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

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.

Provides structured local memory for Claude Desktop, reducing token usage by over 95% through intelligent retrieval and layered storage.

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

An autonomous AI development agent that enables full-stack coding, automated verification, RAG-powered code search, and quality assurance through MCP tools. Supports Gemini CLI, Claude Code CLI, with features like parallel verification, security scanning, and spec-driven development.

Connects any MCP client to the Google Gemini API, providing tools for text generation, chat, vision analysis, embeddings, token counting, and model listing.

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.

Gemini MCP with image, video, svg, landing page generation and search. Grounded search, deep research, image generation... Having them as tools inside Claude beats switching between browser tabs.

A persistent semantic memory system for Claude Code that provides a structured, versioned document store with semantic search and graph visualization. It acts as a memoization layer to store and retrieve research, design decisions, and codebase insights across different work sessions.

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

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.

Enables multi-turn conversations with Google Gemini AI models, supporting file and image analysis, automatic model selection, deep thinking mode, and Google Search integration through the AIStudioProxyAPI backend.

Enables creation and querying of knowledge bases using Google's Gemini API File Search feature, allowing AI applications to upload documents and retrieve information through RAG (Retrieval-Augmented Generation).

Enables AI-powered web searches using Google's Gemini 2.5 models with Google Search Grounding. Supports multiple Gemini models (Flash, Flash-Lite, Pro) with configurable thinking budget and web search capabilities.

A Model Context Protocol server that enables Claude Desktop and other MCP-compatible clients to leverage Google's Gemini AI models with features like thinking models, Google Search grounding, JSON mode, and vision support.

An automated research agent that leverages Google Gemini models and Google Search to perform deep, multi-step web research, generating sophisticated queries and producing citation-rich answers.

A server that provides access to Google Gemini AI capabilities including text generation, image analysis, YouTube video analysis, and web search functionality through the MCP protocol.

Enables querying NotebookLM with Gemini 2.5 from Cursor/Claude Code, returning answers grounded in user-provided sources without the model's internal thinking.

Enables structured team communication for Claude Code agents through Slack-like channels and direct messages. Supports project isolation, subscription management, and agent notes for sophisticated multi-agent collaboration workflows.

Enables Claude to index and retrieve context from codebases using self-hosted Milvus for semantic search, with hardened reliability and security for production use.

Enables Claude Code to search and retrieve information from its past session transcripts, including tool calls, errors, and project-specific history, via an SQLite FTS5 full-text search index.