Awesome-Gemini-Omni-API-Prompts — Claude MCP 必备工具中文教程 是 AI Skill Hub 本期精选MCP工具之一。综合评分 8.0 分,整体质量较高。我们推荐使用将其纳入你的 AI 工具库,帮助提升工作效率。
Awesome-Gemini-Omni-API-Prompts — Claude MCP 必备工具中文教程 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
Awesome-Gemini-Omni-API-Prompts — Claude MCP 必备工具中文教程 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/Anil-matcha/Awesome-Gemini-Omni-API-Prompts
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"awesome-gemini-omni-api-prompts---claude-mcp---------": {
"command": "npx",
"args": ["-y", "awesome-gemini-omni-api-prompts"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例: 用户: 请帮我用 Awesome-Gemini-Omni-API-Prompts — Claude MCP 必备工具中文教程 执行以下任务... Claude: [自动调用 Awesome-Gemini-Omni-API-Prompts — Claude MCP 必备工具中文教程 MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入:"列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"awesome-gemini-omni-api-prompts___claude_mcp_________": {
"command": "npx",
"args": ["-y", "awesome-gemini-omni-api-prompts"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
A curated collection of high-quality prompts and patterns for Google Gemini Omni — Google's natively multimodal any-to-any video generation model. This repository is your go-to reference for prompting Google Gemini Omni across text-to-video, image-to-video, audio-to-lip-sync, and video editing — covering cinematic shots, character-consistent stories, product ads, anime, scientific visualization, B-roll, and more.
Whether you're building a video generation app with the Gemini Omni API or chasing cleaner prompt patterns, you'll find ready-to-use prompts here that unlock Google Gemini Omni's full potential.
Join the discussion: https://www.reddit.com/r/GeminiOmniAI/
API access: All prompts work with MuAPI — a hosted media API that gives you Gemini Omni text-to-video, image-to-video, and video-edit with a simple REST call. Get your API key →
pip install gemini-omni-api
```python from gemini_omni_api import GeminiOmniAPI
api = GeminiOmniAPI(api_key="your-muapi-key")
pip install gemini-omni-api
Or clone this repo and install directly:
git clone https://github.com/Anil-matcha/Awesome-Gemini-Omni-API-Prompts.git
cd Awesome-Gemini-Omni-API-Prompts
pip install -r requirements.txt
cp .env.example .env # add your MUAPI_API_KEY
```python from gemini_omni_api import GeminiOmniAPI
api = GeminiOmniAPI(api_key="your-muapi-key") # or set MUAPI_API_KEY env var
Reference: character reference (full body). Prompt:
Using the attached character as the subject, generate a continuous walking sequence where the environment transitions seamlessly every 3 seconds: 0–3s desert dunes at sunset, 3–6s neon-soaked rainy city street, 6–9s misty alpine forest, 9–12s clean white infinity studio. Character stride, outfit, and proportions remain identical throughout. Camera tracks alongside in profile, locked focal length, 12 seconds, 16:9.
---
Prompt:
Keep the subject and all their motion identical but replace the background environment with a sunlit urban rooftop at golden hour. City skyline visible in the background, warm directional rim light matching the new environment falling on the subject, soft atmospheric haze. Seamless integration — no compositing artifacts.
---
Reference: single portrait of the protagonist. Prompt:
The attached image is the main character. Generate three connected shots, same person in all three, identical face, hair, and wardrobe throughout:
1) 0–4s: Wide shot, she walks out of a Parisian apartment building into morning light, holding a paper coffee cup, slow dolly-back
2) 4–8s: Medium shot, she stops at a flower stall, smiles at the vendor, picks up a bouquet, soft sidelight
3) 8–12s: Close-up, she sits on a bench by the Seine, looks off-camera contemplatively, gentle breeze in hair
Cinematic 35mm look throughout, consistent color grade, no cuts to other characters.
---
References: two character images. Prompt:
Image 1 and image 2 are the two combatants. Generate a 10-second cinematic sword duel under a stormy bamboo forest at night. Choreography: clash 1 sparks fly, parry, character 1 advances with three quick strikes, character 2 dodges and counters with a sweeping cut, locked-blade standoff with both faces close to camera, slow dolly-around. Rain falls throughout, lightning flashes punctuate the impacts. Maintain both characters' exact faces and costumes. 10 seconds, 21:9 cinemascope.
---
Reference: a stylized art piece. Prompt:
Re-render the previous clip in the visual style of the attached image — match its color palette, brush texture, and lighting language. Preserve the original motion, framing, and subject identity exactly.
---
MuAPI provides all three Gemini Omni generation modes — text-to-video, image-to-video, and video-edit — as a hosted REST service. No extra account required beyond an API key.
| Mode | Endpoint | Key inputs |
|---|---|---|
| Text-to-Video | POST /gemini-omni-text-to-video | prompt |
| Image-to-Video | POST /gemini-omni-image-to-video | prompt, image_urls (1–5) |
| Video Edit | POST /gemini-omni-video-edit | prompt, video_url and/or image_urls |
| Audio Profile | POST /gemini-omni-audio | audio_id, name |
| Character | POST /gemini-omni-character | images_list, descriptions |
All modes return {"request_id": "..."}. Poll GET /predictions/{request_id}/result until status == "completed".
