"How to Capture Screenshots from YouTube Videos" matching MCP servers:

Enables MCP-capable agents to add, search, edit, archive, and delete locally stored notes over streamable HTTP without using the web UI.

Builds a searchable knowledge base from YouTube video transcripts with hybrid semantic and keyword search. Allows LLM assistants to search, organize, and retrieve timestamped information from videos you've watched.

Transforms YouTube into a queryable knowledge source with search, video details, transcript analysis, and AI-powered tools for summaries, learning paths, and knowledge graphs. Features quota-aware API access with caching and optional OpenAI/Anthropic integration for advanced content analysis.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Turn Obsidian notes into agent-ready context, preview-only plans, and safe repo handoffs.

Captures and retrieves Markdown records for a personal recording system, enabling journaling, input tracking, search, and date-range review.

MCP server that connects AI agents to Google NotebookLM, enabling natural language interaction with notebooks, including Q&A, source ingestion, and audio overview generation.

Enables local-first knowledge management for Codex, providing tools for guided discussions, contextual recall, review, and daily topics.

Builds a searchable memory bank from persona-specific PDF content and exposes it as an MCP tool for querying.

Metis gives AI agents expert know-how that named reviewers have approved, and only where its recorded conditions match the situation. High-risk situations go to a person. When an agent sees practice depart from procedure, it can send the expert one short question. Every retrieval is recorded on a hash-linked evidence chain.

Self-improving, verifiable memory for AI coding agents. Learns how you work, stops repeating mistakes, models each project, recalls the right lesson at the right moment. Every memory is signed and tamper-evident. Local-first.

Semantic memory for AI builders: capture the tacit engineering know-how that never reaches your docs, recall it the moment it applies. Built in Rust on Postgres and pgvector.

Turn any YouTube video, article, PDF, or image into a reusable Claude Code skill — without leaving your editor.

Lets users manage master data through natural-language conversations with AI agents, enabling schema creation, record capture, validation, search, and query answering via 16 MCP tools backed by local JSON storage.

Enables teams to capture and distill knowledge from sessions, meetings, and feeds into a searchable, vector-embedded graph, then retrieve or synthesize it conversationally via semantic search and citations.

MCP server for sharing, searching, and pulling AI coding-agent sessions (Claude Code and Codex) directly from the agent, with automatic capture and link-based sharing.

Enables coding agents to use an Obsidian vault as long-term memory, with search, reading, and writing of notes, plus automatic capture of learnings that are propagated to MOCs, daily notes, and the knowledge index with git commits.

Local-first MCP server that captures web URLs (X, Reddit, YouTube, Wikipedia, articles) as typed data + Markdown into a self-hosted capture/store/recall substrate, with offline semantic recall. Six tools over a local khiipd daemon; run khiipd serve first.

Public MCP wrapper for SubDownload.Fetch YouTube transcripts, search videos, browse channels and playlists — instant YouTube data for your AI workflow.

Local-first memory layer for AI coding agents — Markdown as source of truth, MCP server + CLI, human-reviewed capture, team knowledge via git PRs

Shared, code-grounded memory for developers and their coding agents. Capture a learning once and the whole team plus every agent recalls it; memory is grounded in your code and stored as git-tracked JSON reviewed in PRs, with citations validated on write and stale memory withheld from recall. Works with any MCP client.

Technical Preview: runtime 0.43.4; Glama release label 0.43.6. Local-first memory for decisions, alternatives, attempts, outcomes and sources. Credential-free MCP: 20 Workflow / 16 compact / 35 full tools. Separate Windows Codex wrapper adds automatic capture and eventual provider-assisted extraction in enrolled projects with explicit sharing. Glama serves MCP; it does not capture local sessions.

Five tiny, single-purpose MCP servers for AI agents — arXiv search, YouTube transcripts, web-to-Markdown, market quotes & FX, and a persistent memory vault. No API keys, no bloat.

Enables agents to check and retrieve concept-structured YouTube video summaries from the oratilo library via lookup and full-text search tools, avoiding redundant summarization work.

Persistent knowledge-base MCP server. Semantic search with source citations over saved YouTube videos, podcasts, articles and PDFs — one endpoint for every MCP-capable AI client.

Enables personal knowledge management through Claude Desktop, allowing users to capture thoughts, connect ideas, and reflect on thinking changes via natural conversation.

MCP server that ingests YouTube videos and podcasts, making them searchable with timestamps and deep links to exact moments.

A minimalist and elegant Model Context Protocol (MCP) server for fast context memo capture, keyword search, dynamic resource digests, and AI prompt workflows.

Helps capture professional achievements using the STAR method through iterative interviews. Generates period summaries and performance review self-assessments.

Local MCP server that turns Mark Builds Brands' YouTube knowledge into an AI coaching assistant for ecommerce and Facebook Ads.