"How to perform a Google search" matching MCP servers:

MCP server that integrates Google News and Google Trends, enabling AI models to fetch news, analyze search interest, calculate growth rates, and summarize articles.

Enables a production-grade multimodal Google Meet copilot that captures live captions, slides, and audio into a durable local buffer, and provides an interactive dashboard, alerting, and AI-powered meeting synthesis for agents.

Search and retrieve news articles and trending keywords from Google News and Google Trends. Summarize articles and extract keywords using optional NLP and LLM Sampling to get concise insights.

Allows you to search the web using DuckDuckGo and optionally fetch and summarize content from search results.

An MCP-based service that analyzes user search keywords to determine their intent, providing classifications, reasoning, references, and search suggestions to support SEO analysis.

A Node.js MCP server providing browser search and web page access capabilities, including Google search, intelligent web analysis, and LLM-powered summarization.

Enables semantic search over personal files using natural language, with optional AI summarization, all running locally.

Fetches category data from a Q&A service API and returns a markdown summary grouped by category.

Provides clean, bounded web content to AI by filtering HTML noise and optionally summarizing, preventing context window overflow.

Enables local analysis of unstructured documents (PDF, DOCX, PPTX, SVG, PNG) by extracting text and structure with citation anchors, and verifies summaries against source material before a human approves saving a report.

Model Context Protocol server for Archive of Our Own: search fanfiction and have an AI read and rank fics for you.

A small MCP server that gives agents rich context about a YouTube video — its transcript, jump-to-the-moment deep links, metadata, and most-replayed moments — so they can answer questions, summarize, pull quotes, or surface highlights.

science agent for literature search and summary

tooltrim reduces the tokens agents spend re-reading bloated tool results. Run it as an MCP server exposing compress and expand_tool_output, or as a gateway in front of any upstream MCP server: it re-exposes the upstream tools unchanged and shrinks each result (HTML/JSON/logs/tables) before it reaches the model, keeping the relevant content only.

Measures AI-detection risk in text and provides a line-by-line rewrite plan to lower the score.

Search and discover YouTube channels via natural language, track them, and summarize videos without transcripts using Gemini API.

MCP server for koreafilings.com — AI-summarized Korean DART (전자공시) corporate disclosures, paid per call in USDC via the x402 protocol on Base. Tools: get_pricing (free), get_disclosure_summary (0.005 USDC).

Two self-hosted MCP servers: manage a local model machine (Ollama pull/switch, LoRA training) and bridge to local Ollama/vLLM for pure language processing tasks (writing, summarizing, classifying, extraction) without giving the calling agent tools or file access.

Lets any AI agent score and simplify its own text before it reaches a human, using Flesch readability metrics and plain-language rewrites entirely on the local machine.

MCP server that searches the web, reads pages, and returns concise summaries with cited sources via the research_web and read_url tools.