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Gemini Terminal Agent MCP Server

@Nghiauet

代码仓库

基本信息

分类

AI 与智能体

许可证

MIT license

传输方式

stdio

作者

Nghiauet

关于 Gemini Terminal Agent MCP Server

create agent with mcp server

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

Gemini Terminal Agent MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

Gemini Terminal Agent MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

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

常见问题

1

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.

2

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.

3

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.

4

What search features are available?

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

5

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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