for files up to 64 MB (larger upscales stay on the server's disk).

Skills

The skills/ directory contains Agent Skills that teach agents the full workflow for each media type: intent, prompt craft, model choice, cost checks, review and iteration. They cover interactive use as well as unattended runs.

Plugin installs (Claude Code, Codex, Gemini CLI, VS Code) include the skills. To install them in any Agent Skills–compatible agent, run npx skills add mordor-forge/gemini-media-mcp, or copy the folders into .agents/skills/ or ~/.claude/skills/.

Models

Use an alias or a full model ID. Run gemini-media-mcp models for the built-in catalog with prices, or call list_models, which also applies your override file and, with live: true, checks what your key can use.

Veo on the Gemini API. Google is shutting down the Veo 3.1 previews (and the gemini-omni-flash-preview model) on the Gemini API on 2026-10-22. Until then lite, fast and standard still work there with a deprecation warning; after it the server uses omni instead and says so. Veo 3.1 stays available on Vertex AI, now called Gemini Enterprise Agent Platform (veo-3.1-*-generate-001): to keep using it, run the server against a Google Cloud project: GOOGLE_CLOUD_PROJECT plus gcloud auth application-default login, and GEMINI_MEDIA_BACKEND=vertex if an API key is also set (see Configuration).

Updating or adding a model without waiting for a release. Create a YAML file and point GEMINI_MEDIA_CATALOG at it. The server merges it with the built-in catalog by id and reloads it automatically:

defaults:

video: fast models:

• id: veo-3.1-fast-generate-preview pricing: { perSecond: { 720p: 0.10, 1080p: 0.12, 4k: 0.30 } }
• id: veo-4.0-generate-preview # a brand-new model aliases: [veo4] pricing: { perSecond: { 720p: 0.50 } }

See internal/catalog/models.yaml for the full schema.

Configuration

Settings are layered: built-in defaults < config file <