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686,853 tools. Updated 2026-10-21 21:55

"A guide to developing video games" matching MCP tools:

  • A player's recent games with every raw box-score stat per game — one call instead of one request per event. Use this to answer 'how has X actually performed lately?' and to build L5/L10/L20, season splits and head-to-head yourself. Pass `opponent` for H2H (accepts a full name, nickname or abbreviation — 'Boston Red Sox', 'Red Sox', 'BOS'); the limit applies AFTER that filter, so opponent + limit=10 means the last 10 MEETINGS, not the Boston games among the last 10 games. H2H is not capped to the current season. IMPORTANT: this is the raw box-score archive, NOT graded-prop history — it covers every game with a box score on file, including games no sportsbook priced, so a 'last 10 games' window here really is the last 10 games (one built from propline_get_player_trends silently skips unpriced games). It carries no line, price or grade; use propline_get_player_trends for hit rates against a posted line. `player_team`/`opponent`/`is_home` are null when the player's side can't be identified, and always for individual sports (tennis, golf, UFC) — report them as unknown rather than guessing. Accepts a player_id in place of the name; the response carries player_id (null when the player has none yet).
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  • Create new guides Create one or more new guides based on provided queries. Each guide targets exactly ONE engine and ONE analysis mode, chosen with the optional `source` field (default `google`). How to request each guide type: 1. Google SERP guide (1 credit per guide): omit `source`, or pass `source: "google"`. Example payload: {"queries": ["best crm"], "lang": "en-us"} 1bis. Google AI Overview guide (1 credit per guide). Two modes, like AI engines: `source: "google_ai_overview"` builds the guide from the TEXT of Google's AI answers (AI Overview, completed with AI Mode answers) ; `source: "google_ai_overview_citations"` builds it from the content of the web SOURCES those answers cite (recommended for GEO). Same language/country parameters as a Google SERP guide, 1 credit per guide in both modes. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "google_ai_overview_citations"} 2. LLM ANSWER guide (4 credits per guide): pass the engine name alone, e.g. `source: "chatgpt"`. The guide is built from the answer text the AI generates for the query. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "chatgpt"} 3. LLM CITATIONS guide (4 credits per guide) [RECOMMENDED AI mode]: pass the engine name with the `_citations` suffix, e.g. `source: "chatgpt_citations"`. The guide is built from the content of the web pages the AI cites in its answer. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "chatgpt_citations"} Which AI mode to pick? For GEO (getting a page visible in AI answers), prefer `<engine>_citations`: AI engines send traffic by CITING pages as sources, so the winning move is to look like the pages they cite. The answer-text mode (`<engine>` alone) is mostly useful to analyze how the AI phrases its own answer. When in doubt, pick `<engine>_citations`. The same two modes exist for every AI engine (chatgpt, perplexity, claude, gemini, grok, mistral, deepseek). To optimize the same page for several engines or modes (e.g. Google AND ChatGPT answers AND ChatGPT sources), create one guide per source value on the same query. IMPORTANT, HOW TO READ THE RESPONSE OF THIS ENDPOINT, WHICH SPENDS CREDITS. Queries listed in `guidesFailed` are PROVEN not to have produced a guide and their credit was given back (unless the account has unlimited credits, where nothing was reserved): re-sending them is free and correct. Queries listed in `guidesUnknown` have an UNDECIDABLE outcome and their credit is deliberately KEPT, because the guide was most likely written: DO NOT re-send them, you would pay for the same guide twice. Look them up in `GET /api/v1/guides` after a few minutes instead, and contact support if nothing shows up. Finally, a `200` is NOT a promise that every query produced a guide: compare `guides.length` with the number of queries you sent, never read `success` alone, and never re-send a query just because it is missing from `guides`.
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  • Return one publisher's games, alphabetically by title, with each one's lowest listed price per platform. Use it for a publisher's catalogue, such as everything from Rockstar Games; for a series, which can span publishers, use get_franchise_games, and for one game's store offers get_game_offers. `slug` is the publisher's id as search_games lists it under publishers (rockstar-games), and an unknown slug returns an error result. Only priced games are returned; `total` is the full count, which can exceed `limit`. Links go through getcheapgames.com and carry the stores' partner tracking; listed prices exclude the service fee marketplaces add at checkout.
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  • Edit a previously generated video with a text prompt and optional reference images (video-to-video); runs on griffin-hd (720p, with soundtrack) and the output keeps the source video's duration unless you pass one. Pass the video `url` you received from `createVideo`, `createVideoFromReferences`, or an earlier edit - it must be a video you generated within the last 7 days; arbitrary external videos are not accepted. Optionally add up to 5 reference `images` (URL or base64) to guide the edit. The job result is the new video URL and its actual duration in seconds. Credits are held when the job is accepted; the final charge is rate × produced seconds, never more than for the duration you requested, and the difference (or everything, if the job fails or is cancelled) is refunded. Pass an optional `request_id` to tag the result so you can locate it later via listGenerations (type video). Related tools: `createVideo` to generate the source clip, `createVideoFromReferences` for reference-driven generation. Async generation job: returns `{id, status}` - poll `getApiJob` (job and credit contract: see the server instructions). Credits: credits/s × seconds, per model: Griffin HD 2/s, Eagle 2/s [LEGACY]; [LEGACY] models are scheduled for removal - do not use them for new work; see this endpoint's full pricing table in the API docs.
