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Menghubungkan IDE Anda ke BigQuery menggunakan MCP Toolbox
Panduan ini menunjukkan cara menggunakan MCP Toolbox for Databases untuk menghubungkan instance BigQuery Anda ke berbagai Integrated Development Environment (IDE) dan alat developer. Alat ini menggunakan Model Context Protocol (MCP), sebuah protokol terbuka untuk menghubungkan model bahasa besar (LLM) ke sumber data seperti BigQuery, sehingga Anda dapat menjalankan kueri SQL dan berinteraksi dengan project langsung dari alat yang sudah ada.
Panduan ini menunjukkan proses koneksi untuk IDE berikut:
Konfigurasi peran dan izin yang diperlukan untuk menyelesaikan tugas ini. Anda memerlukan peran Pengguna BigQuery (roles/bigquery.user), peran Pelihat Data BigQuery (roles/bigquery.dataViewer), atau izin IAM yang setara untuk terhubung ke instance.
Download MCP Toolbox versi terbaru sebagai biner. Pilih biner yang sesuai dengan sistem operasi (OS) dan arsitektur CPU Anda. Anda harus menggunakan MCP Toolbox versi V0.7.0 atau yang lebih baru:
Catatan: Variabel lingkungan BIGQUERY_PROJECT menentukan Project ID Google Cloud default yang akan digunakan MCP Toolbox. Semua operasi BigQuery, seperti menjalankan kueri, dijalankan dalam project ini.
Menggunakan alat
Alat AI Anda kini terhubung ke BigQuery menggunakan MCP. Coba minta asisten AI Anda untuk mencantumkan tabel, membuat tabel, atau menentukan dan menjalankan pernyataan SQL lainnya.
Alat berikut tersedia untuk LLM:
ask_data_insights: melakukan analisis data, mendapatkan insight, atau menjawab pertanyaan kompleks tentang isi tabel BigQuery.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-09-04 UTC."],[],[],null,["# Connect your IDE to BigQuery using MCP Toolbox\n==============================================\n\nThis guide shows you how to use the [MCP Toolbox for Databases](https://github.com/googleapis/genai-toolbox) to connect your BigQuery instance to a variety of Integrated Development Environments (IDEs) and developer tools. It uses the [Model Context Protocol (MCP)](https://modelcontextprotocol.io/introduction), an open protocol for connecting large language models (LLMs) to data sources like BigQuery, allowing you to run SQL queries and interact with your project directly from your existing tools.\n\nThis guide demonstrates the connection process for the following IDEs:\n\n- [Cursor](#configure-your-mcp-client)\n- [Windsurf](#configure-your-mcp-client) (formerly Codeium)\n- [Visual Studio Code](#configure-your-mcp-client) (Copilot)\n- [Cline](#configure-your-mcp-client) (VS Code extension)\n- [Claude desktop](#configure-your-mcp-client)\n- [Claude code](#configure-your-mcp-client)\n\nBefore you begin\n----------------\n\n1. In the Google Cloud console, on the [project selector page](https://console.cloud.google.com/projectselector2/home/dashboard), select or create a Google Cloud project.\n\n2. [Make sure that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n3. [Enable the BigQuery API in the Google Cloud project](https://console.cloud.google.com/flows/enableapi?apiid=bigquery.googleapis.com&redirect=https://console.cloud.google.com).\n\n4. Configure the required roles and permissions to complete this task. You will need the [BigQuery User](/bigquery/docs/access-control) role (`roles/bigquery.user`), the BigQuery Data Viewer role (`roles/bigquery.dataViewer`), or equivalent IAM permissions to connect to the instance.\n\n5. Configure [Application Default Credentials (ADC)](/docs/authentication/set-up-adc-local-dev-environment) for your environment.\n\nInstall the MCP Toolbox\n-----------------------\n\n1. Download the latest version of the MCP Toolbox as a binary. Select the [binary](https://github.com/googleapis/genai-toolbox/releases) corresponding to your operating system (OS) and CPU architecture. You must use MCP Toolbox version V0.7.0 or later:\n\n ### linux/amd64\n\n ```\n curl -O https://storage.googleapis.com/genai-toolbox/VERSION/linux/amd64/toolbox\n ```\n\n Replace \u003cvar translate=\"no\"\u003eVERSION\u003c/var\u003e with the MCP Toolbox\n version---for example `v0.7.0`.\n\n ### macOS darwin/arm64\n\n ```\n curl -O https://storage.googleapis.com/genai-toolbox/VERSION/darwin/arm64/toolbox\n ```\n\n Replace \u003cvar translate=\"no\"\u003eVERSION\u003c/var\u003e with the MCP Toolbox\n version---for example `v0.7.0`.\n\n ### macOS darwin/amd64\n\n ```\n curl -O https://storage.googleapis.com/genai-toolbox/VERSION/darwin/amd64/toolbox\n ```\n\n Replace \u003cvar translate=\"no\"\u003eVERSION\u003c/var\u003e with the MCP Toolbox\n version---for example `v0.7.0`.