Gemini MCP for Claude Desktop

While this might not appear to be my first post on Houtini, it is a particularly special one. I've had Houtini-LM live for around 3 weeks, built a website, written the user guide, so all in all I've had a very productive time. But, now the real work begins. I have to convince you that all of that effort was a good idea.

I think that AI based tool use is completely inevitable. Think for just a moment - what might "work" look like in a few years? I believe that AI will be completely embedded in the day to day operations of the businesses we work for.

AI tools, used properly, take the "grunt" work away. It's a mistake to think of this emergence as a threat. With AI, we can iterate and innovate on our own ideas. In the future, ideas will be the currency, execution the commodity.

I suspect we even face the extinction of the SAAS web UI. OK, that's a bit of a brave statement - but what I've learned, and what I am now sharing, is that with a well configured AI chat app (I use Claude Desktop *a lot*) can perform any action available via an SAAS API service. The power of this is very hard to come to terms with immediately, but it is a massive change and very, very important to comprehend.

Those are all big statements and it's better to show, not tell. So...

Let's start at the beginning. We will learn how to install an MCP server as a Claude Desktop user.

We're going to do something cool and connect Gemini via our MCP ( github / npm ).

I've been working for some time with this concept. Houtini-lm, our local LLM MCP (originally built for LM Studio, now serving via vLLM) can augment, review, generate or interrogate data to supplement a chat in Claude. A second pair of hands? A second pair of eyes. For now, though, why would you add Gemini to Claude Desktop?

LLMs don't make great search engines because they are not search engines. They're language models trained on historical data with knowledge cutoffs, meaning they don't access "real-time" information and might generate plausible-sounding but inaccurate content. This is where grounding becomes essential. Grounding connects AI responses to verifiable, current sources by integrating web search, then providing citations that link claims directly to their sources.

This transforms the AI from a creative writer into a research assistant that can access current information whilst showing exactly where that information comes from. Gemini MCP for Claude was built for precisely this - a research workflow tool to add to Claude.

If you want to begin testing MCP servers for the first time, read on. If you already know the ropes check out our NPM repo here , or from Github here .

Getting Started: Foundations

Before we get into installing MCP servers, let's establish what makes this all possible. MCP servers are built on Node.js and distributed through npm (Node Package Manager), so it's worth knowing what they are.

What is Node.js?

Node.js runs JavaScript on your computer rather than inside a web browser. Think of it as the engine that powers MCP servers - it provides all the necessary components to run JavaScript on your computer, not just in your browser. This is what allows MCP servers to function as standalone tools that Claude can communicate with.

Node.js is particularly good at handling lots of small concurrent requests, which is exactly what happens when Claude talks to external tools. It's the same technology that powers everything from web servers to command-line tools.

The MCP-npm Connection

Many MCP servers use npm (think of npm as a big, free software registry) for distribution. This means that installing an MCP server is as simple as running an npm command. When developers create MCP servers (like our Gemini MCP), they:

1. Build the server logic using Node.js
2. Package it as an npm module with all its dependencies
3. Publish it to the npm registry
4. Make it available for anyone to install with a simple command

This is what makes MCP servers so accessible. You're not downloading random executables or dealing with complex installation processes - you're using the same package management system that millions of developers use every day.

Prerequisites: Installing Node.js

Before you can install any MCP server, you'll need Node.js on your system. Here's how to get it:

For Windows Users:

1. Head to nodejs.org and download the LTS (Long-Term Support) version
2. Run the .msi installer - accept the defaults and make sure to install the tools for Native Modules when prompted
3. Once complete, open Command Prompt and verify with:
   

   node -v
   npm -v

For macOS Users:

1. Visit nodejs.org and download the LTS version
2. Run the .pkg installer and follow the prompts
3. Open Terminal and verify your installation:
   

   node -v
   npm -v

Pro tip for Mac users: If you have Homebrew installed, you can simply run brew install node instead.

Installing Your First MCP Server

Now that you have Node.js and npm ready, installing MCP servers is straightforward. Let's use the Gemini MCP as our example:

1. Get Your API Key

Visit  Google AI Studio  to create your free API key.

Step 2: Configure Claude Desktop

Find your claude_desktop_config.json file - this is where you register your MCP:

Windows: %APPDATA%\Claude\claude_desktop_config.json
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

Add this configuration to your Claude Desktop config file:

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

*Quite often, the "mcpservers": bit of that json is already in the default json config file, so pay attention to how many brackets you've pasted. Only valid json will work.

Step 3: Restart Claude Desktop

After updating the configuration file, restart Claude Desktop to load the new MCP server.

Using Gemini in Claude

Whenever I need some additional research carrying out on a project, Gemini is powerful. The grounding metadata is included in the response so you can dig out the citation sources of the information you're mining. While this mcp is primarily intended for research purposes I did have some fun and asked Claude and Gemini to decide on what they would "like to work on together" in a research context:

That's the whole process. Once you've done it for Gemini, every other MCP server follows the same shape: an npm package, a config entry, a restart. And if you don't have Claude Desktop yet, you can start with a free week of Claude Code .

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