Gemini Terminal Agent

Name: Gemini Terminal Agent
Author: Nghiauet

@Nghiauet

リポジトリ

Gemini Terminal Agent について

create agent with mcp server

#mcp-agent #gemini-terminal-agent #terminal-agent

基本情報

カテゴリ

AI とエージェント

ライセンス

MIT license

ランタイム

python

トランスポート

stdio

公開者

Nghiauet

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "mcp-agent-nghiauet": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Gemini Terminal Agent?

Gemini Terminal Agent is a terminal-based agent that uses Google’s Gemini model and integrates real‑time web search via Google Custom Search Engine. It is intended for developers and power users who want a conversational AI interface directly in their terminal.

How to use Gemini Terminal Agent?

Install Python 3.9+, clone the repository, create a virtual environment, install dependencies, and add your API keys to a .env file. Run python main.py to start the agent. Type prompts or questions, and use commands such as help, clear, and exit.

Key features of Gemini Terminal Agent

Conversational AI interface using Google’s Gemini models
Web search integration for up‑to‑date information
Conversation history maintained across turns
Advanced search options (domain filtering, exclusions, time range)
Clean, modular architecture that is easy to extend

Use cases of Gemini Terminal Agent

Ask questions and receive Gemini‑powered answers from the terminal
Perform real‑time web searches without leaving the command line
Maintain multi‑turn context for deeper technical discussions

FAQ from Gemini Terminal Agent

What is the difference between Gemini Terminal Agent and the Gemini web UI?

Gemini Terminal Agent runs locally in your terminal and adds built‑in web search capabilities, which the standard Gemini web interface does not provide.

What are the runtime dependencies?

Python 3.9 or higher, a Google Gemini API key, and a Google Custom Search Engine (CSE) API key with its corresponding CSE ID.

Where is conversation history stored?

History is kept in memory for the duration of the session. It can be cleared by typing the clear command.

What search features are available?

The agent supports both basic and advanced web search, including domain filtering, site exclusion, and time‑range options.

How do I configure the model and search settings?

All settings are managed through the .env file, where you can set the model name, maximum concurrent requests, timeouts, and cache TTL.

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