How does context management work?
Sessions maintain conversational state across interactions. You can add, retrieve, search, and clear context entries, and unused sessions expire automatically.
@MCP-Mirror
基本信息
Mirror of
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"ogoldberg_gemini-context-mcp-server": {
"command": "node",
"args": [
"dist/mcp-server.js"
]
}
}
}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。
An MCP server that leverages Gemini’s capabilities for context management and caching. It maximizes Gemini’s 2M token context window while providing tools for efficient reuse of large prompts and session-based conversation state.
Install via npm, configure a Gemini API key in a .env file, build with npm run build, then start with node dist/mcp-server.js. Integrate with MCP-compatible clients (Claude Desktop, Cursor, VS Code) using the included quick-setup commands or manual configuration. Use the provided MCP tools for context management and caching.
Sessions maintain conversational state across interactions. You can add, retrieve, search, and clear context entries, and unused sessions expire automatically.
The server supports creating named caches for large prompts with configurable TTL. You can generate responses from a cache, list caches, update their TTL, and delete them when no longer needed.
Node.js 18+ is required, and a Gemini API key must be provided. The server runs locally and can be integrated with any MCP-compatible client.
Quick-setup commands (`npm run install:claude`, `npm run install:cursor`, `npm run install:vscode`) configure the server automatically. Manual integration is also supported via MCP configuration files.
Sessions and caches are stored in memory and expire after a configurable timeout (default 120 minutes). Persistent storage and vector search are planned future improvements.
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