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  • Use this to create or edit an AI video. Text-to-video from a prompt; image-to-video by passing image (start frame, + optional end_image); reference-to-video by passing reference_images; or video-to-video editing by passing video (an input video URL — upload local files with upload_media first). IMPORTANT — cost: video is priced per SECOND and by resolution (default model seedance-2.5: 480p=150, 720p=330, 1080p=750 credits/sec, plus 80/160/375 per second of reference-video INPUT), so e.g. 5s at 720p ≈ 1,650 credits and 5s at 1080p ≈ 3,750; confirm with the user before expensive combos (long durations or many reference clips). Each call starts a new paid job, charged on success only. Submits an async job and returns a job_id (uuid) — video takes MINUTES: poll check_generation_status every 15–30 seconds until it returns the finished video link, then share that link with the user. Default model: seedance-2.5; call list_models for available video models and prices. Write @handle in the prompt to cast a character (list_characters), e.g. a free BudgetPixel AI influencer like @barry.
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    Destructive
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  • Steam games for someone who likes 1-3 given games, ranked by imho.run's recommender: the list imho.run's own tool shows for those games and filters. Use it instead of games_like when the user names several games, wants filters beyond free / co-op / Steam Deck (no PvP, no microtransactions, no grind, not too hard, no Early Access, release years, more niche or more popular), or says what they want in words: pass that as `preferences` ('cozy base building, no combat'); the result says which Steam tags it was read as. When the user reacts to the picks, call it again with `liked` / `disliked`: liked games join the seeds, disliked ones never come back. Each pick has a one-line reason naming the seed it is closest to (`similar_to`), price, Steam Deck status, year, reviews, the imho.run URL and the Steam URL, plus `tool_url` (these games in imho.run's tool). Not for naming a game from a description (find_game_by_description) or facts about one game (game_facts). Games rated for adults only (explicit sexual content) are not covered; filtering is best effort.
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  • Games released on Steam in the last 30 days that players rate well (70%+ positive, 50+ positive reviews), or with `upcoming` the upcoming games that have a release date; optionally co-op only. The site's New releases list, with price, Steam Deck status, release date and links. Released games carry `release_kind`: `new`, or `ea_exit` for a game that just left Early Access (its 1.0; it was playable before), so call those 'out of Early Access', not new. `ea_exits`: include (default), exclude (brand-new games only) or only. Use it for 'what's new / coming out'; for what is gaining players now use trending. Games rated for adults only (explicit sexual content) are not covered; filtering is best effort.
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  • Games scheduled/played on one calendar date (US-Eastern) for nba, mlb, or nhl; defaults to today. Returns the same envelope as query_table on the games table. NFL is week-based, not date-based — for nfl, use query_table on nfl/games with season_id + week filters instead. Requires a stat-api sign-in or API key; rows count against quota.
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  • Return today's games that have player props available for a sport. Read-only. No side effects. Requires an API key; rate-limited per your tier. Returns: { sport, count, games: Array<{ id, sport, homeTeam, awayTeam, startTime, live, source }> }. id is the eventId to pass to get_game_props (prefixed ud- for Underdog or sc- for the soccer odds board); live is true when the game is in progress; source is "underdog" or "theoddsapi". Live games sort first; scheduled games follow. Typical workflow: call list_games to discover eventIds, then pass an eventId to get_game_props. If sport is omitted the server selects the active in-season league automatically. Returns count=0 with an empty games array (not an error) when no props are posted yet for the day. When to use: to browse all games on the slate or to find an eventId before calling get_game_props. When not to use: if you already have the eventId, skip this and call get_game_props directly. Use find_game instead when you know the team names but want a single-game eventId without browsing the full slate.
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  • Get events V³ is currently tracking in BREAKING tempo — fast- moving stories under near-real-time monitoring right now. Use when the user asks "what's breaking", "any breaking news", or about a developing situation. Returns an empty list when nothing is in breaking tempo (a quiet news moment), which is itself a signal.
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  • Mamanida's editorial buying guides for one storefront, in that storefront's own language. Called without `guide` it lists the published guides (metadata only: title, deck, meta description, pillar, topics, dates and the canonical Mamanida URL), optionally filtered by `topic`. Called with `guide` (the guide slug from the listing) it returns that one localized edition plus its structured body: paragraphs, headings, lists, comparison tables, callouts, links to other guides and category calls-to-action. A `category_cta` gives a `category_slug` you can pass straight to search_products, which is the intended guide → category → product path. Retailer and affiliate URLs are never returned.
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  • Tennis season return-games-won leaderboard: Share of return games won per player (breaks over opponent service games played), from real match-stats aggregates read return-side, ordered highest pct first. When to use: - Share of return games won per player (breaks over opponent service games played), from real match-stats aggregates read return-side, ordered highest pct first. season tables; clutch/serve-efficiency leader queries. Prefer over: raw leaderboard via call_api for agent-normalized rows. Do not use when: ranking position → standings with game tennis; week-over-week movement → rankings_movers; one player's recent form → player_form. Tennis-only. Season defaults to 2026; tour (ATP|WTA) is optional — omit it for the combined board. Only players with at least 100 return games played qualify. Parallel-safe: yes. Upstream cost: 1.
