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Upscale, stabilize, denoise and raise the frame rate of videos locally on your NVIDIA GPU
AI Video Enhancer Studio is an MCP server entry in ChatHome Skills, sourced from Official MCP Registry and scored 78/100. As a Model Context Protocol server, it exposes tools that MCP-compatible LLM clients such as Claude, Cursor, and Copilot can call directly, extending an agent's reach beyond its built-in capabilities. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding AI Video Enhancer Studio to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
npx -y @contentasoft/ai-video-enhancer-mcp@1.0.2Review the upstream source before running this command.
{
"_meta": {
"io.modelcontextprotocol.registry/official": {
"status": "active",
"isLatest": true,
"updatedAt": "2026-10-05T04:43:07.513535Z",
"publishedAt": "2026-10-05T04:43:07.513535Z",
"statusChangedAt": "2026-10-05T04:43:07.513535Z"
}
},
"server": {
"name": "com.contenta-software/ai-video-enhancer",
"title": "AI Video Enhancer Studio",
"$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
"version": "1.0.2",
"packages": [
{
"version": "1.0.2",
"transport": {
"type": "stdio"
},
"identifier": "@contentasoft/ai-video-enhancer-mcp",
"registryType": "npm"
}
],
"repository": {
"url": "https://github.com/contentasoftware/mcp-launcher",
"source": "github",
"subfolder": "packages/ai-video-enhancer-mcp"
},
"websiteUrl": "https://www.contenta-software.com/aivideoenhancer/",
"description": "Upscale, stabilize, denoise and raise the frame rate of videos locally on your NVIDIA GPU"
}
}