Gemini Context
Provides persistent conversation history, semantic search, and API-level caching for Gemini models to optimize token usage and reduce costs.
About
The Gemini Context MCP server provides AI assistants with enhanced context management capabilities when working with Google's Gemini models. It maintains conversation history across sessions, implements semantic search for retrieving relevant context, and offers API-level caching for large prompts to optimize token usage and reduce costs. The server exposes tools for generating text, managing conversation context, creating and using context caches with configurable TTL, and searching through previous interactions. Built with TypeScript and the MCP SDK, it supports multiple client environments including Cursor, Claude Desktop, and VS Code through a flexible installation system, making it particularly valuable for applications requiring persistent context and efficient handling of large language model interactions.
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