"Information or resources about video editing" matching MCP servers:

A Model Context Protocol server that transforms video downloading into a tool-based system for LLM orchestration, allowing users to download videos from 1000+ platforms with intelligent workflows and security features.

Enables AI agents to create and manage video compilations through n8n workflows with smart query optimization, quality analysis, batch processing, and trusted channel filtering for platforms like YouTube.

Hands a human's working browser session — tabs, scroll positions, video timestamps, and reasoning thread — to any MCP agent as a signed, scoped, revocable Resume Token. The resume tool lets Claude, Cursor, or any MCP client pick up exactly where the human left off instead of starting cold.

Discover and connect your agents with other agents via A2A protocol. Share resources for free or fee.

FableCut is a Premiere-style non-linear video editor that runs entirely in your browser — and exposes its whole timeline as one JSON document. Edit it by hand, from the UI, or let an AI agent (Claude Code, Claude Desktop, or anything that speaks MCP/REST) cut your video for you while you watch the timeline update live.

Search and discover AI agents, skills, prompts, bundles and MCP connectors from a curated catalog of 4500+ assets. Provides tools for searching, browsing categories, and accessing detailed information about each asset.

Provides AI assistants with real-time access to the AGNO framework documentation by enabling them to browse, search, and fetch documentation pages. This server allows users to query information about AGNO's Agents, Teams, and Workflows directly through MCP-compatible clients.

Enables selecting a saved Codex or Claude Code session from the same PC and importing its recent context into the other tool, so work can continue across clients with source and omission information.

A persistent memory implementation using a local knowledge graph that lets Claude remember information about users across conversations.

The AgentOps MCP server provides access to observability and tracing data for debugging complex AI agent runs. This adds crucial context about where the AI agent succeeds or fails.

A server that implements the Model Completion Protocol (MCP) to allow LLMs to interact with Databricks resources including clusters, jobs, notebooks, and SQL execution through natural language.

Enables deploying applications and managing cloud resources in Timeweb Cloud through natural language.

A Model Context Protocol server allowing Claude AI to interact with AWS resources through natural language, enabling users to query and manage AWS services without using the traditional AWS Console or CLI.

A ready-to-use starter implementation of the Model Context Protocol (MCP) server that enables applications to provide standardized context for LLMs with sample resources, tools, and prompts.

A Model Context Protocol server that provides Coze resources and tools for managing workspaces, bots, and conversations.

Claude, Codex, or ChatGPT builds it. Revdoku puts it online: turn an AI-generated report, dashboard, or prototype into a real website, public, password-protected, or on your own domain. Regenerate anytime; the URL never changes.

Delivers the LXAgents shared agent instruction set via MCP prompts and resources. It includes read-only tools for setting up and checking agent instructions in repositories.

A sample implementation of a Model Context Protocol server using Next.js and the Vercel MCP Adapter, allowing developers to create AI assistants with custom tools and resources.

A message bus that enables AI assistants (Claude, ChatGPT, Gemini, Perplexity) to communicate via shared channels using MCP or REST APIs.

A declarative framework that manages LLM resources, prompts, and tools through YAML configuration files. It enables LLMs to interact with external data, CLI commands, and Python functions using the Model Context Protocol.