"Using cursor-based pagination with Supabase" matching MCP servers:

A TypeScript-based MCP server for handling a simple notes system with NextJS that supports creating and summarizing text notes using MCP concepts.

Enables interactive AI chat through the Anthropic API, with document retrieval, slash commands, and extensible MCP tool integrations.

Enables natural language management of Gmail through MCP tools for searching, analyzing, summarizing, drafting, and sending emails, with AI reasoning and user confirmation for actions.

Integrates local language models (like Qwen3-8B) with MCP clients, providing tools for chat, code analysis, text generation, translation, and content summarization using your own hardware.

A Model Context Protocol server that implements a simple notes system, allowing users to create, list, and summarize text notes.

Enables Claude to read and analyze PDF documents with automatic OCR processing for scanned files. Features intelligent text extraction, caching for performance, and secure file access with search capabilities.

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.

Provides MCP-compatible AI clients with offline text analysis and rewriting tools, including statistics, extractive summaries, keywords, readability scores, case conversion, entity extraction, and diffing, all running locally without API keys or network calls.

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

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

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.

Analyzes unstructured documents in a local folder, extracting structure and key terms, and supports generating summaries via a host LLM with validated, approval-based report saving.

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.

Enables transcription, summarization, and action item extraction from audio files on your Mac using MacWhisper and Claude Desktop, all locally without any cloud APIs.