"How to integrate with Google Meet video conferencing app" matching MCP tools:

• picsart_model_catalog

  Picsart GenAI

  Returns the Picsart AI model catalog as plain data — renders NO widget or UI. Use this when YOU (the assistant) need catalog knowledge for your own reasoning: picking a model before `picsart_generate`, answering "which models support X", or comparing options — without pushing a model-picker widget into the conversation. When the user wants to SEE or browse models visually, use `picsart_list_models` instead (it renders the Picsart Studio picker). Same filters and result shape as `picsart_list_models`, but every item is rich by default: `id`, `name`, `mode`, `inputType`, `provider`, `badges`, `description`, plus `supportedAspectRatios`/`supportedResolutions` when the model declares an enum for that param — enough to answer "which models support 16:9" without `picsart_model_params`. Do NOT use it to fetch a single model's FULL parameter schema (use `picsart_model_params`) or estimate per-call cost (use `picsart_preflight`). Inputs (all optional): `mode` (filter to image/video/audio/text — text = LLM models that return generated text), `provider` (case-insensitive substring like "flux", "kling", "google"), `acceptsImage` (true → only models that take an image input — i2i, i2v, i2t), `acceptsVideo` (true → only models that take a video input — v2v, v2a, v2t), `acceptsAudio` (true → only models that take an audio input — a2v, sts), `inputType` (exact-match escape hatch; one of t2v/i2v/v2v/a2v/t2i/i2i/t2a/v2a/tts/sts/sfx/music/t2t/i2t/v2t), `limit` (1–100, default 20), `concise` (default false; when true items carry only id/name/mode/inputType plus the ratio/resolution fields, to save tokens). inputType codes — first letter is input modality, second is output: t2i (text→image), i2i (image→image), t2v (text→video), i2v (image→video), v2v (video→video), a2v (audio→video), t2a (text→audio), v2a (video→audio), tts (text-to-speech), sts (speech-to-speech), sfx (sound effects), music (music gen), t2t/i2t/v2t (LLM text output from text/image/video input). Example: `{ mode: "audio", inputType: "music" }` returns music-generation models. Returns `{ items, total, truncated }` — `truncated` is true when more matched than were returned; refine filters or raise `limit` (max 100) to see more. Read-only; spends no credits and works without authentication.

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• publish

  uplika

  Post to social channels. Channels open today: threads, youtube. Get accountIds from select_channels — do not guess which channel the person meant. Text limits differ per channel: Threads 500 characters, YouTube 5000 UTF-8 bytes. Over the limit nothing goes out to any channel, so shorten it before calling. Images and video both work on the channels that take them, and a carousel can mix them. YouTube is different: it takes exactly one video, no images, and it needs options.youtube.title. Its description is measured in UTF-8 bytes, so Korean and Japanese cost three per character. There are three ways to get a media id, pick by where the file is: media_from_url when it already has a public https address, media_upload_link when it is on the person's own device, media_presign plus media_complete when you can PUT the bytes yourself. Then pass the media ids here. This publishes immediately on every channel except YouTube, which can be scheduled with options.youtube.publishAt while privacyStatus is private. If the user asks to schedule anywhere else, tell them uplika cannot do that yet. A YouTube video published before Google finishes reviewing this app is locked to private viewing, so say that when you report a YouTube post as done. Returns while the post is still publishing. The permalink is null at that moment. Call get_post with the returned id to see the final status and link. Pass wait: true to hold the response until it is really out — then you can tell the person it is posted instead of guessing. For a long post use threadItems instead of publish-then-reply: we keep the order and wait for each piece to land before sending the next one.

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• get_channel_transcripts

  YouTube Transcript Downloader

  Get transcripts for a YouTube channel's most recent videos (newest first) as timestamped markdown, one section per video. Use for research across a creator's recent output; for one known video use get_transcript. Read-only; requires an API key. Charges 1 credit per video that returns a transcript, including repeat calls; videos without captions are skipped free. A 10-video call typically costs up to 10 credits, so start with a small limit. Rate limit: 5 requests per 10 seconds.

