# Slice Muse connector

From musedirectory.ai, the independent directory of Meta Muse connectors. Not affiliated with Meta.

## Slice

Turn podcasts and videos into captioned vertical clips for social media.

- Record: https://musedirectory.ai/connector/slice
- Category: Marketing & Ads
- Developer: Slice Media (https://tryslicemedia.com/agents)
- Muse status: Extra setup. Not in Muse's Connectors list yet. Muse can still use it: its page gives you a request to paste into Muse.
- Health: Working, 89ms, checked 2026-10-29T11:26:30Z
- Endpoint: https://mcp.tryslicemedia.com/mcp
- Auth: No account needed; Pricing: unknown
- Screening: Screened, no issues found (2026-10-29T11:26:30Z)
- Source: Found in the official MCP Registry (com.tryslicemedia/slice) https://registry.modelcontextprotocol.io/v0/servers?search=com.tryslicemedia%2Fslice

Slice transcribes long podcast episodes, interviews, streams and videos, finds the best moments, and renders them as captioned vertical clips ready to post. Supports MP3, M4A, WAV, OGG, FLAC and video files up to 4.5GB and 90 minutes.

Example request: "Turn my latest podcast episode into 30-second clips with captions for TikTok and Instagram Reels."

How to connect: Not in Muse's Connectors list yet, but Muse can still use it. Paste this into Muse: "Use Slice to help me. It is a free service with an MCP server at https://mcp.tryslicemedia.com/mcp. It does not need an API key. Ask me before you share anything with it." Muse asks before it shares anything with the app's site. Meta does not review apps used this way, so only use ones you trust. We tested this in the Muse app on September 24, 2026: Muse used an app's link directly this way and returned a live answer.

Tools:
- start_episode: Use this when the user wants a podcast, interview, stream or other video turned into short clips. An audio-only episode (MP3, M4A, WAV, OGG or FLAC) works too: its clips come out as captioned vertical videos drawn with an audio template. With a video or audio file attached in the
- get_episode: Use this when the user asks how an episode is going, whether it is ready, or what clips were found. Returns one status for the whole pipeline (waiting_for_upload, uploading, transcribing, finding_clips, ready or failed) and, once ready, the found clips with number, ref, title, op
- make_clips: Use this when the user picks found clips to make. Cuts each one from the episode and renders it with captions burned in, in one step. Pass the numbers or refs get_episode listed (refs in brackets are fine). Optional style, caption_size, position, hook_title, fit and background ap
- get_job: Use this when the user wants to know whether a clip is cut or rendered, or wants the finished file. Pass the job_id from make_clips or restyle_clip, or a clip_id for that clip's latest render. Returns the status, progress, a still from the clip and, when finished, a short downloa
- restyle_clip: Use this when the user wants a made clip changed and rendered again: a different caption style, bigger or smaller captions, captions moved up or down, the hook title turned on, off or reworded, or the whole video shown instead of cropped (fit, background). The change is saved on 
- list_styles: Use this when the user wants to know which caption looks they can choose from. Returns each style's id, name, a one-line description and a link to a preview picture. Pass styles to look up particular ones. Do not use to change a clip (use restyle_clip or make_clips).
- find_clips_about: Use this when the user wants clips from an episode on a particular topic or for a particular audience, e.g. "clips about creativity for artists" or "moments for young entrepreneurs". Searches the episode again for moments that fit the focus, skipping clips already found, and adds
- read_captions: Use this when the user asks what a clip says, what is on screen at a particular moment, which caption contains a word or a typo, or who said something. It is also the only way to get a caption's id, so read it first whenever a later step needs to name one caption. Narrow with at_
- transcribe_audio: Use this when the user wants the words: speech in an audio or video file turned into text, from a podcast, interview, lecture, meeting or voice note. Accepts a file the user attached (file) or a direct https link to a media file such as .mp3, .m4a, .wav or .mp4 (url). Returns the
- transcription_status: Use this when transcribe_audio returned status "processing", to check whether the transcript is finished and get its text. Pass the transcription_id it returned. Call it again after a short wait while the status is still "processing". Only answers in the conversation (or Slice ac
- email_transcript: Use this only when the user explicitly asks for a finished transcript to be emailed to them. Needs a Slice sign-in, asked for on first use, and sends the .txt, .srt and .vtt files only to the confirmed email address on that Slice account, never to another address. Each transcript

Screening checks:
- MCP handshake: pass (Answered in 89ms)
- Domain against threat feeds (Cloudflare security DNS): pass (mcp.tryslicemedia.com, tryslicemedia.com not flagged)
- Published packages against the OSV malicious-package database: n/a (No npm or PyPI package published)
- Hidden instructions or invisible characters in tool text: pass (11 tools read, nothing found)
- Inputs asking for passwords, card numbers or seed phrases: pass (None found)
- Domain and redirects: pass (Domain registered 450 days ago)
- AI review of purpose and tool behavior: pass (No concerns)