"React Query" matching MCP servers:

MCP Long Context Reader is a Python-based toolkit designed to overcome the context window limitations and high costs associated with Large Language Models (LLMs) processing extensive documents. It provides a FastMCP server with multiple, powerful strategies for an LLM agent to 'read' and query long documents without needing to load the entire text into its context window.

An MCP server that exposes tools to query Erick Wendel's talks, blog posts, and videos, supporting filters and pagination, plus prompts and resources for content discovery and summarization.

Enables complex queries over data on the DANDI Archive and provides a system for managing text notes. It features tools for note creation, resources for note access via custom URIs, and prompts for generating summaries.

Enables MCP clients to query and search curated RSS feeds covering data, AI, and cloud topics, and to generate local-LLM digests with citations, trends, and impact analysis via Ollama. It also exposes source listings and a ready-made competitive-watch prompt.

MCP server that fetches, ranks, and summarizes global news from 28 RSS sources across 12 categories, exposing 16 tools for LLMs to query technology, AI, finance, politics, and more.

Connects your Plaud voice recorder to Claude, giving access to recordings, transcripts, and AI summaries so you can query your notes via natural language.

A Model Context Protocol server that analyzes YouTube videos, enabling users to extract transcripts, generate summaries, and query video content using Gemini AI.

A TypeScript-based MCP server that interacts with Contentful's Delivery API, enabling users to create, query, and summarize text notes through natural language.

Enables AI assistants to manage Google NotebookLM notebooks, add sources from URLs, YouTube, Drive, or text, query and summarize content, and generate audio overviews, infographics, and slide decks through natural language.

Enables AI agents to query and recall your entire Gmail inbox locally, providing fast summarization and semantic search without relying on Gmail's search API.

Enables AI assistants such as Claude, ChatGPT, and Cursor to query, summarize, manage, and schedule WhatsApp conversations and related contacts, groups, labels, media, reminders, and analytics through the Model Context Protocol while processing remains local in the browser extension.

Enables AI agents and MCP clients to compress retrieved web documents against a query, pruning irrelevant noise through deterministic algorithmic scoring so downstream context stays lean. It exposes this capability over the Model Context Protocol for integration with Claude Desktop, Cursor, and similar clients.

Enables AI agents to compress retrieved web documents against a query, pruning irrelevant noise so only the most relevant context reaches the model. It runs as a zero-dependency Python MCP server that accepts a query payload and returns structured, scored output.

An AI-powered meeting assistant that combines FastAPI backend with React frontend to generate high-quality meeting summaries and provide Q&A functionality using OpenAI and Selenium.

A remote MCP server that compresses long text contexts, stores compact reusable summaries, and retrieves relevant context by title/tag/query, helping reduce token usage.