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• get_playlist_transcripts

  YouTube Transcript Downloader

  Get transcripts for the videos in a YouTube playlist (in playlist order) as timestamped markdown, one section per video. Use for working through a course, series, or curated list; for one known video use get_transcript. Read-only; requires an API key. Charges 1 credit per video that returns a transcript, including repeat calls; videos without captions are skipped free. A 10-video call typically costs up to 10 credits, so start with a small limit. Rate limit: 5 requests per 10 seconds.

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• get_channel_transcripts

  YouTube Transcript Downloader

  Get transcripts for a YouTube channel's most recent videos (newest first) as timestamped markdown, one section per video. Use for research across a creator's recent output; for one known video use get_transcript. Read-only; requires an API key. Charges 1 credit per video that returns a transcript, including repeat calls; videos without captions are skipped free. A 10-video call typically costs up to 10 credits, so start with a small limit. Rate limit: 5 requests per 10 seconds.

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• get_playlist_transcripts

  YouTube Transcript Downloader

  Get transcripts for the videos in a YouTube playlist (in playlist order) as timestamped markdown, one section per video. Use for working through a course, series, or curated list; for one known video use get_transcript. Read-only; requires an API key. Charges 1 credit per video that returns a transcript, including repeat calls; videos without captions are skipped free. A 10-video call typically costs up to 10 credits, so start with a small limit. Rate limit: 5 requests per 10 seconds.

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• get_resource_usage

  Dockhold

  Show your account's compute, database-RAM, and storage pools: how much you've bought, how much is used, and how much is free, plus every app's current size. Call this before any resize tool (the allowed sizes come from its steps fields), and to explain to the user why an app ran out of memory or a deploy was refused for capacity.

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• upscaleVideo

  Ludo AI Game Assets

  Upscale a previously generated video to twice its resolution (2x). Pass the video `url` you received from `createVideo`, `createVideoFromReferences`, or `editVideo` — it must be a video you generated within the last 7 days; arbitrary external videos are not accepted. Only videos below 960x960 pixels can be upscaled (larger sources are rejected). Synchronous: the call blocks until upscaling finishes and returns the new video URL and its duration in seconds. Billed per second of video, independent of model, charged only on success. Pass an optional `request_id` to tag the result so you can locate it later via `getVideoResults`. Related tools: `createVideo` for image-to-video, `editVideo` to modify a generated video. Requires an API key (user scope). Credits: 0.2 credits per second of video.

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• viddler_videos_register

  Viddler

  Step 2 of uploading a video: after the file has been PUT to the uploadUrl, call this with the uploadId to create the video record. Returns the video (muxPlaybackId will be 'pending'). Poll viddler_videos_get until muxPlaybackId resolves — processing usually takes under a minute. If title/description are omitted, AI generates them from the video content.

