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Meeting bot and transcripts for Google Meet, Teams and Zoom. Live or after, speakers labelled.
제작자가 쓴 설명(영어 원문)
Model Context Protocol server for Google Gemini AI with chat, research, and grounding
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
GEMINI_API_KEY비밀로 표시된 값은 내 계정의 열쇠예요. 절대 다른 사람과 공유하거나 채팅에 붙여 넣지 마세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"gemini": {
"command": "npx",
"args": [
"-y",
"@houtini/gemini-mcp"
],
"env": {
"GEMINI_API_KEY": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add gemini --env GEMINI_API_KEY=your-value -- npx -y @houtini/gemini-mcp실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"gemini": {
"command": "npx",
"args": [
"-y",
"@houtini/gemini-mcp"
],
"env": {
"GEMINI_API_KEY": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"gemini": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@houtini/gemini-mcp"
],
"env": {
"GEMINI_API_KEY": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 GitHub 계정 houtini-ai 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
입력해야 할 값: GEMINI_API_KEY
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(2.10.1)은 13일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.
같은 카테고리에는: Vexa, emailmd, MCP WhatsApp Cloud
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Meeting bot and transcripts for Google Meet, Teams and Zoom. Live or after, speakers labelled.
Render markdown into email-safe HTML, lint drafts for deliverability problems, and preview emails.
MCP server for WhatsApp Cloud API (Meta) — messages, media, and templates via Graph API
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
I've had this Gemini MCP server running in my Claude Desktop setup for the best part of a year now. It's one of the few I leave switched on permanently. Not because Gemini replaces Claude (it doesn't), but because grounded search, image generation, SVG diagrams and video are things Gemini happens to do well, and having them as tools inside Claude beats flipping between browser tabs.
Fourteen tools, built around the models people actually come looking for: Nano Banana Pro (gemini-3-pro-image) and Nano Banana 2 for images, Veo 3.1 for video with synchronised audio, Gemini 4 Argon for chat and Gemini 3.1 Pro for deep research, both with Google Search grounding. Everything previews inline in Claude Desktop through MCP Apps rather than landing as a file path you have to go and open.
One npx command. That's it.
New here? The full user guide walks through every tool, the free-tier gotcha, and what to do when something breaks.
Quick Navigation
What it makes | Get started | What it does | Image output | Configuration | Tools | Models | Requirements
Everything below came out of the tools in this repo, unretouched, on the afternoon I wrote this. Prompts are in the captions so you can judge for yourself.
Image generation with search grounding. One generate_image call with use_search=true. Gemini looked up the actual Met Office forecast for the week, then drew it. The dates and temperatures are real (well, as real as a forecast gets).
*Prompt: "A polished editorial infographic poster: London weather, this week. Use real forecast data from search for the next 5 days..." - gemini-3-pro-image, 16:9, 2K.*
Text that's actually spelled correctly. This is the thing Nano Banana Pro does that the previous generation of image models couldn't. Every label here is straight out of the model.
*Prompt: "A clean, magazine-quality infographic titled How an MCP tool call works, with four numbered steps..." - gemini-3-pro-image.*
Generate, then edit. Left is generate_image. Right is edit_image on that file with one sentence of instructions: change the track to Monza in daylight, swap the rim lighting for window light, make the pedals red. Same cockpit, same camera angle.
generate_image | edit_image |
|---|---|
Image to video with Veo 3.1. The night-time cockpit above, passed to generate_video as firstFrameImage. Eight seconds at 1080p with generated audio (engine note, tyre hiss) - the GIF below is silent and squashed for GitHub, the real file is a proper MP4.
SVG that you can actually use. Not a picture of a diagram - real vector markup you can drop into a page, edit by hand or commit to a repo. Both of these are the raw .svg files the tool wrote to disk.
generate_svg style=technical | generate_svg style=data-viz |
|---|---|
A landing page from a paragraph. generate_landing_page with a brief, a company name and a brand colour. Self-contained HTML, inline CSS, the little chart in the hero is animated SVG. Screenshot of the file opened in Chrome, nothing else touched.
And the fast one. Nano Banana 2 (gemini-3.1-flash-image) for when you want volume rather than 4K. This took about ten seconds.
Step 1: Get a Gemini API key
Go to Google AI Studio and create one.