All endpoints follow the same submit → poll pattern:
POST https://api.muapi.ai/api/v1/{endpoint} → {"request_id": "abc123", "status": "processing"}
GET https://api.muapi.ai/api/v1/predictions/{request_id}/result → poll until status == "completed"
import requests, time
API_KEY = "your-muapi-key"
BASE = "https://api.muapi.ai/api/v1"
resp = requests.post(
f"{BASE}/gemini-omni-text-to-video",
headers={"x-api-key": API_KEY},
json={
"prompt": "35mm anamorphic rain-soaked Tokyo alley at 2 AM, slow dolly-in",
"duration": 8, # 4 | 6 | 8 | 10
"aspect_ratio": "16:9", # "16:9" | "9:16"
"resolution": "1080p", # "720p" | "1080p" | "4k"
# "audio_ids": ["aoede"], # optional — list of up to 3 voices
# "character_ids": [...], # optional character IDs
# "seed": 42, # optional seed
},
)
request_id = resp.json()["request_id"]
while True:
r = requests.get(f"{BASE}/predictions/{request_id}/result", headers={"x-api-key": API_KEY}).json()
if r["status"] == "completed":
print(r["outputs"])
break
time.sleep(5)
```python
with open("reference.png", "rb") as f: image_url = requests.post( f"{BASE}/upload_file", headers={"x-api-key": API_KEY}, files={"file": f} ).json()["url"]
resp = requests.post( f"{BASE}/gemini-omni-image-to-video", headers={"x-api-key": API_KEY}, json={ "prompt": "Animate the subject with subtle breathing and gentle hair movement", "image_urls": [image_url], # list of 1–5 URLs "duration": 6, "aspect_ratio": "9:16", "resolution": "1080p", # "720p" | "1080p" | "4k" # "audio_ids": ["aoede"], # optional — list of up to 3 voices # "character_ids": [...], # optional character IDs }, )
#### Video Edit
python with open("clip.mp4", "rb") as f: video_url = requests.post( f"{BASE}/upload_file", headers={"x-api-key": API_KEY}, files={"file": f} ).json()["url"]
resp = requests.post( f"{BASE}/gemini-omni-video-edit", headers={"x-api-key": API_KEY}, json={ "prompt": "Change the season to winter, add falling snow", "video_url": video_url, "trim_start": 0, "trim_end": 8, # max 10 s window; source video max 30 s "duration": 8, "aspect_ratio": "16:9", "resolution": "1080p", # "720p" | "1080p" | "4k" # "image_urls": [...], # optional reference images (max 5) # "audio_ids": ["aoede"], # optional — list of up to 3 voices # "character_ids": [...], # optional character IDs }, )
#### Audio Profile
python resp = requests.post( f"{BASE}/gemini-omni-audio", headers={"x-api-key": API_KEY}, json={ "audio_id": "aoede", # base voice from AUDIO_IDS "name": "My Narrator Voice", # "voice_description": "Warm storytelling tone", # optional # "example_dialogue": "Welcome to the story.", # optional }, ) request_id = resp.json()["request_id"]
| Parameter | T2V | I2V | V2V | Values | |||
|---|---|---|---|---|---|---|---|
prompt | ✓ | ✓ | ✓ | string (required) | |||
duration | ✓ | ✓ | ✓ | 4 \ | 6 \ | 8 \ | 10 (default 8) |
aspect_ratio | ✓ | ✓ | ✓ | "16:9" \ | "9:16" (default "16:9") | ||
resolution | ✓ | ✓ | ✓ | "720p" \ | "1080p" \ | "4k" (default "1080p") | |
audio_ids | ✓ | ✓ | ✓ | list of up to 3 voice names (optional) | |||
character_ids | ✓ | ✓ | ✓ | list of character IDs (optional) | |||
seed | ✓ | ✓ | ✓ | int 0–2147483647 (optional) | |||
image_urls | — | ✓ | opt | list of 1–5 URLs, each ≤20 MB | |||
video_url | — | — | opt | URL, max 100 MB / 30 s | |||
trim_start | — | — | ✓ | float seconds (default 0) | |||
trim_end | — | — | ✓ | float seconds, max 10 s window (default 10) |
Image slot budget (V2V): when video_url is set, max 5 image_urls.
Available audio_ids voices: achernar · achird · algenib · algieba · alnilam · aoede · autonoe · callirrhoe · charon · despina · enceladus · erinome · fenrir · gacrux · iapetus · kore · laomedeia · leda · orus · puck · pulcherrima · rasalgethi · sadachbia · sadaltager · schedar · sulafat · umbriel · vindemiatrix · zephyr · zubenelgenubi
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
经综合评估,Awesome-Gemini-Omni-API-Prompts — Claude MCP 必备工具中文教程 在MCP工具赛道中表现稳健,质量良好。如果你已有明确的使用需求,可以直接上手体验;如果还在评估阶段,建议对比同类工具后再做决策。
| 原始名称 | Awesome-Gemini-Omni-API-Prompts |
| 原始描述 | Curated Google Gemini Omni prompts & API examples — text-to-video, image-to-video, video edit via the Gemini Omni API on muapi.ai. Python wrapper, MCP server, REST examples. |
| Topics | ai-artai-filmmakingai-videoawesome-listgemini-apigemini-omniprompt |
| GitHub | https://github.com/Anil-matcha/Awesome-Gemini-Omni-API-Prompts |
| License | MIT |
| 语言 | Python |
收录时间:2026-05-22 · 更新时间:2026-05-22 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端