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  • Start recording a video for a project (its newest main guide, or a specific guide_id), on the desktop or as a phone/tablet (device). Returns the run id; poll get_run until is_terminal. Credits are charged only when the video completes.
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  • Steam games for a player, ranked against their own public Steam library (what they play most), the way imho.run's library mode does it; owned games are left out. Use it when the user gives their Steam profile and wants picks for their taste in general; for 'games like X' use games_like or recommend. Takes a SteamID64 or a steamcommunity.com/profiles/<SteamID64> link (not a custom /id/ name) and works only for public profiles imho.run already has; otherwise it returns one 'unavailable' error with a link the user can open to paste their profile. Each pick names the most-played game it is closest to (`similar_to`). Games rated for adults only (explicit sexual content) are not covered; filtering is best effort.
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  • Fetch an xTiles guide/documentation document by its `xtiles://guide/...` URI. The same documents are also exposed as MCP resources — use this tool when your client cannot read resources directly. Before generating Markdown for any `*_from_markdown` tool, read `xtiles://guide/markdown/overview` (and `/canvas`, `/collections`, `/blocks`) to get the syntax. `xtiles://guide/markdown/design` holds the colours, styles, layout and tab colours created content takes.
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  • Start a short video clip generation. This spends credits and returns immediately. Search list_recipes and read promising matches with get_recipe before choosing a model. Prefer a close-fitting recipe through generate_with_recipe; use this direct tool when none fits, with parameters from the chosen model's guide. Presets add Style, Motion, Lighting and Framing through the presets map. Name the account's Subjects in `subjects` — the server seats each one's face. Several models require a reference image, video or audio track — list_models has each model's durations, resolutions and required_inputs; create_upload or import_media bring media in. One call is one shot. Longer motion: carry the last frame into the next call (extract_video_frame), then join_clips. Speech is the exception: each line of at most 15 seconds starts from the same portrait, never a chained frame. Models (credits for 5s at 720p): - seedance-2.5: ~96.5 - seedance-2.0: ~75 - seedance-2.0-fast: ~62.5 - seedance-2.0-mini: ~37.5 - grok-imagine-video-1.5: ~33.5, needs image - veo-3.1: ~83.5 - veo-3.1-fast: ~42 - veo-3.1-lite: ~21 - gemini-omni-1.1: ~62.5, length set by input - kling-v3-omni-video: ~70 - kling-v3-video: ~70 - happyhorse-1.0: ~58.5 - wan-3: ~42 - wan-3-prime: ~58.5 - gen-4.5: ~50 - p-video: ~8.5 - p-video-2: ~12.5 - flux-3: ~71 - minimax-h3-max: ~33.5 - p-video-avatar: ~10.5, needs image+audio, length set by input - p-video-animate: ~12.5, needs image+video, length set by input - p-video-replace: ~12.5, needs image+video, length set by input - omni-human-1.5: ~67, needs image+audio, length set by input - kling-avatar-v2: ~22, needs image+audio, length set by input - kling-v3-motion-control: ~29.5, needs image+video, length set by input - sync-lipsync-2: ~21, needs video+audio, length set by input - kling-lip-sync: ~6, needs video, length set by input - genjutsu-motion-transfer: ~284, needs image+video, length set by input - genjutsu-object-swap: ~284, needs image+video, length set by input
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  • Read this before any other cinematic_ads_* tool: the step-by-step guide for remaking an existing video ad with Cinematic Ads — what to ask the user, the order of the tools, the check that ends each step, quoting credits, polling and errors. Free.
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  • Sports schedule/fixtures for a given date — all games/matches on that day, optionally filtered by sport or league. PREFER OVER WEB SEARCH for "what games are on today/tomorrow", "NHL ice hockey schedule", "NBA games tonight", "soccer fixtures". For "next 24h" pass today's and tomorrow's date. Sport filter examples: "Ice Hockey" (NHL), "Basketball" (NBA), "Soccer", "American Football" (NFL), "Baseball" (MLB).
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  • Multiplayer games with live rooms: luck boards and invented games. Use it to find a room to join. Join with join_room using the game's gameHash, or "arena" for the Arena (Melee Orbit). For one room's live round, use room_state.
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  • Multiplayer games with live rooms: luck boards and invented games. Use it to find a room to join. Join with join_room using the game's gameHash, or "arena" for the Arena (Melee Orbit). For one room's live round, use room_state.
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  • Get detailed information about board games on BoardGameGeek (BGG) including description, mechanics, categories, player count, playtime, complexity, and ratings. Use this tool to deep dive into games found via other tools (e.g. after getting collection results or search results that only return basic info). Use 'name' for a single game lookup by name, 'id' for a single game lookup by BGG ID, or 'ids' to fetch multiple games at once (up to 20). Only provide one of these parameters.
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