google-search-mcp

An advanced Model Context Protocol (MCP) server that provides a high-level agentic interface to Google's Gemini 3.1 models via Vertex AI.

Unlike a standard search tool, this server exposes a single "Agent" tool that combines real-time Google Search, deep URL analysis, and Python code execution to solve complex, multi-step research and data tasks.

• Search Grounding: Uses Google Search to find up-to-the-minute information.
• URL Context: Automatically fetches and parses the content of specific web pages for deep analysis.
• Code Execution: Writes and executes Python code on-the-fly to perform calculations, data manipulation, or logical reasoning.
• Thinking Mode: Utilizes Gemini's internal reasoning capabilities (ThinkingLevel.MEDIUM) to plan and refine its approach before answering.

1. Google Cloud Project: You must have a Google Cloud project with the Vertex AI API enabled.
2. Authentication: You must have gcloud CLI installed and authenticated:

    gcloud auth application-default login

1. Permissions: Your account needs the Vertex AI User role on the project.

The server requires the following environment variables:

| Variable | Description | Default | | :--- | :--- | :--- | | GCP_PROJECT_ID | Your Google Cloud Project ID (Required) | - | | GCP_LOCATION | Vertex AI location | global |

*Note: GOOGLE_CLOUD_PROJECT can also be used instead of GCP_PROJECT_ID.*

npm install
npm run build

Add the following to your ~/.config/goose/profiles.yaml (or manage via the Goose UI):

  gemini-agent:
    cmd: node
    args:
      - /path/to/gemini-agent-mcp/build/index.js
    envs:
      GCP_PROJECT_ID: "your-project-id"
      GCP_LOCATION: "global"