gwanggo-mcp
gwanggo-mcp
AIエージェントに画像・動画生成の力を。
Gwanggo API 用のMCPサーバー + CLI — Seedream、Sora、Veo、Kling、GPT Image など30以上のモデルを1つのキーで。
Claude Code · Claude Desktop · Cursor · Codex など、MCPに対応するあらゆるツールで動作します。
You: "우리 신제품 세럼 광고 이미지 만들어줘, 화장품 무드로"
Agent: [calls generate_image with seedream-5] → https://…/result.pngセットアップ(2分)
1. アカウントを接続(ブラウザでの承認が開きます — パスワードの貼り付けは不要):
npx gwanggo-mcp login
# or, after install:
gwanggo auth login新規アカウントには無料クレジットが付与されます:gwanggo.ai でサインアップしてください。
loginをスキップしてGWANGGO_API_KEYを設定することもできます(ダッシュボード → APIキー で作成)。
2. エージェントに追加:
Claude Code
claude mcp add gwanggo -- npx -y gwanggo-mcpClaude Desktop / Cursor(claude_desktop_config.json / .cursor/mcp.json)
{
"mcpServers": {
"gwanggo": {
"command": "npx",
"args": ["-y", "gwanggo-mcp"]
}
}
}Codex CLI(~/.codex/config.toml)
[mcp_servers.gwanggo]
command = "npx"
args = ["-y", "gwanggo-mcp"]login の代わりにキーを明示的に渡すには、"env": { "GWANGGO_API_KEY": "gwk_..." } を追加します。
Related MCP server: Corent MCP Server
ツール
ツール | 説明 |
| クレジットコストとモデル別オプションを含む35以上の画像・動画モデル |
| テキスト→画像 / 画像編集。完了を待ってURLを返します |
| テキスト→動画 / 画像→動画(Seedance 2.0、Kling 3.0、Veo 3.1、Sora 2 …) |
| 以前の生成をIDで確認 |
| 残りのクレジット残高 |
失敗した生成はサーバー側で自動返金されます。
CLIの使い方
同じバイナリがCLIとしても機能します:
gwanggo auth login
gwanggo models
gwanggo generate image "neon alley cat, cinematic" --model gpt-image-2 --quality high
gwanggo generate video "waves crashing at dawn" --model seedance-2.0 --resolution 720p --duration 5 --generate-audio
gwanggo me # account and credits
gwanggo task <id> # check statusgwanggo コマンドは gwanggo auth login で保存されたアカウントを再利用します。APIキーの環境変数は不要です。GWANGGO_API_KEY はCIやその他の非対話環境でも引き続き使用できます。
仕組み
公開されている Gwanggo /v1 REST API のシンクライアントです — オープンソースの Gwanggo Studio を支えるのと同じAPIです。キーは ~/.config/gwanggo/config.json(0600)に保存され、Bearerトークンとしてのみ送信されます。ブラウザログインのキーは GWANGGO_API_KEY より優先されるため、古い環境キーが新しく承認されたログインを上書きすることはありません。ログインファイルが存在しないCIでは、GWANGGO_API_KEY が使用されます。
ライセンス
Available Tools
5 toolsgenerate_imageA
Generate an image with a Gwanggo model. Spends credits. Waits for completion and returns the image URL. Use list_models first to choose a model slug and see its options.
| Name | Required | Description | Default |
|---|---|---|---|
| model | Yes | Model slug, e.g. "seedream-5", "gpt-image-2" | |
| prompt | Yes | What to generate | |
| quality | No | Model-dependent quality tier, e.g. "basic" | "high" | |
| image_url | No | Reference image URL for edit/i2i models | |
| aspect_ratio | No | e.g. "1:1", "16:9", "9:16" (model-dependent) |
generate_videoA
Generate a video with a Gwanggo model. Spends credits (often per-second — check list_models). Waits up to 10 minutes and returns the video URL.
| Name | Required | Description | Default |
|---|---|---|---|
| model | Yes | Model slug, e.g. "seedance-2.0", "kling-3", "veo-3.1" | |
| prompt | Yes | Scene/motion description | |
| duration | No | Seconds (model-dependent, e.g. 5 or 10) | |
| image_url | No | Reference image URL for image-to-video | |
| resolution | No | e.g. "480p", "720p", "1080p" (model-dependent) | |
| aspect_ratio | No | e.g. "16:9", "9:16" (model-dependent) | |
| generate_audio | No | Generate audio track (model-dependent) |
get_creditsA
Get the connected Gwanggo account email and remaining credit balance.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
get_taskA
Check the status/result of a previous generation by its id.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Generation id returned by generate_image/generate_video |
list_modelsA
List available AI image/video generation models with credit costs and per-model options (aspect ratios, resolutions, durations). Call this first to pick a model slug.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Filter by model type |
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
5 tool updates
v0.1.0- First observed
generate_image - First observed
generate_video - First observed
get_credits - First observed
get_task - First observed
list_models
TDQS
Scored across 5 tools
Each tool serves a distinct function: generating images, generating videos, checking credits, checking task status, and listing models. No overlaps or ambiguity.
All tool names follow a consistent verb_noun pattern (generate_image, generate_video, get_credits, get_task, list_models), making predictions easy.
With 5 tools, the set covers the core workflow for an AI media generation service without being too sparse or excessive.
The surface covers model discovery, generation for both image and video, credit tracking, and task status. Missing a cancel/delete tool is a minor gap but not critical.
Maintenance
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