"How to control my computer remotely or locally" matching MCP servers:

MCP server that converts PDF, video, web, and audio inputs into structured Markdown notes with support for checkpointing, batch processing, and Obsidian integration.

A Model Context Protocol (MCP) server that automates generating LinkedIn post drafts from YouTube videos. This server provides high-quality, editable content drafts based on YouTube video transcripts.

A note management MCP server that enables users to store, retrieve, and summarize personal notes via a custom URI scheme. It provides tools for adding content and prompts for generating brief or detailed summaries of stored information.

MCP server for aggregating and analyzing hot news from multiple platforms, with AI-powered summaries, smart filtering, and multi-channel notifications.

A TypeScript-based MCP server that enables users to manage text notes and generate summaries, showcasing key MCP concepts like resource representation and LLM integration.

This MCP server enables users to analyze YouTube videos by extracting transcripts and generating specialized content like summaries, chapter timestamps, and social media posts.

An MCP server that turns an LLM API into MCP tools, providing four LLM-powered tools (ask_llm, summarize, translate, extract_json) and running locally over stdio or remotely over HTTP.

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.

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.

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.

Fetches, parses, and summarizes ETSI telecommunications and media standards documents, enabling Claude to autonomously look up and ingest standards mid-conversation for answering questions, generating conformant code, or writing XML.

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

Analyzes YouTube videos using Google's Gemini API, allowing users to get summaries or ask questions about video content via direct URL input.

Local MCP server that enables delegating low-risk tasks like summarization or code patches to a low-cost model, with the main agent reviewing results.

A privacy-first, zero-cost AI assistant that lets you chat with your documents locally via CLI or web app, supporting search, summarization, and Q&A using your own model.

Converts subtitles or text into a single 1080×1620 infographic card (HTML+PNG) using LLM to generate content and Puppeteer for rendering.

Enables counting characters or bytes in text with options to include or exclude whitespace. Provides a simple tool for text analysis and length measurement.

Access 50+ AI-generated book summaries and chapter breakdowns directly in Claude Desktop. Search books by title, author, or ISBN, and get instant access to key insights from business, self-help, and educational books.

Provides various AI capabilities through DeepInfra's OpenAI-compatible API including image generation, text processing, embeddings, speech recognition, object detection, and classification tasks. Enables users to access multiple AI models for diverse tasks like generating images from prompts, transcribing audio, analyzing text sentiment, and performing computer vision operations.

Enables AI-generated text detection using the GPTZero API. Provides confidence scores and detailed analysis to identify whether text was written by humans or AI, with multilingual support.