Gemini Agent MCP Server

Gemini Agent MCP Server

An advanced MCP server that provides an agentic interface to Google's Gemini 3.1 models via Vertex AI, combining real-time Google Search, URL analysis, and Python code execution to solve complex multi-step research and data tasks.

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Gemini Agent MCP Server

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.

Features

  • 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.

Prerequisites

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

Configuration

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.

Installation & Usage

1. Build the project

npm install
npm run build

2. Integration with Goose

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"

3. Integration with Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "gemini-agent": {
      "command": "node",
      "args": ["/path/to/gemini-agent-mcp/build/index.js"],
      "env": {
        "GCP_PROJECT_ID": "your-project-id",
        "GCP_LOCATION": "global",
        "PATH": "/usr/local/bin:/usr/bin:/bin" 
      }
    }
  }
}

Tools

ask_gemini_agent

A single powerful entry point for complex queries.

  • Arguments: query (string)
  • Description: Handles research, data analysis, and technical questions by orchestrating search, web page reading, and code execution.

Limitations

  • Gemini 3.1 Preview: Uses the gemini-3-flash-preview model; availability may vary by region.
  • Python-only Code Execution: The code execution environment is restricted to standard Python libraries provided by the Gemini sandbox.
  • Stdio Transport: This server currently only supports standard I/O communication.

License

MIT

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