Grounding Lite MCP Server

Grounding Lite MCP Server

Provides custom tools to the Gemini model for spatially grounding responses using Google Maps Platform APIs (Places, Routes, Elevation).

Category
访问服务器

README

Grounding Lite Sample App

thumbnail

Overview

This repository contains a sample application demonstrating the use of Grounding Lite with the Gemini API to provide spatially grounded responses using Google Maps Platform data. The application uses the agent to converse and a companion 3D Google Maps.

Please refer to the official documentation for more details: Grounding Lite Documentation.

Architecture

The application employs a client-server architecture where a Node.js backend hosts the Model Context Protocol (MCP) server, allowing the Gemini model to dynamically access real-time geographic information via Google Maps Platform tools.

Key Components

  • Client (Web App): Built with Vite and Lit, handles user chat interaction and displays the dynamic 3D map (using the Maps JavaScript API).
  • Backend Server (Node/Express): Acts as a central proxy, managing communication between the Client, the Gemini API, and hosting the MCP Server.
  • Grounding Lite MCP Server: Exposes a set of custom tools to the Gemini model, providing the capability to ground its responses in real-world geographic data.
  • MCP Tools: Custom functions defined by the MCP server that translate natural language requests into structured Google Maps Platform API calls (Places API, Routes API, Elevation API).
  • Gemini API: The Large Language Model (LLM) that leverages the provided MCP tools for geographically accurate, grounded responses.

Data Flow Diagram (Grounding Lite)

graph TD
    subgraph Client/UI
        C[Client Web App]
    end
    style Client/UI fill:#FFFFFF

    subgraph Backend Services
        B[Backend Server]
    end

    subgraph Gemini and APIs
        G[AI API]
        P[Maps Platform other APis]
    end

    subgraph Grounding Lite
        M[MCP Server] --> T[MCP Tools]
    end

    C --> B("User Query")
    
    %% Combined edges to prevent overwriting in some renderers
    B --> G("Send Query + Tool Schema<br/>Send Tool Results")
    G --> B("Model Decision (Tool Call)<br/>Final Grounded Response")

    B --> M("Execute MCP Tool")
    T --> P("Call Specific GMP API")
    P --> T("Return Data")
    T --> B("Return Tool Results")

    B --> C("Display Response")

Prerequisites

  • A Google Cloud Project with the necessary APIs enabled
  • Create API keys
    • Server API Key:
      • Grounding Lite MCP Service
      • Gemini API (aka Generative Language API)
      • Complementary APIs to manage the 3D map:
        • Routes API for the polyline
        • Places API (New) for the name of the businesses on markers
        • Elevation API to adjust camera altitude to the map location
    • Client API key:
      • Maps JavaScript API
      • Places UI Kit
  • Node.js and npm installed.

Installation

Key Dependencies

  • Vite: A fast, modern development server and build tool for web projects.
  • @google/genai: The official SDK for interacting with the Google Gemini API.
  • @modelcontextprotocol/sdk: The SDK for creating and interacting with Model Context Protocol (MCP) servers.
  • Lit: A simple library for building fast, lightweight web components.
  • Tailwind CSS: A utility-first CSS framework for rapidly building custom user interfaces.
  • Express: A minimal and flexible Node.js web application framework used for the backend server.
  • dotenv: A zero-dependency module that loads environment variables from a .env file.
  1. Install the dependencies:
npm install
  1. Configure your environment:

Create a .env file in the root directory and add your API keys.

For the frontend (Google Maps JavaScript API loading), use:

GOOGLE_MAPS_API_KEY="YOUR_GOOGLE_MAPS_API_KEY"

For the server-side (Maps Platform MCP calls and Gemini API calls), use:

SERVER_API_KEY="YOUR_SERVER_API_KEY_HERE"

Architecture

Running the Application

This application uses concurrently to run both the Vite frontend server and the Node.js backend server (which hosts the Model Context Protocol (MCP) server).

Development Mode

Run the application in development mode:

npm run dev

This command executes: concurrently "vite" "npm run dev:server:watch"

  • The frontend (Vite) will typically run on http://localhost:5173.
  • The backend server (Node.js/Express) handles the MCP server setup and API routes.

Production Build

  1. Build the application:
npm run build
  1. Start the production server:
npm start
# or
npm run start:prod

Cloud Run Deployment

This application can be deployed to Google Cloud Run by building and deploying directly from the source code.

  1. Ensure prerequisites are met: You must have the Google Cloud CLI installed and authenticated.

  2. Deploy the application: Run the following command, replacing the environment variable placeholders and project ID with your values.

    Note: For this sample app to function correctly, you must pass the SERVER_API_KEY (for server-side Google Maps Platform and Gemini APIs) and GOOGLE_MAPS_API_KEY (for client-side Maps JavaScript API) as environment variables.

  3. Use the deployment script: We have provided a generic deployment script, deploy.sh, which reads SERVER_API_KEY and GOOGLE_MAPS_API_KEY directly from your local .env file and passes them securely to the gcloud run deploy command.

    The generic script requires the GCP Project ID and Region as arguments:

./deploy.sh YOUR_GCP_PROJECT_ID us-central1

Terms of Service

This is a sample application provided for demonstration purposes.

This sample application is not a Google Maps Platform Core Service. Therefore, the Google Maps Platform Terms of Service (e.g. Technical Support Services, Service Level Agreements, and Deprecation Policy) do not apply to the code in this solution.

Support

This sample application is offered via an open source license. It is not governed by the Google Maps Platform Support Technical Support Services Guidelines, the SLA, or the Deprecation Policy (however, any Google Maps Platform services used by the sample application remain subject to the Google Maps Platform Terms of Service).

If you find a bug, or have a feature request, please file an issue on GitHub. If you would like to get answers to technical questions from other Google Maps Platform developers, ask through one of our developer community channels. If you'd like to contribute, please check the Contributing guide.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选