"How to operate notes in the Memos app" matching MCP servers:

Enables managing plain-text notes on disk through MCP resources, tools, and prompts, so natural-language requests can create, read, search, delete, and summarize notes via an interactive client.

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

An MCP server for managing and persisting notes, offering CRUD operations, note summarization, and resource-based access via a note:// URI scheme.

Enables MCP-compatible clients to create, list, search, and delete notes, read all notes as markdown, and use prompts to summarize or clean up notes.

Lets users search, add, and summarize their saved entries, and expose them as context to AI clients through a local JSON-backed store.

Enables an LLM to keep a persistent scratchpad by adding and reading notes, retrieving the latest note as context, and generating summaries through MCP.

Enables creating and managing text notes through MCP resources and tools. Provides note creation capabilities and automatic summarization of all stored notes.

A simple note storage system that lets users create and summarize notes with varying detail levels using Claude.

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

Automatically extracts subtitles, captures screenshots at specified timestamps, and generates structured Obsidian markdown notes from YouTube videos using Claude AI.

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.

Lightweight MCP server for adding, reading, and summarizing sticky notes persisted in a local file.

A Python-based MCP server that allows users to create, read, and manage digital sticky notes with Claude integration for AI-powered note summarization.

A TypeScript-based MCP server that enables users to manage text notes with features like note creation and summary generation using a Model Context Protocol.

Enables AI agents to create, read, and summarize sticky notes stored in a local text file through MCP tools, resources, and prompts.

Enables AI agents and assistants to retrieve Indian news briefs synthesized from many outlets, including corroboration counts, framing comparisons, daily digests, topic alerts, and Breaking News, through public and account-authenticated tools over Streamable HTTP and OAuth.

Enables AI assistants to manage local sticky notes, allowing users to add, read, retrieve the latest note, and generate AI summaries through natural language.

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.

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

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).

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.

Youtube, readable in AI chats.

A Model Context Protocol server that distills documents from multiple sources into HTML articles and Obsidian notes, with features like key element detection, image filtering, and async task management.

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.

An MCP (Model Context Protocol) server specialized in deciphering PDF internal structures.

Model Context Protocol server exposing the bankstatementparser library as first-class agent tools for reading bank statements.

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.

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