Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@com.losercoreplaylist/creative-tools Prepare a melancholy three-song video draft with captions and a workspace link."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Public integration tools for Losercore Playlist: starter-track discovery, original scene prompts and editable playlist-video drafts. The browser workspace supports free local editing with your own audio and text/LRC.
Streamable HTTP: https://losercoreplaylist.com/mcp
Authentication: none. No API keys or environment variables.
claude mcp add --transport http losercore-playlist https://losercoreplaylist.com/mcpFor other clients, add the URL as a remote Streamable HTTP MCP server. Setup and feature guide.
Official MCP Registry record: com.losercoreplaylist/creative-tools v1.0.0. server.json describes this existing remote service; it is not an npm package manifest.
Related MCP server: Sonicmatch
npx skills add nullurl/losercore-agent-tools --skill losercore-playlistClawHub listing · Download Skill ZIP
Read the skill first. It contains instructions, public reference links and a dependency-free Node.js request helper. It supports agents implementing the SKILL.md format, including Codex and Claude Code. The skill does not automatically connect an MCP server; use the connection above or its bundled helper.
Try: “Prepare a melancholy three-song Losercore playlist-video draft in Chinese. Use original captions and give me the JSON to import into the free video workspace.”
Tool | Inputs | Result |
| query, limit | Song/artist/mood metadata from four starter tracks, dated 2026-10-21 |
| beanie-loser or turn-on-the-playlist | Original adult-character visual scene prompt |
| 1–12 title/artist pairs; optional three original captions and en/zh/id language | Editable JSON draft and browser workspace URL |
Two resources expose starter metadata and workspace guidance; plan_playlist_video supplies a mood-based planning prompt. Discover current input schemas through tools/list. A live Spotify catalogue, music files and song lyrics are not provided.
Call prepare_video_project with song titles/artists and three short original captions, or use its defaults.
Save only the returned project object as the returned filename.
Open workspaceUrl and use Import AI project to load the file.
Add audio/text or LRC you have permission to publish, review timing, and export locally. Save your work before refreshing. MP4 codec support depends on the browser; Chrome/Edge is recommended.
Preparing a draft is free and costs 0 credits. It does not render an MP4 or submit a cloud AI job.
This repository includes a runnable bridge for MCP clients restricted to stdio. It forwards tools, resources and prompts to the same hosted public service; it is not an offline copy of the website backend.
git clone https://github.com/nullurl/losercore-agent-tools.git
cd losercore-agent-tools
npm ci --ignore-scripts
npm startNode.js 22.12+ is required. Configure your stdio client with command: "node" and args: ["/absolute/path/losercore-agent-tools/src/stdio.mjs"]. No npm package has been published under this name. Network access to losercoreplaylist.com is required. A Dockerfile is included for directory inspection and stdio execution.
llms.txt links to interlinked Markdown references for features, pricing, data scope, site structure and MCP. llms-full.txt combines the reference material.
Local editing is free. Optional cloud AI is separate and uses credits. Fetch the live pricing reference for current amounts and purchase availability rather than assuming all displayed plans are on sale. Neither this skill nor this MCP exposes account balances, purchases, private media or cloud-generation credentials.
Tool inputs pass through your chosen agent host and the Losercore service. The bridge/helper sends no API keys, local media or account cookies. Supplied titles/captions are processed for the request; this integration does not save them as a website project. Do not send secrets or private media. This public repository contains integration tooling only; it does not contain the private website source or deployment credentials.
Privacy · Terms · Support: joyforjoker43@gmail.com
The skill directory is MIT-0 (matching ClawHub publication terms); the bridge and other root files are MIT. These licenses do not grant rights to third-party recordings, lyrics, brands, or the separately hosted website implementation.
npm test
node skills/losercore-playlist/scripts/mcp-call.mjs tools/listThe smoke test uses the official MCP SDK to connect through the local stdio bridge, lists tools/resources/prompts, prepares an original draft and confirms invalid inputs fail. It calls only the public free endpoint.
Return one of two original adult-character scene prompts for a PS2-inspired concept. This prepares text only and never submits or charges an AI generation request.
Inputs: template (required).
Prepare a free local-workspace JSON draft from 1–12 song/artist title cards and three original captions. Save the project field as JSON, then import it on the linked workspace. It does not render a video, fetch audio or provide song lyrics.
Inputs: tracks (required), captions, language.
Search four starter tracks by song, artist or mood. This is a dated starter selection, not a live or complete Spotify catalogue. Returns metadata and listening links only.
Inputs: limit, query.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
Scored across 3 tools
Each tool maps to a distinct step: searching the starter track list, fetching a scene-prompt template, and assembling a JSON project draft. There is mild thematic overlap between search_playlist and prepare_video_project since both concern songs, but the descriptions make clear that one returns metadata and the other builds a file draft.
All three tools follow a consistent snake_case verb_noun convention (search_playlist, get_creation_template, prepare_video_project). Verb choices accurately reflect each action's read-versus-prepare semantics.
Three tools is minimal but matches a narrowly scoped creative-asset helper with a clear three-step pipeline. It is not thin in the problematic sense, since each tool covers a genuinely different stage of the workflow.
The surface is read-and-prepare only: there is no way to retrieve, list, or revise a previously prepared project draft, and no tool exposes the linked workspace or template list. Rendering, audio fetching, and lyric lookup are explicitly out of scope, so the remaining gaps are structural rather than broken.
Video knowledge base for agents: search your library's transcripts, keyframes and on-screen text.
YouTube transcripts, search, channel/playlist listings and upload tracking for AI agents.
Music industry tools for AI agents: artist research, catalogs, release plans and content.
Reproducible, IP-clean assets for agents: seven engines, from print designs to voice and video.
