"Information about the Gemini 2.5 Pro" matching MCP servers:

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.

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

Enables AI assistants to perform real-time internet searches and get AI-powered analysis of current information through the gemini-cli tool.

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.

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 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 assistants to access and search Expo documentation with semantic search and AI-enhanced code examples and explanations using Gemini AI.

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 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 comprehensive MCP server that provides intelligent access to Perplexity AI's search and reasoning models with automatic model selection, conversation management, and project-aware storage. Supports real-time search, deep research, chat sessions, and async operations for complex queries.

Transforms static gemini-cli documentation into a queryable RAG service, enabling developers to ask questions about Gemini CLI in natural language and receive instant, accurate answers based on the official documentation directly within their workflow.

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

Leverages Google's Gemini AI with a 1M token context window for comprehensive codebase analysis, enabling intelligent code search, architecture analysis, and targeted improvement suggestions.

A Model Context Protocol server that enables LLMs to perform web searches using Google's Gemini API and return synthesized responses with citations.

An enhanced memory repository MCP service that builds and queries temporally-aware knowledge graphs from user interactions and data. Features asynchronous parallel processing, task management, broader AI model compatibility, and a comprehensive visual management interface.