原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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Gemini

作者:houtini-ai版本 2.10.1i★ –i在你的电脑上运行
注册名称io.github.houtini-ai/gemini

安装

概览

作者提供的说明(英文原文)

Model Context Protocol server for Google Gemini AI with chat, research, and grounding

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 聊天与邮件
  • 你需要填写:GEMINI_API_KEY

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "gemini": {
      "command": "npx",
      "args": [
        "-y",
        "@houtini/gemini-mcp"
      ],
      "env": {
        "GEMINI_API_KEY": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add gemini --env GEMINI_API_KEY=your-value -- npx -y @houtini/gemini-mcp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "gemini": {
      "command": "npx",
      "args": [
        "-y",
        "@houtini/gemini-mcp"
      ],
      "env": {
        "GEMINI_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "gemini": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@houtini/gemini-mcp"
      ],
      "env": {
        "GEMINI_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • GEMINI_API_KEY 机密 必填 env
    Google AI Studio API key (get from https://aistudio.google.com/apikey)

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月8日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 houtini-ai 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“聊天与邮件”中的其他服务器比较i

  • 星标数多于此分类中其他 1838 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 1838 个服务器的 68% 更新
  • 基础检查结果等于或优于此分类中其他 1838 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Gemini 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:GEMINI_API_KEY

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(2.10.1)于14天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:Vexa, emailmd, MCP WhatsApp Cloud

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Vexa

作者:Vexa-ai

Meeting bot and transcripts for Google Meet, Teams and Zoom. Live or after, speakers labelled.

在云端运行★ 2,949Apache-2.02个月前更新
安装

emailmd

作者:anypost

Render markdown into email-safe HTML, lint drafts for deliverability problems, and preview emails.

电脑或云端★ 1,385MIT32天前更新
安装

MCP WhatsApp Cloud

作者:codespar

MCP server for WhatsApp Cloud API (Meta) — messages, media, and templates via Graph API

在你的电脑上运行★ 277MIT5个月前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Gemini MCP - Google Gemini image generation, video and search grounding inside Claude

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


What it makes

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_imageedit_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=technicalgenerate_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.


Get started in two minutes

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:

  • Windows: C:\Users\{username}\AppData\Roaming\Claude\claude_desktop_config.json
  • macOS: ~/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.

Local build instead

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 (CLI)

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.


What it does

Chat with Google Search grounding
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.

Deep research
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.

Image generation with search grounding
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.

Video generation with Veo 3.1
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 vertical
  • generateAudio - on by default; dialogue and effects that match the prompt
  • firstFrameImage - animate from a still (that's how the cockpit clip above was made)
  • referenceImages - up to three, for characte

只显示了开头部分;其余内容请在仓库中阅读

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