"How to connect to my AWS accounts" matching MCP servers:

Enables AI assistants to convert CSS-animated SVGs into videos (MP4/WebM/MKV/MOV) and animated images (aPNG/GIF) with frame-accurate rendering and transparency support.

Routes one brief to the right image model across 60+ (gpt-image-1.5, Ideogram 3, Recraft V4, Flux), validates the output, and fans out to iOS/Android/PWA/favicon/visionOS/Flutter bundles. Works without an API key via Pollinations, HF Inference, Stable Horde, or host-LLM inline SVG.

Enables LLM agents to process local videos into timestamped, citable text documents and then query them through tools for listing videos, retrieving transcripts, and fetching specific segments, all fully offline.

Turns a single image of an object into a textured 3D model (GLB with web-ready copy and six-view previews) on your own NVIDIA GPU, returning the written files and a preview. Runs locally as an MCP tool or, optionally, offloads the job to hosted GPUs with an API key.

Enables MCP clients to turn direct video URLs and chosen start/end times into ready-to-post vertical 9:16 MP4 clips with animated burned-in captions, thumbnails, and SRT files, including batch processing for multiple highlights.

MCP server for ingesting UI screenshots, Figma MCP node JSON, or hybrid Figma-plus-screenshot sources into a cross-platform design-to-code artifact pipeline.

Provides governed MCP tools for a controlled, AI-assisted asset-change pipeline, featuring natural-language requests, mandatory approvals, execution-time revalidation, and complete audit.

Enables AI agents on Windows to control Photoshop, After Effects, Illustrator, and Affinity through local MCP connectors, and to access account-based creative tools for styles, recipes, images, video, voice, and music.

Enables text-to-image generation using Zhipu AI's CogView-4 API. Supports generating images from text prompts with configurable size and quality parameters through MCP-compatible clients like Claude Desktop and Cline.

Converts local images or remote image URLs to Base64 format via the MCP protocol, enabling AI assistants to process images.

Chat raw clips into a finished cut. Ingest local media, then drive a persistent multi-turn editing thread on the Cassette agent.

Enables AI clients to generate animated videos from natural language prompts, handling scriptwriting, voiceover synthesis, and MP4 rendering.

Enables chat-driven video editing by letting an MCP host analyze raw clips and produce finished, beat-synced montages with matched music, subtitles, transitions, and picture-in-picture, all previewed as a timeline digest before rendering. It runs locally through agents such as Claude Code, Codex, Hermes, and OpenCode.

Enables users to turn raw video clips into finished, beat-synced montage cuts through natural-language chat, with the agent selecting shots, matching music, adding subtitles and transitions, and rendering the final video.

Enables an AI agent to ingest raw video clips, plan and edit a montage from natural-language prompts, and produce a rendered, beat-synced cut with matched music, subtitles, transitions, and picture-in-picture.

Enables users to turn raw clips into finished, beat-synced montage videos through natural-language chat, including shot selection, music matching, subtitles, transitions, and picture-in-picture. It lets agents analyze footage, plan and review cuts before rendering, and export final edits without a GPU or timeline editor.

Enables coding agents such as Claude Code, Codex, Hermes, and OpenCode to turn a folder of raw clips plus a plain-language brief into a finished, beat-synced montage, handling shot selection, music matching, subtitles, transitions, and rendering. Each turn returns a timeline digest and contact sheet so the cut can be reviewed before any frames are rendered.

A local MCP server that lets chat-based coding agents turn a folder of raw clips into finished, beat-synced montage videos by handling shot selection, music matching, subtitles, transitions, and rendering through natural language. It returns a timeline digest and contact sheet for approval before any frame is rendered.

Enables users to turn raw video clips into finished, beat-synced cuts through natural-language chat with compatible agents, handling shot selection, music matching, subtitles, transitions, and rendering while allowing review before export.

Enables Claude Code, Codex, Hermes, OpenCode, and other MCP hosts to turn natural-language prompts over raw video clips into finished, beat-synced montage edits with music matching, subtitles, transitions, and picture-in-picture, while returning reviewable timeline digests and contact sheets before rendering.

A local MCP server that lets an AI coding agent turn a folder of raw clips into a finished, beat-synced montage from a plain-language brief. It handles clip analysis, shot selection, timeline planning, music matching, subtitles, transitions, and rendering, returning a reviewable timeline digest and contact sheet before any frame is exported.

Enables users to turn raw video clips into finished, beat-synced montages through natural-language chat, with automated shot selection, music matching, subtitles, transitions, and picture-in-picture. It returns reviewable timelines and contact sheets before rendering on approval.

Enables users to turn folders of raw clips into finished, beat-synced montage videos through natural-language chat, handling shot selection, pacing, music matching, subtitles, transitions, and rendering. It returns a readable timeline digest and contact sheet each turn so the cut can be reviewed and approved before anything is rendered.

A local MCP server that turns plain-language chat prompts about a folder of raw clips into finished, beat-synced montage videos — handling shot selection, music matching, subtitles, transitions, and picture-in-picture, and returning a reviewable timeline digest and contact sheet before anything renders. It works from Claude Code, Codex, Hermes Agent, or OpenCode, so editing happens entirely in chat with no timeline software or GPU.

Turns natural-language requests into finished, beat-synced montage videos by analyzing raw clips, selecting shots, matching and syncing music, adding subtitles, transitions, and picture-in-picture, then rendering a final cut for review and approval.

Enables AI coding agents to turn a folder of raw clips into a finished, beat-synced montage from a single natural-language prompt, handling shot selection, pacing, music matching, subtitles, transitions, and picture-in-picture. It returns a reviewable timeline digest and contact sheet for approval before rendering the final file.

Enables users to chat with compatible AI coding agents to turn raw clips into finished, beat-synced montage videos, handling shot selection, music matching, subtitles, transitions, picture-in-picture, and rendering after user approval.

Enables users to turn raw clips into finished, beat-synced montage videos through natural-language chat with an AI coding agent, handling shot selection, music matching, subtitles, transitions, picture-in-picture, and rendering. It also lets users review a timeline digest and contact sheet before rendering.

A local MCP server that lets AI coding agents turn a folder of raw video clips into a finished montage from a single natural-language prompt, handling clip analysis, shot selection, beat-synced cuts, music matching, subtitles, transitions, and picture-in-picture. Each turn returns a reviewable timeline digest and contact sheet so nothing is rendered until the user approves the plan.

Enables users to edit raw video clips through natural-language chat in AI coding agents, turning footage into finished montage videos with beat-synced cuts, music matching, subtitles, transitions, and picture-in-picture.