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• picsart_list_models

  Picsart GenAI

  Lists Picsart AI models across ALL modes (image / video / audio / text) and renders the Picsart Studio model-picker widget so the USER can browse, compare, and pick a model visually. Each item carries `id`, `name`, `mode`, `inputType`, `supportedAspectRatios`/`supportedResolutions` (when the model declares an enum for that param) (and `provider`, `badges`, `description` when `verbose` is true). Use this when the user wants to SEE the available models or pick one themselves — especially when they have not committed to an output mode yet, or for cross-mode searches ("all flux models", "every model with image input"). To narrow to one output mode without a separate tool, pass the `mode` filter (image/video/audio/text) on this same tool. Ratio/resolution constraints ride along in `supportedAspectRatios`/`supportedResolutions`, so you rarely need `picsart_model_params` just to check whether a model supports a given aspect ratio or resolution. Do NOT use it to fetch a single model's FULL parameter schema (use `picsart_model_params`) or estimate per-call cost (use `picsart_preflight`). If you only need catalog knowledge for your own reasoning (no UI shown to the user), use `picsart_model_catalog` instead. Inputs (all optional): `mode` (filter to image/video/audio/text — text = LLM models that return generated text), `provider` (case-insensitive substring like "flux", "kling", "google"), `acceptsImage` (true → only models that take an image input — i2i, i2v, i2t), `acceptsVideo` (true → only models that take a video input — v2v, v2a, v2t), `acceptsAudio` (true → only models that take an audio input — a2v, sts), `inputType` (exact-match escape hatch; one of t2v/i2v/v2v/a2v/t2i/i2i/t2a/v2a/tts/sts/sfx/music/t2t/i2t/v2t), `limit` (1–100, default 20), `verbose` (default false; when true each item adds provider/badges/description). inputType codes — first letter is input modality, second is output: t2i (text→image), i2i (image→image), t2v (text→video), i2v (image→video), v2v (video→video), a2v (audio→video), t2a (text→audio), v2a (video→audio), tts (text-to-speech), sts (speech-to-speech), sfx (sound effects), music (music gen), t2t/i2t/v2t (LLM text output from text/image/video input). Example: `{ mode: "video", acceptsImage: true, limit: 10 }` returns image-to-video models. Returns `{ items, total, truncated }` — `truncated` is true when more matched than were returned; refine filters or raise `limit` (max 100) to see more. Read-only; spends no credits and works without authentication.

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• update_youtube_video

  Hermoso

  Edit an existing video on the connected channel: title, description, tags, and/or privacy (unlisted | public | private). THIS IS HOW YOU FLIP AN UNLISTED UPLOAD PUBLIC — post_to_youtube defaults to UNLISTED, and without this there was no way to publish it afterwards. Making a video PUBLIC puts it on the channel where anyone can find it, so show the user exactly what will change and get an explicit yes before calling with privacy:"public". Fields you omit are left untouched. Needs a connected YouTube channel.

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• regenerate_schedule

  My TV Channel

  Rebuild the channel's schedule now using the current weights. Call this after changing weights on a channel that is ALREADY live, otherwise the change will not air until the hourly cron. Throttled to one call per channel per 5 minutes; exceeding that returns 429 with a Retry-After header giving the seconds remaining. Requires the channel to meet launch requirements.

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• score_my_video

  AINSOF

  Put music on a video and hand back the finished file. Give a link to the video and a brief, and this measures the video, picks the AINSOF cue that fits its exact length and edit pace, mixes it underneath any existing dialogue at a level that keeps speech clear, and returns an MP4 the user can download and watch. Accepts a direct video URL or a Dropbox or Google Drive share link; for YouTube, Vimeo, Dailymotion or Twitch we cannot pull the file, so ask for the file itself or use get_upload_link. Pass track_id instead of a brief when the user has already chosen a cue. DIRECTING THE SCORE. A user who says what they want at each moment — "big opening, then pull back when she reads the letter, then build to the last shot" — is describing `sections`, not one brief. Pass a list of {from, to, brief} and each act gets its own cue chosen from its own words; add track_id, version or stems to an act to pin it exactly. Use `silences` for the opposite move — a moment the music stops dead. Both are snapped onto the video's real shot boundaries, so a boundary lands ON the cut. Call analyze_video first if you need the cut list to place them. To revise a score, call again with the same arguments and change only what the user asked to change — the response tells you how. Rendering takes about a minute, so the first reply is often { ok: false, error: "still_running" } — that is normal and not a failure. Call it AGAIN with the same arguments; it picks up the render already in progress rather than starting a second one. A genuine failure comes back as error "video_failed" with a reason to pass on.

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• frame_animation

  spriteship

  FREE, and NO AI AT ALL — no video model, no credits, nothing to approve. The tiles of a tileset/staged asset ARE the frames: give the tile indices in playback order (repeats allowed) and they are composited into a real spritesheet animation on that asset, exportable to every engine. This is how you animate a coin flip, a flickering torch or a chest opening WITHOUT paying for image-to-video. Try this before animate_asset whenever the motion already exists across the tiles. Returns a jobId — poll get_job.

