"Using Gemini CLI for research purposes" matching MCP servers:

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.

Provides web and local search capabilities via Brave Search combined with advanced academic paper analysis using Google's Gemini model. It allows AI assistants to perform real-time information retrieval and structured research synthesis directly through the Model Context Protocol.

A Model Context Protocol server leveraging Google's Gemini Flash 2 to analyze datasets, generate research papers, and deliver results via email.

Enables comprehensive academic research by searching and analyzing papers from PubMed, Google Scholar, ArXiv, and JSTOR. Provides full-text access, citation management, and research organization through five powerful consolidated tools.

Enables coding and research agents to run paid, cited deep research on AI infrastructure, MCP, and security topics via remote MCP tools, with query-tied excerpt packs and uncited or failed calls billed at $0.

Enables federated multi-source research by fanning out queries across web, community, and social sources, deduplicating and interleaving results, and storing a persistent corpus for cross-checking.

A read-only FastMCP server for academic research that lets agents search papers, inspect metadata, follow citation graphs, generate BibTeX, and read full texts of open-access PDFs via semantic scholar, OpenAlex, arXiv, DBLP, and Crossref.

Enables AI coding agents to run Tavily-powered web searches and asynchronous, cited research through MCP, with tools for focused search, task creation, and status retrieval.

MCP server exposing ATLAS research capabilities: live tokenized stock market data, on-chain source-of-truth reads, and published research atlases. Connects to MCP clients over stdio with no API keys required for public testnet endpoints.

An MCP server for academic literature research that integrates Scopus, CrossRef, OpenAlex, and Unpaywall to search documents, get abstracts, author profiles, citing papers, and open-access PDF links.

Research methods, workflow tools, and independent review for AI agents, packaged as a Skill, plugin, and local MCP server.

A deep-research MCP server exposing a single task-augmented tool that runs GPT-Researcher with Tavily search, Anthropic Claude, and OpenAI embeddings, streaming progress via MCP tasks and Upjack entity stream.

Enables users to conduct evidence-driven product research through MCP by importing documents, extracting JavaScript code clues, recording cited facts and inferences, tracking validation, managing research lifecycles, and exporting Markdown or JSON reports. It provides 25 MCP tools for turning source materials into traceable research findings and verification plans.

Enables AI assistants to programmatically access and manage Gemini Notebook (formerly Google NotebookLM), including creating notebooks, adding sources, querying content, generating studio content, downloading artifacts, and running batch or cross-notebook workflows through natural language.

Enables MCP clients to drive local Codex on a target Git repository: inspect repo state, start and follow up on tasks, review events and diffs, and record audit evidence for research governance.

AI-operable research workspace integrating Zotero, Obsidian, and NotebookLM. Search papers (arXiv/Semantic Scholar/PubMed/CrossRef), ingest into Zotero, sync per-paper notes to Obsidian, verify NotebookLM briefs. All three external tools optional.

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.

Enables LLM clients to access crop yield predictions from RGB imagery, topic-based PDF literature, and soil lab/moisture CSV data.

Enables evidence-grounded implementation research by searching GitHub, scoring candidate repositories, extracting source evidence, and generating planning artifacts like research and implementation checklists.