"A resource for learning about video editing" matching MCP servers:

Enables AI agents to perform exact-match, transactional multi-file edits with atomic writes, dry-run diffs, and self-correcting error diagnostics that reduce token usage.

Enables developers to record feature-based development processes and turn Git changes, AI conversations, token usage, technical decisions, and debugging attempts into structured Obsidian learning reviews.

A learning-focused MCP server that demonstrates how to build arithmetic tools for AI assistants, currently featuring addition functionality with structured input/output.

A beginner-friendly repository for learning the Model Context Protocol (MCP) using FastMCP and uv, providing step-by-step setup and development workflow.

An MCP Server that provides a natural language interface to Google Cloud Resource Settings API, enabling users to view and manage settings for Google Cloud resources through conversation.

An MCP server that connects to the Resource Hub, allowing centralized configuration and management of tools and resources across different MCP environments.

Estimates physical quantum resources (qubit count, runtime) for quantum algorithms on fault-tolerant hardware through natural language queries.

A beginner-friendly MCP server built in plain Node.js/JavaScript that exposes five tools (calculator, UUID generator, read notes, get weather, password generator) to teach how the Model Context Protocol works under the hood.

Enables educational and learning tasks including flashcard generation with Anki integration, Zotero library management, Obsidian vault interaction, and mathematical expression verification with LaTeX support.

A comprehensive tutorial project that teaches Model Context Protocol (MCP) development from beginner to advanced levels, covering both server-side and client-side development.

An MCP server that generates comprehensive Learning Hour content for Technical Coaches, enabling teams to practice technical excellence through structured deliberate practice sessions.

A sovereign, AI-driven pedagogical and spaced-repetition skills development MCP server supporting progressive syllabi, Bloom's Taxonomy, and secure LMS handshakes.

A professional video format conversion tool based on MCP protocol that supports multiple formats, batch processing, and quality control for video files.

Minimal MCP server for testing client support for resources/subscribe and notifications/resources/updated, simulating an asynchronous status update.

A task manager MCP server that demonstrates core MCP concepts (resources, tools, prompts, stdio) and syncs data with a Next.js web app.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

Enables an AI agent to screen-record a live Expo app on a connected phone, auto-plan and direct the footage with captions, motion graphics, pop-outs and sound, then export a 1080p MP4. It also opens an interactive studio where users refine scenes by dragging, resizing, or typing prompts, and exposes all app_* control tools from expo-mcp-bridge in the same session.