"Deep research on Gemini" matching MCP servers:

MCP server that runs Google Gemini Deep Research using live Chrome session cookies, enabling autonomous web research and cited report generation without an API key.

An MCP server that exposes Gemini's Deep Research Agent for comprehensive web research.

A Python-based agent that integrates research providers (OpenAI, Gemini, DR-Tulu, Open Deep Research) with Claude Code via the Model Context Protocol for automated deep research.

MCP server for AI-powered research using Gemini. Provides fast grounded web search, deep autonomous research, URL extraction, and session management.

Integrates Gemini API research capabilities (Deep Research, Quick Search, URL Analysis) into a unified MCP server, enabling comprehensive research, web search, and URL analysis through natural language.

An open-source deep research MCP server that provides multi-source web search and synthesis with citations, enabling agents to perform citation-backed research using Qwen3-30B-A3B-Thinking and other models.

Just to be clear about the final JSON: the MCP server is named herdr-inbox, and it enables Claude Code agents in herdr to ask questions asynchronously without stalling, with all open questions answered from one popup and answers routed back to the asking agent.

Enables users to create and refine a research outline, queue report generation in the background, and retrieve progress or completed Markdown reports, with automatic checkpointing so unfinished work can resume after a restart.

This is a Model Context Protocol (MCP) server adaptation of LangChain Ollama Deep Researcher. It provides the deep research capabilities as MCP tools that can be used within the model context protocol ecosystem, allowing AI assistants to perform in-depth research on topics (locally) via Ollama

Enables AI tools to access local crypto market data, run analyses, perform 66-item deep research, search RAG context, and retrieve generated reports and prompts via MCP.

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.

45-tool MCP server for video analysis, deep research, content extraction, web search, and Weaviate knowledge storage. Powered by Gemini 3.1 Pro.

Connect Google Antigravity 2, VS Code, Cursor and Claude Code to Gemini Notebooks (formerly NotebookLM, both personal and Google Cloud Enterprise). Exposes 21 MCP tools for workspace notebook binding, grounded Q&A with citations, Fast and Deep Research, bi-directional file sync, and Studio artifact generation.

A tool that helps users conduct comprehensive research on complex topics by exploring questions in depth, finding relevant sources, and generating structured, well-cited research reports.

Bridges MCP clients to the Windows ChatGPT Classic desktop app, letting them drive Think-mode deep research queries through UI automation with topic-based session reuse, optional research-prompt templates, and a tool to diagnose the app window and Think toggle state.

Enables fully local, zero-cost autonomous research by planning questions, searching and reading web pages, generating cited summaries or reports, and retaining semantic memory across sessions.

Enables Claude to work with a user's Google/Gemini subscription to generate and edit Nano Banana images, manage and continue Gemini chats, choose models and Gems, run Deep Research, and check usage limits, with output files delivered as temporary links.

Enables deep research evidence synthesis and citation verification by generating structured research graphs through the Model Context Protocol.

Enables AI agents to conduct zero-key multi-source deep research, run quick searches across DuckDuckGo, Wikipedia, and ArXiv, and cryptographically verify claims with token-compressed, citation-backed evidence.

Enables deep research tasks using a multi-agent architecture that integrates any LLM and MCP tools. Available via MCP stdio, streamable HTTP, and SSE transports.

Enables AI agents and MCP clients to run deterministic deep research consensus arbitration by parsing queries, evaluating source authority and contradictions, and returning structured JSON dossiers and telemetry.

An MCP server that provides autonomous, multi-source web research capabilities for AI agents. It delivers comprehensive, validated information through deep research tools while maintaining security and compatibility with various LLM providers.

Enables AI agents to analyze and link citations across multiple research sources, building cross-citation graphs and resolving consensus from conflicting findings. It exposes this capability as a deterministic, zero-dependency MCP server that plugs into Claude Desktop, Cursor, and other MCP-compliant clients.

Enables AI agents to perform deep research across multiple sources, arbitrating consensus while evaluating source authority and detecting contradictions. It integrates via MCP with clients like Claude Desktop and Cursor to deliver deterministic, structured research dossiers.

An agent-based tool that provides web search and advanced research capabilities including document analysis, image description, and YouTube transcript retrieval.

An MCP server that enables deep internet research through natural language, supporting stdio and HTTP/SSE modes for flexible integration.

An AI-powered deep research agent that automates the full research pipeline from web search to structured executive reports using a 4-tool pipeline (search, fetch, cluster, report).

Provides real-time web research and URL summarization capabilities using Gemini 2.5 Flash with native Google Search grounding. It enables users to perform factual searches and summarize web content directly within MCP-compatible clients like Claude Desktop.

Enables AI assistants to perform deep web research and generate comprehensive reports using a multi-agent divide and conquer approach.

Enables autonomous research workflows to construct and analyze multi-source cross-citation graphs and resolve consensus from structured outputs via MCP.