"Using SearxNG for Deep Research" matching MCP servers:

Enables production-grade web research through MCP, combining local SearXNG search with hosted fallback providers, fetch and crawl tools, summarization, and budget guardrails.

A TypeScript-based MCP server for SearXNG that allows users to create and summarize text notes using simple URIs and metadata, facilitating natural language interaction with stored content.

An MCP server that provides tools, resources, and prompts for reading, writing, and summarizing research notes stored in a local flat-file database.

Enables LLMs to search, analyze, and summarize academic research papers in real-time from arXiv, Semantic Scholar, and PubMed. Provides automatic deduplication, citation analysis, and BibTeX generation across multiple research databases.

An offline MCP server that enables research tasks such as summarizing text, extracting key points, and saving/retrieving notes via a CLI client and stdio transport.

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 clients to search YouTube, fetch video transcripts, and generate transcript-grounded research briefs using MCP tools.

Aggregates and summarizes security research from IEEE, NIST, CISA, and blogs with a live-streaming web UI.

An MCP server that adds real-time web research to Claude Desktop using Gemini 2.5 Flash with native Google Search grounding.

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.

MCP server for evidence-based bullet point summarization guidance. Validates and improves bullet lists using scientifically-validated principles from cognitive psychology and UX research.

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

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.

A FastMCP server that enables AI assistants to extract structured information from unstructured text using Google's langextract library through a secure, optimized Model Context Protocol interface.

Enables LLMs to interact with Fathom.video API for managing meeting recordings, retrieving transcripts and AI-generated summaries, searching meeting content, and accessing analytics and team data.

Integrates Vale prose linting into AI coding assistants, enabling users to check text files for style and grammar issues using Vale's powerful linting engine. Provides automated style feedback with smart configuration discovery and rich formatted results.

Enables natural language interaction with local .docx files, allowing users to find, read, search, and summarize Word documents using friendly names and location hints.

Exposes the Aporix document optimization API as an MCP tool for AI agents, enabling document compression and token/cost savings analysis.

Enables analysis of clinical trial protocols using MCP tools for document listing, entity extraction, adverse event clustering, and summarization.

Unofficial MCP server for working with Kagi without API access (you'll need to be a customer, tho). Searches and summarizes. Uses Kagi session token for easy authentication.