"Using Google Search to Find Answers" matching MCP servers:

Enables AI assistants to perform Google searches with real, resolvable sources and transparent search terms.

Enables AI agents to search local Markdown documents using natural language, with automatic indexing and section-level retrieval.

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.

Read-only MCP server for discovering and ranking on-chain agents on Stellar mainnet via natural language search, reputation probes, and profile lookups.

An MCP server that integrates AI agents with Figma, enabling reading and programmatic modification of designs.

Enables AI agents to directly control Figma Desktop via MCP, supporting UI creation, editing, prototyping, and variable management with over 60 tools.

A Model Context Protocol server that connects to Google Cloud services, allowing users to query logs, interact with Spanner databases, and analyze Cloud Monitoring metrics through natural language interaction.

Enables AI assistants to read and modify Figma designs programmatically through the Model Context Protocol.

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.

Enables fast literal and regex search over local workspaces using a sparse n-gram index for candidate pruning, with deterministic verification against file contents.

An MCP server that enables AI assistants to perform web searches on Perplexity.ai using browser automation instead of an official API. It supports persistent authenticated sessions and returns search results along with cited sources directly to the client.

Enables agents to quickly find and edit code in a codebase with surgical precision. Find symbols, edit them everywhere with tools for reading code blocks, searching/replacing text, and making precise line-based modifications.

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.

Enables AI assistants to read, search, and traverse your entire reMarkable library, including handwritten notes via OCR.

Enables interaction with Steam: search games, get store details, reviews, prices, discounts, news, and player profiles, libraries, and achievements via the Steam Web API.

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.

Enables AI assistants to search live jobs, view full details, save and track applications in a Kanban board, set follow-up reminders, and subscribe to job alerts—no account needed for searching.

MCP server for Obsidian vaults — search, memory, link graph, 23 tools, OAuth-protected. Runs locally via Docker or remotely with Obsidian Sync + OAuth 2.1.

Provides local, offline searchable access to Roku and BrightScript development documentation via MCP tools and resources, including full-text search, sectioned reading of large docs, and background syncing from the upstream repo.

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