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

Provides an institutional research backend for AI assistants, with 15 tools for company, financial, funding, competitor, industry, and news intelligence, plus Markdown/PDF report generation, featuring deterministic source routing, extraction, validation, and citation generation.

Provides institutional research data retrieval, extraction, validation, and citation generation for AI assistants via the Model Context Protocol.

Enables AI assistants to perform institutional research on companies, financials, industry, news, litigation, and risk, and to generate cited markdown, HTML, or PDF reports through MCP.

Fetches YouTube video transcripts, using free captions when available and falling back to Gemini-based transcription for missing or broken captions.

Enables AI assistants to perform institutional research and due diligence by retrieving, extracting, validating, and citing data from public sources, then generating reports in markdown, HTML, or PDF.

Enables coding agents to deliver short retrieval-practice questions about what was just built, with tools for answering, viewing progress, and managing pacing, topics, mutes, and difficulty.

MCP server for overseer.nvim — gives any MCP-capable coding agent running inside Neovim (Claude Code, Codex, Gemini CLI, opencode) the same visibility and control over tasks the user has: list, run, tail, restart, stop. Agent-started dev servers land in the user's own task list instead of becoming invisible orphaned processes.

Enables any MCP-compatible LLM to perform AI-powered web research using Google's AI Mode, returning synthesized and cited answers instead of raw search results.

Local MCP server for generating image assets with Google Gemini (Nano Banana 2 / Pro). Supports transparent PNG/WebP output, exact resizing/cropping, up to 14 reference images, and Google Search grounding.

Connects LLMs to your macOS Shortcuts library, enabling interactive workflows, discovery, and management through AppleScript and CLI integration.

Gemini-powered MCP server for automated code review, analysis, and documentation.

Enables AI agents to interact with Google NotebookLM and Gemini API for document analysis, deep research, and notebook creation with enterprise-grade security including post-quantum encryption and 14 security layers.

A local-first, no-API-key MCP server that enables LLMs to search the web, fetch pages, and read documents using multiple engines and smart fallbacks.

Enables AI models to access and search offline Wikipedia and other knowledge bases stored in ZIM format files. Provides intelligent content retrieval, structured browsing, advanced search capabilities, and metadata extraction for comprehensive offline knowledge access.

Read-only MCP server for Grafana Loki: lets AI agents (Claude Code, Cursor, Copilot) discover labels, read bounded LogQL pages, count lines by label or time, and export logs — across several Loki stands

Standalone MCP server for Obsidian vaults - hybrid search (FTS5 + vector + cross-encoder reranking), images and PDFs in agent-readable form, Kanban-aware tasks (Tasks-plugin + Dataview formats), structured memory with topic recall, fine-grained read/write tools for optimal token efficiency, and link graph support. Run locally, self-host, or one-click deploy for remote access. OAuth 2.1.

Enables AI assistants to generate real images via multiple models (OpenAI, Gemini, Recraft, Seedream, Grok, Arrow) and returns usable file paths instead of base64 data.

Model Context Protocol (MCP) server for GitLab — exposes 1006 GitLab REST & GraphQL API operations as MCP tools (42 meta-tools / 57 enterprise), 24 resources, 38 prompts, and 17 completion types for AI assistants. Written in Go, single static binary, stdio and HTTP transport.

Unofficial MCP server for the messdienst24.de utility portal, providing tools to retrieve heating and hot-water consumption data, download PDF reports, and compare usage trends.

MCP server for the ReactUse library. Exposes 110+ React Hook signatures, examples, and API metadata so AI coding assistants can discover and use any hook from @reactuses/core directly.