"Aufgaben von Claude zu Gemini zuweisen, um Token zu sparen" matching MCP servers:

An MCP server that provides access to Google Gemini models via Vertex AI, enabling text generation, multi-turn chat, image/video generation, and frontend design through Claude Code.

Enables Claude Code to offload routine code generation and text processing tasks to a local Ollama LLM, saving Cloud API tokens and costs with automatic model selection and security features.

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

Enables Claude Code to call Gemini models through an OpenAI-compatible API, providing tools for deep analysis, brainstorming, code review, and general queries using Gemini's capabilities.

A lightweight server that connects Claude Code with Google's Gemini AI models, allowing developers to leverage Gemini's massive context window (1M+ tokens) for code analysis without leaving their coding environment.

An MCP server that bypasses Claude's context by routing file processing to local or cloud AI, saving token costs. It reads files from disk and returns distilled results without Claude seeing the raw content.

Enables seamless real-time collaboration between Claude Code and the Gemini CLI for discussing ideas and refining solutions. It provides tools to initiate collaborative sessions, consult Gemini with context preservation, and access conversation history.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

A private MCP server that lets Claude generate images using Google Gemini/Imagen, exposing a generate_image tool.

Bridges Claude Code and Google's Gemini AI models to enable AI-to-AI collaboration for code reviews, brainstorming, and direct questions.

MCP server for estimating LLM token consumption and costs from project documents, code, and materials. Provides 8 tools including project budget planning, token/cost estimation, GitHub repo analysis, and pricing refresh.

A local MCP proxy that strips web pages to clean text, reducing token usage for AI agents by up to 99.6%.

Claude Code token usage and cost visibility for MCP-capable agents.

An MCP server that lets Claude query Google's Gemini CLI as a sub-agent. Get second opinions, verify information, and cross-reference answers between AI models.

High-performance Model Context Protocol (MCP) server connecting Claude Code and AI agents to Google Gemini 3.8 Flash, Gemini 3.1 Pro, reasoning effort, and image generation.

MCP server that reduces token consumption in AI coding assistants by up to 90% via structural reads, PreToolUse hooks, and tp-\* subagents.

Enables image generation and transformation using Gemini API, returning file paths instead of base64 data to avoid token limit issues in Claude Code.

MCP plugin that alerts you when AI token usage is wasteful. Fires warnings, errors, and alerts on large outputs, verbose logs, and repetitive history, auto-suppressing noise to keep your context lean.

A fully offline MCP server for token estimation, prompt compression, model routing, and semantic caching to optimize LLM usage costs and efficiency.

Token-safe code search for AI agents: queries the language-server index (clangd / Roslyn / tsserver / pyright) instead of grep and returns a token-capped file:line list — ~20x fewer tokens. Symbol-level editing + a grep→index rewrite hook. Local-only, no IDE.