mcp server
Recao
Rank a competitor's EU App Store ads by longevity. From Apple's official Ad Repository.
Description as published by the maintainer. Source
- version 1.0.0
- active
active — Most recent push to the repository was 2026-07-12.
What this server can do
17 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.
assemble_status(job_id)- Check an assemble_video job by its job_id. Returns the status (processing, done, or error). When done, returns the final MP4 url, the aspect, clip count, total duration, and the booked cost in EUR. When it errored, returns the reason. Only jobs on your own account are visible. Required: job_id.
assemble_video(clips, intro, outro, aspect)- Stitch rendered scene clips into one ad-ready MP4 with burned-in subtitles and crossfades. Pass 1 to 6 clips in order, each with its mp4 url, its duration in seconds (3 to 12), and an optional subtitle line to burn over that clip. Every clip is scaled and padded to the chosen aspect (9:16 default 1080x1920, 1:1 1080x1080, or 16:9 1920x1080). Optional intro and outro title cards: pass intro/outro as { text, duration_s? } to bookend the ad with a centred title card (1 to 5 seconds, default 2) that crossfades into the video; cards do not count toward the 6-clip limit. Assembly is our compute, so it carries a small flat fee (about 0.12 EUR), booked only when the file is produced, against your trust cap. Runs in the background over up to a couple of minutes and returns a job_id: poll assemble_status with it to get the finished MP4 url. Feed it the clips from clips_status (map each to url, duration_s, subtitle). Paid plans only. Required: clips.
clips_status(job_id)- Check a generate_clips render job by its job_id. Returns the status (processing, done, or error). When done, returns the finished clip URLs, the model used, and the booked cost in EUR. When it errored, returns the reason. Only jobs on your own account are visible. Required: job_id.
generate_avatar(count, model, persona_brief)- Generate a UGC persona: your agent passes a persona brief (physical look plus vibe of one invented creator), and we return stills of that invented person plus an avatar_id. The persona brief anchors the same character in generate_clips takes, and the stills are the customer's reference artifact for the creative. Ask for up to 3; the default model returns a single strong base still, imagen and flux return the full set. Metered per generation; the price is shown in the response. Paid plans only. Required: persona_brief.
generate_clips(model, aspect, scenes, confirm, persona, avatar_id, reference_image_urls)- Render UGC video scenes as ad-ready clips, metered per second of video (the estimate shows the exact price before anything renders). Pass 3 to 6 scenes (5 to 8 seconds each, one action per scene, spoken lines at most 20 words; empty spoken_line for silent characters). Consecutive scenes pack into single TAKES of up to 15 seconds, one generation each. HOW CHARACTER IDENTITY WORKS, read carefully: all characters are described in TEXT (avatar_id resolves to its persona brief; or write the persona field yourself, covering one character or a whole ensemble). The video model rejects every image that contains a person, so no photo can anchor a face. Text keeps a character IDENTICAL only WITHIN a take; ACROSS takes it preserves the look and styling but the exact face can drift, and neither avatar_id nor persona prevents that. Structure your script so scenes where the same character must be recognizably identical sit adjacent and fit one take (15s or less); treat cross-take appearances as different shots of a matching character, and review the result. reference_image_urls (up to 9 https images) keeps real products or props on-model in every take; these images must contain no people. Without confirm, it validates the contract and returns the per-scene price estimate in EUR, and makes nothing. With confirm=true it starts the metered render and returns a job_id: rendering runs in the background over a few minutes, so poll clips_status with that id to get per-scene clip URLs plus the uncut takes. Paid plans only. Required: scenes.
get_ad_details(adId, datePreset)- Get full details and locale/creative variations for one specific ad (use adId from get_competitor_ads). Shows every language variant, creative asset URLs, and icon variations. Useful to see how a competitor localizes a winning ad. Required: adId.
get_competitor_ads(id, type, countries, datePreset)- Get all Apple App Store ads a competitor has run (EU storefronts, up to 1 year back), with creative copy, placements, formats, and an inferred winner analysis: ads sorted by how long they've been running (longevity = the advertiser keeps paying = likely converting). Source: official Apple Ad Repository (DSA transparency data). Required: id.
get_playbook(slug)- Get a Recao GTM playbook: the go-to-market moves a solo app founder's agent runs, wired to the competitor data tools. Start with 'the-roadmap' (diagnoses the founder's stage and its binding constraint, then routes you to the right playbook). Call with no slug to list all playbooks.
memory_index- List this account's company memory, one line per entry (name + description), newest first. Traverse index-first: scan this, then memory_recall(name) for full bodies. Memory accrues automatically from your competitor scans (exhaust) and from your own memory_note writes.
memory_note(body, name, description)- Write (or update) a memory entry on this account: decisions, campaign outcomes, learnings. Use a short kebab-case name and a one-line description (that's the index line); details go in body. Your future sessions and Recao's weekly reports read this. Required: name, description, body.
memory_recall(name)- Read one memory entry's full body by name (get names from memory_index). Required: name.
roadmap_status- Where the founder's agent starts its go-to-market work: diagnose which stage of the Recao Roadmap this account is in (S0 pre-launch to S4 scale), the binding constraint, and the playbook to run. Reads your scans and memory. Sharpen it: write a memory_note named 'company-stage' with your MRR band and funnel numbers, and this tool will use it.
search_app_advertiser(name, types)- Search the Apple Ad Repository for apps or developers advertising on the EU App Store. Returns ids to use with get_competitor_ads. Start here with your competitor's app name. Required: name.
sign_up(email, app_name)- Request a free Recao account for your human. This does NOT create an active account: it registers a PENDING one and emails your human an activation link; nothing works and no terms are accepted until they click it (the human accepts the terms at activation, not you). The API key in the response stays inert until then. Consent stays with the human, so calling this is a request, not a decision made for them: in an interactive session their approval of this tool call is the go-ahead; if you run autonomously, surface this step to your human instead of calling it. After activation, reconnect with header `Authorization: Bearer <key>`. Required: email.
upgrade(plan)- Get the checkout link to upgrade this account to a paid plan (Indie €29/mo: 10 competitors + weekly auto-reports; Pro €79/mo: 25 competitors, new channels first, full API). Payment happens in the browser. Hand the link to the human. Required: plan.
usage- Show this account's metered generation spend this period and its billing position: the usage cap, what has accrued toward it, and whether generation is waiting on a payment. Use it to report costs back to your human.
whoami- Show the authenticated account (plan, email, verification state), or confirm you're anonymous.
Last successful function declaration observed on . Source: https://recao.app/api/mcp. We list what the server declared; we do not call any of these functions.
Endpoint status observed on . Source: https://recao.app/api/mcp.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| GitHub stars | 0 | Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. | cumulative, all time | GitHub | |
| Last commit | 2026-07-12 | Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. | point in time | GitHub | |
| Open issues | 0 | Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. | as of fetch | GitHub | |
| Latest published version | 1.0.0 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-07-12 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| License | MIT | Licence GitHub detected in the repository. Detection can be wrong; the LICENSE file is authoritative. | as of fetch | GitHub | |
| First listed in the MCP Registry | 2026-07-12 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| repository status | active | The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. | as of fetch | GitHub | |
| mcp tools declared | 17 tools | Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. | as of probe | recao.app | |
| mcp endpoint status | ok | The server listed 17 functions when asked. | as of probe | recao.app |
Where to get it
This record as data
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GET /api/v1/entries/mcp_server.json