MCP Gemini Server

@MCP-Mirror

代码仓库

基本信息

分类

AI 与智能体

传输方式

stdio

作者

MCP-Mirror

关于 MCP Gemini Server

Mirror of

#mcp-gemini#mcp-server #google-gemini

MCP Gemini 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": {
    "bsmi021_mcp-gemini-server": {
      "command": "npx",
      "args": [
        "-y",
        "@smithery/cli",
        "install",
        "@bsmi021/mcp-gemini-server",
        "--client",
        "claude"
      ]
    }
  }
}

MCP Gemini 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。

点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。

概览

What is MCP Gemini Server?

This server wraps the @google/genai SDK, exposing Google Gemini model capabilities as standard MCP tools. It allows other LLMs (like Cline) or MCP-compatible systems to leverage Gemini’s text generation, function calling, chat, file handling, and caching features.

How to use MCP Gemini Server?

Install via Smithery (npx -y @smithery/cli install @bsmi021/mcp-gemini-server) or manually (clone, npm install, npm run build). Configure your MCP client’s settings with the server’s path and required environment variables (GOOGLE_GEMINI_API_KEY, optionally GOOGLE_GEMINI_MODEL). Restart the client after configuration.

Key features of MCP Gemini Server

Standard and streaming text generation (gemini_generateContent, gemini_generateContentStream)
Function calling that lets Gemini request client-defined functions
Stateful chat sessions with history management
File upload, list, retrieve, and delete operations
Cache content creation, listing, retrieval, update, and deletion

Use cases of MCP Gemini Server

Integrate Gemini text generation into MCP-compatible assistants (e.g., Cline)
Enable function calling workflows where Gemini invokes external tools
Build conversational agents that maintain context across multiple turns
Upload and manage files (images, documents) for multimodal prompts
Optimize repeated prompt patterns with server-side content caching

常见问题

What runtime is required?

Node.js version 18 or later.

Where do I get an API key?

An API key from Google AI Studio ([https://aistudio.google.com/app/apikey](https://aistudio.google.com/app/apikey)).

Can I use Vertex AI authentication?

No. The server only supports Google AI Studio API keys; file handling and caching features are not compatible with Vertex AI credentials.

How do I set a default Gemini model?

Set the `GOOGLE_GEMINI_MODEL` environment variable (e.g., `gemini-1.5-flash`). If not set, the `modelName` parameter becomes required on applicable tool calls.

What error types does the server return?

Errors are returned as `McpError` objects with an error code (`InvalidParams`, `InternalError`, etc.), a message, and optional details for troubleshooting (e.g., safety block reasons).

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