\n\n ### windows/amd64\n\n ```\n curl -O https://storage.googleapis.com/genai-toolbox/VERSION/windows/amd64/toolbox\n ```\n\n Replace \u003cvar translate=\"no\"\u003eVERSION\u003c/var\u003e with the MCP Toolbox\n version---for example `v0.7.0`.\n2. Make the binary executable:\n\n chmod +x toolbox\n\n3. Verify the installation:\n\n ./toolbox --version\n\nConfigure the MCP client\n------------------------\n\n### Claude code\n\n\u003cbr /\u003e\n\n1. Install [Claude Code](https://docs.anthropic.com/en/docs/agents-and-tools/claude-code/overview). \n2. Create `.mcp.json` file in your project root, if it doesn't exist. \n3. Add the configuration, replace the environment variables with your values, and save: \n\n```\n{\n \"mcpServers\": {\n \"bigquery\": {\n \"command\": \"./PATH/TO/toolbox\",\n \"args\": [\"--prebuilt\",\"bigquery\",\"--stdio\"],\n \"env\": {\n \"BIGQUERY_PROJECT\": \"PROJECT_ID\"\n }\n }\n }\n}\n```\n\n### Claude desktop\n\n\u003cbr /\u003e\n\n1. Open [Claude Desktop](https://claude.ai/download) and navigate to **Settings** . \n2. In the **Developer** tab, click **Edit Config** to open the configuration file. \n3. Add the configuration, replace the environment variables with your values, and save: \n\n```\n{\n \"mcpServers\": {\n \"bigquery\": {\n \"command\": \"./PATH/TO/toolbox\",\n \"args\": [\"--prebuilt\",\"bigquery\",\"--stdio\"],\n \"env\": {\n \"BIGQUERY_PROJECT\": \"PROJECT_ID\"\n }\n }\n }\n}\n```\n\n4. Restart Claude Desktop. \n5. The new chat screen displays a hammer (MCP) icon with the new MCP server. \n\n\u003cbr /\u003e\n\n### Cline\n\n\u003cbr /\u003e\n\n1. Open [Cline](https://github.com/cline/cline) extension in VS Code and tap **MCP Servers** icon. \n2. Tap Configure MCP Servers to open the configuration file. \n3. Add the following configuration, replace the environment variables with your values, and save: \n\n```\n{\n \"mcpServers\": {\n \"bigquery\": {\n \"command\": \"./PATH/TO/toolbox\",\n \"args\": [\"--prebuilt\",\"bigquery\",\"--stdio\"],\n \"env\": {\n \"BIGQUERY_PROJECT\": \"PROJECT_ID\"\n }\n }\n }\n}\n```\n\nA green active status appears after the server connects successfully. \n\n### Cursor\n\n\u003cbr /\u003e\n\n1. Create the `.cursor` directory in your project root if it doesn't exist. \n2. Create the `.cursor/mcp.json` file if it doesn't exist and open it. \n3. Add the following configuration, replace the environment variables with your values, and save: \n\n```\n{\n \"mcpServers\": {\n \"bigquery\": {\n \"command\": \"./PATH/TO/toolbox\",\n \"args\": [\"--prebuilt\",\"bigquery\",\"--stdio\"],\n \"env\": {\n \"BIGQUERY_PROJECT\": \"PROJECT_ID\"\n }\n }\n }\n}\n```\n\n4. Open [Cursor](https://www.cursor.com/) and navigate to **Settings \\\u003e Cursor Settings \\\u003e MCP** . A green active status appears when the server connects. \n\n### Visual Studio Code (Copilot)\n\n\u003cbr /\u003e\n\n1. Open [VS Code](https://code.visualstudio.com/docs/copilot/overview) and create `.vscode` directory in your project root if it does not exist. \n2. Create the `.vscode/mcp.json` file if it doesn't exist, and open it. \n3. Add the following configuration, replace the environment variables with your values, and save: \n\n```\n{\n \"servers\": {\n \"bigquery\": {\n \"command\": \"./PATH/TO/toolbox\",\n \"args\": [\"--prebuilt\",\"bigquery\",\"--stdio\"],\n \"env\": {\n \"BIGQUERY_PROJECT\": \"PROJECT_ID\"\n }\n }\n }\n}\n```\n\n### Windsurf\n\n\u003cbr /\u003e\n\n1. Open [Windsurf](https://docs.codeium.com/windsurf) and navigate to Cascade assistant. \n2. Click the MCP icon, then click **Configure** to open the configuration file. \n3. Add the following configuration, replace the environment variables with your values, and save: \n\n```\n{\n \"mcpServers\": {\n \"bigquery\": {\n \"command\": \"./PATH/TO/toolbox\",\n \"args\": [\"--prebuilt\",\"bigquery\",\"--stdio\"],\n \"env\": {\n \"BIGQUERY_PROJECT\": \"PROJECT_ID\"\n }\n }\n }\n}\n```\n\nUse the tools\n-------------\n\nYour AI tool is now connected to BigQuery using MCP. Try asking your AI assistant to list tables, create a table, or define and execute other SQL statements.\n\nThe following tools are available to the LLM:\n\n- **execute_sql**: execute SQL statement\n- **get_dataset_info**: get dataset metadata\n- **get_table_info**: get table metadata\n- **list_dataset_ids**: list datasets\n- **list_table_ids**: list tables\n\n| **Note:** Prebuilt tools are pre-1.0, so expect some tool changes between versions. LLMs will adapt to the tools available, so this shouldn't affect most users."]]
