MCP with Gemini Tutorial
About
It is a tutorial repository that provides the complete code for building a Model Context Protocol (MCP) server with Google's Gemini 2.0 model. The server integrates Brave Search and exposes tools for web and local search.
Explore
- Complete MCP server with Brave Search integration
- Two implemented tools: Web Search and Local Search
- Example clients for basic and Gemini‑powered usage
- Easy to extend with custom tools and schemas
- Uses Bun for fast TypeScript execution
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
MCP with Gemini TutorialCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
- Bun (for fast TypeScript execution)
- Brave Search API key
- Google API key for Gemini access
bun install
Create a .env file with your API keys:
BRAVE_API_KEY="your_brave_api_key"
GOOGLE_API_KEY="your_google_api_key"
bun examples/basic-client.ts
bun examples/gemini-tool-function.ts
```
This MCP server exposes two main tools:
1. Web Search: For general internet searches via Brave Search
2. Local Search: For finding businesses and locations via Brave Search
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"mcp with gemini tutorial": {
"mcp-gemini-tutorial": {
"command": "bun",
"args": [
"examples/basic-client.ts"
]
}
}
}
}McpServers
{
"mcp-gemini-tutorial": {
"command": "bun",
"args": [
"examples/basic-client.ts"
]
}
}This repository contains the complete code for the tutorial on building Model Context Protocol (MCP) servers with Google's Gemini 2.0 model, as described in this blog post.
What is Model Context Protocol (MCP)?
MCP is an open standard developed by Anthropic that enables AI models to seamlessly access external tools and resources. It creates a standardized way for AI models to interact with tools, access the internet, run code, and more, without needing custom integrations for each tool or model.
Key benefits include:
- Interoperability: Any MCP-compatible model can use any MCP-compatible tool
- Modularity: Add or update tools without changing model integrations
- Standardization: Consistent interface reduces integration complexity
- Separation of Concerns: Clean division between model capabilities and tool functionality
Project Overview
This tutorial demonstrates how to:
- Build a complete MCP server with Brave Search integration
- Connect it to Google's Gemini 2.0 model
- Create a flexible architecture for AI-powered applications
Getting Started
Prerequisites
- Bun (for fast TypeScript execution)
- Brave Search API key
- Google API key for Gemini access
Installation
```bash
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