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

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.

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.

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.

An MCP server that provides structural codebase indexing and surgical query tools to drastically reduce token usage through symbol-level searches and transitive impact analysis. It supports multiple languages and integrates with git to help AI agents understand code dependencies and the impact of changes in sub-millisecond time.

Provides sandboxed code execution and data processing for CSVs and logs to achieve over 95% token savings. It enables secure multi-language execution and progressive tool disclosure to optimize LLM context usage.

A server that enables Claude Desktop to generate images using Google's Gemini AI models through the Model Context Protocol (MCP).

A Model Context Protocol server that enables Claude to interact with Google's Gemini AI models, allowing users to ask Gemini questions directly from Claude.

Wraps the Claude Agent SDK as MCP servers, letting you spawn multiple specialized Claude Code agents — each with its own model, tools, system prompt, and personality — from any MCP client.

Enables interaction with Google's Gemini AI models including file uploads, conversation management, and batch API processing for large-scale tasks at reduced costs. Supports multiple Gemini models with advanced features like embeddings generation and automated workflow processing.

Enables Claude Code sessions to communicate with each other, allowing discovery, messaging, and synchronous queries across sessions.

Self-improving learning engine for Claude Code. Extracts signals from sessions (corrections, successes,confusion), runs periodic reflections, and evolves behavioral frameworks through evidence. 9 MCP tools, automatichooks, local-only.

Multi-agent AI consultation framework for Claude Code via MCP — get second opinions from OpenAI, Gemini, Qwen, DeepSeek

A fire-and-poll MCP server that lets Claude Code run long background jobs without hitting tool-call timeouts.

A TypeScript server that integrates Google's Gemini Pro model with Claude Desktop through the Model Context Protocol, allowing Claude users to access Gemini's text generation capabilities.

A TypeScript MCP server that enables agents to request focused, one-shot consultations with allowlisted Gemini models, with guaranteed model provenance and no silent model changes.

A dedicated server that wraps Google's Gemini AI models in a Model Context Protocol (MCP) interface, allowing other LLMs and MCP-compatible systems to access Gemini's capabilities like content generation, function calling, chat, and file handling through standardized tools.

MCP server for orchestrating multiple Claude Code instances via tmux, enabling spawning, reading, sending, listing, and killing sessions.

Enables image generation and multi-turn editing sessions using the Gemini API within MCP-compatible environments. Users can create, modify, and configure images through natural language commands, supporting features like aspect ratio adjustments and session-based image transformations.

Enables Claude to collaborate with Gemini for code reviews, second opinions, and iterative software development. It facilitates multi-step workflows including PRD creation and code generation through an AI orchestration framework.

Enables collaboration between multiple AI models (GPT, Claude, Gemini) to work together on complex tasks, with intelligent task distribution and role-based expert assignment for code development, review, and optimization.