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.
README
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
- Google Cloud Project: You must have a Google Cloud project with the Vertex AI API enabled.
- Authentication: You must have gcloud CLI installed and authenticated:
gcloud auth application-default login - Permissions: Your account needs the
Vertex AI Userrole 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-previewmodel; 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
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.