A word on the free tier, because the defaults lean on a paid model. Google's pricing page gives Gemini 3 Flash Preview a free tier, but the flagship models are paid-only - and gemini-4-argon is the default for gemini_chat and generate_landing_page, with gemini-3.1-pro-preview the default for gemini_deep_research (synthesis) and analyze_image. On a free key those calls will fail unless you point them at a free model: set GEMINI_DEFAULT_MODEL=gemini-3-flash-preview (covers chat and landing pages), GEMINI_DEEP_RESEARCH_MODEL and GEMINI_IMAGE_ANALYSIS_MODEL likewise, or pass model per call. generate_svg already defaults to gemini-3-flash-preview. Check the pricing page for the other models before relying on them - Google changes these tiers.
Step 2: Add to your Claude Desktop config
Config file locations:
C:\Users\{username}\AppData\Roaming\Claude\claude_desktop_config.json~/Library/Application Support/Claude/claude_desktop_config.json{
"mcpServers": { "gemini": { "command": "npx", "args": ["@houtini/gemini-mcp"], "env": { "GEMINI_API_KEY": "your-api-key-here" } } } }
Step 3: Restart Claude Desktop
That's it. Tools show up automatically. npx pulls the package on first run, so there's no separate install.
For development, or if you'd rather not rely on npx:
git clone https://github.com/houtini-ai/gemini-mcp
cd gemini-mcp npm install --include=dev npm run build
Then point your config at the local build:
{
"mcpServers": { "gemini": { "command": "node", "args": ["C:/path/to/gemini-mcp/dist/index.js"], "env": { "GEMINI_API_KEY": "your-api-key-here" } } } }
Claude Code doesn't read claude_desktop_config.json. Use claude mcp add instead:
claude mcp add -e GEMINI_API_KEY=your-api-key-here -s user gemini -- npx -y @houtini/gemini-mcp
With an output directory for images and video:
claude mcp add \
-e GEMINI_API_KEY=your-api-key-here \ -e GEMINI_IMAGE_OUTPUT_DIR=/path/to/output \ -s user \ gemini -- npx -y @houtini/gemini-mcp
Check with claude mcp get gemini - you want to see Status: Connected.
Use gemini:gemini_chat to ask: "What changed in the MCP spec in the last month?"
Grounding is on by default. Gemini searches Google before it answers, so you get this month's information rather than a training-cutoff guess, and the sources come back as markdown links. For questions where you want pure reasoning ("explain this code", that sort of thing) set grounding: false.
Runs on gemini-4-argon (Gemini 4 Argon) unless you say otherwise. Pass model: "gemini-3.8-flash" if you'd rather have speed than depth, or model: "gemini-3.1-pro-preview" for the previous flagship. thinking_level works on Gemini 3.x and 4 models: high for the hard stuff, low to keep it snappy.
Use gemini:gemini_deep_research with:
research_question="What are the current approaches to AI agent memory management?" max_iterations=5
Runs grounded search passes and then writes them up as one report. The passes run on gemini-3.8-flash with low thinking (they're gathering facts, not reasoning about them), and the synthesis at the end runs on gemini-3.1-pro-preview with high thinking. Two passes plus a synthesis is the default and lands in two to three minutes.
That split matters more than it sounds. Earlier versions ran everything on Pro with full thinking, and one pass on a broad question could run past Claude Desktop's four-minute timeout on its own. Keep max_iterations at 2 or 3 in Claude Desktop; in an IDE or an agent framework, 5 to 7 produces noticeably better synthesis. focus_areas takes an array if you want to steer each pass.
Use gemini:generate_image with:
prompt="Stock price chart showing Apple (AAPL) closing prices for the last 5 trading days" use_search=true aspectRatio="16:9"
Default model is gemini-3-pro-image, which is Nano Banana Pro now that it's out of preview. It renders legible text, does 4K, and it's the only one that supports conversational editing. gemini-3.1-flash-image (Nano Banana 2) is the fast option - not far off in quality, a fraction of the time and the cost. There's a Lite variant too if you're doing hundreds.
With use_search=true, Gemini looks things up before it draws. Weather, prices, sports results, that kind of data-driven image works reliably. The full-resolution file always goes to disk; the inline preview is resized to fit the MCP transport cap but the original is untouched.
Use gemini:generate_video with:
prompt="A close-up shot of a futuristic coffee machine brewing a glowing blue espresso, steam rising dramatically. Cinematic lighting." resolution="1080p" durationSeconds=8
Google's Veo 3.1. Four to eight second clips at up to 4K with native, synchronised audio. It's asynchronous on Google's side and takes two to five minutes; the tool polls until it's ready so you don't have to.
Options worth knowing about:
aspectRatio - 16:9 landscape or 9:16 for verticalgenerateAudio - on by default; dialogue and effects that match the promptfirstFrameImage - animate from a still (that's how the cockpit clip above was made)referenceImages - up to three, for characte앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요