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• save_to_drive

  Hermoso

  Save a Hermoso render — or ANY file — into the user’s connected Google Drive. Pass a Hermoso render URL as url (or urls[] for several); for a local/external file, call upload_file first and pass the url it returns. Optional folder (created if new) + name. Returns the Drive file(s) with a webViewLink. Needs Google Drive connected (Settings ▸ Connectors ▸ Google Drive — one connection covers Drive, Sheets and Docs). NOTE: Hermoso uses the drive.file scope, so it reaches ONLY the files it created plus any the user explicitly handed over with the Google file picker in the app — never their whole Drive.

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• recommend_staffing

  QueueSim

  INVERSE of simulate_mmc — given an arrival rate, service rate, and a target average wait time, returns the SMALLEST number of servers needed to meet the target. Use this when the user asks 'how many servers do I need?' / 'what staffing keeps wait under N minutes?'. The tool runs a binary search over candidate server counts (up to maxServers, default 50), invoking the simulator for each candidate. Saves Claude from iterating simulate_mmc 3-5 times by hand. If even maxServers servers can't meet the target, the recommendation is null and the response includes the achieved wait so Claude can explain that the target is infeasible at the given load. ANTI-FABRICATION: `recommendedServers` and `achievedAvgWaitMinutes` come from real DES runs. Quote them VERBATIM. Do not propose a different number you think 'feels right'; this tool already binary-searches for the minimum that meets the target. If the user asks 'what if c=N?' for a specific N, call simulate_mmc with that c.

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• integrate_overview

  mcp

  Orientation for wiring a redu.cloud capability (backups, DNS, extra storage, a managed DB, ...) INTO an app already deployed on redu, e.g. 'add a backup feature to the Supabase I deployed on redu'. Explains the pattern: mint a LEAST-PRIVILEGE scoped API key (with the user's approval via create_api_key), inject it into the app, and call the redu API from the app. Call this when a user asks to add/integrate a redu feature into a running deployment and you are unsure how.

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• whoami

  agentcard

  Show who you are operating as: the authenticated AgentCard account's email, user id, name, plan, KYC + account status, member-since date, and how this session is connected (personal login vs a third-party OAuth app connection, with the app name). Call this when the user asks "who am I" / "which account is this", or before money-moving actions when you need to confirm the account. Read-only. KYC shown here is the stored snapshot — use get_kyc_status when you need the live, provider-checked state.

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• video_to_audio

  Media Generator — Images, Videos & Audios

  Input: A muted video URL along with a textual prompt describing the desired audio. Output: We will return the video URL with the applied audio. Functionality: This tool now takes a muted video and a text prompt as input. It generates an audio track based on the provided prompt and applies this audio to the video, resulting in a video with integrated sound. Steps: 1. We will get the user_id from the request context. 2. We will validate the user's generation tokens. 3. We will call the Audio Application API with the muted video URL and the provided prompt. 4. The API will generate the audio from the prompt and merge it with the muted video, returning a JSON response with the updated video URL. 5. We will return the updated video URL to the user. INSTRUCTION FOR CLIENT MODEL: - Extract the required input parameters 'video_url' (type: string, URL) and 'prompt' (type: string, describing the desired audio) from the user's prompt. - Ignore any extraneous information in the user's input. - Pass the extracted values to this tool as 'video_url' and 'prompt'. - Example: For user input "Add dramatic orchestral music to this video https://example.com/video.mp4", extract 'video_url' as 'https://example.com/video.mp4' and 'prompt' as 'dramatic orchestral music'.

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• request_strategy_session

  TESSA Marketing & Technology

  Book a 30-minute strategy session with TESSA on Kevin Callen's calendar. Finds an open slot in the requested window (or the next 5 business days), creates a Google Calendar event with a Google Meet link, and emails the prospect the invite. If no slot is available, captures the lead and Kevin follows up manually. TESSA-only tool — directory firms use request_introduction instead. requested_window accepts ISO 8601 ranges ('2026-04-30T13:00/2026-04-30T17:00'), single dates ('2026-04-30'), or English ('tomorrow', 'next week').

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