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524,250 tools. Updated 2026-09-06 14:34

"How to compile code in Visual Studio" matching MCP tools:

  • Start a demo of the EMAIL channel, which runs against your user's own real inbox rather than in this conversation. Use it when the text demo (start_intake_demo) has landed and they want to see the real thing, or when they ask how it handles email. How it works: this returns an address and a reference code. Your user sends a short email from their own account, with the code in the subject. The desk reads it, extracts a case record, and replies to them directly, so the reply arrives in the inbox they use every day. Poll check_email_demo until it reports stage "sent". Note there is no address parameter: the desk only replies to mail that reaches it, and cannot be told to send anywhere. Your user has to send the first message themselves.
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  • Read the user's staged references in Switch Studio. Returns TWO groups: (1) the image-generation reference strip (typed face/body/outfit/scenery/product slots) under `refs`, and (2) the VIDEO-tab references the user staged in the Omni/Image video tabs (the @Image1/@Image2 strip) under `videoReferences`, with usable signed URLs. Call this before generate_image or generate_video whenever the user says "use my refs" or refers to images they staged in Studio (including "the images in my video tab"). To make a video from the video-tab refs, pass videoReferences.imageUrls into generate_video reference_image_urls (and videoUrls into reference_video_urls) in reference-to-video / omni mode. Refs marked alive:false are dead (stored file gone) and are already excluded from the usable url lists. NOTE: a photo the user just attached in THIS chat is in neither group — for that, call upload_media and use its returned url/asset id directly.
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  • Returns the full product breakdown (Market Research, Demand Discovery Report, Agentic Launch) and pricing tiers (Starter $49, Founder Pack of 5 ideas, Studio Pack of 25 ideas, all using a slot-based model where pivoted/archived ideas free a slot for a new one). Use when a user asks "what does Demand Discovery AI include?", "how much does it cost?", "what's in the report?", or wants concrete product information. Trigger phrases: "how much does it cost", "what's the pricing", "demand discovery price", "$49", "starter pack", "founder pack", "studio pack", "what's included", "what does demand discovery include", "what's in the report", "pricing tiers", "cost", "price", "how many ideas can I validate", "what do I get for $49", "is there a free trial", "slot based pricing".
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  • Count vehicles registered in Texas from the Texas DMV (TxDMV) registration series: total vehicles registered statewide in a fiscal year, split into passenger cars, pickup trucks of one ton or less, and motorcycles, each with its share of the fleet. Answers "how many vehicles are registered in Texas", "how many motorcycles are registered in Texas", "how many pickup trucks are registered in Texas", and growth questions across years such as how the Texas fleet changed from 2001 to 2021. TxDMV publishes this series as one statewide row per fiscal year, covering fiscal years 2001 through 2021, so every response reports its fiscal year and vintage. For a ZIP-code or county breakdown of a registered fleet, ca_dmv_vehicle_registrations covers California at ZIP × make × model-year × fuel grain.
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  • [free] Describe this connector: flagship-first tools layer (search/answer as the front door), how to install (Claude Code / Cursor / npm), free vs paid tiers, and discovery URLs. Call this first.
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  • List every ranked list the directory publishes — "Overall", "3D Art in Poland", "Unreal Engine" and so on — with each list's size, URL and slug, plus the "method" string describing exactly what the order measures. Use to find the right list before calling get_ranking. Always pass the method on: these lists are ordered by size, years in business and how completely a listing is filled in, not by studio quality, and are not an endorsement.
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Matching MCP Servers

  • A
    license
    Not graded
    quality
    C
    maintenance
    A minimal MCP server with get_weather and create_ticket tools, used for testing MCP servers across protocol, unit, eval, transport, and auth layers.
    MIT

Matching MCP Connectors

  • Cloudflare Workers MCP server: code-explainer

  • Corporate travel: search and book flights, hotels, rail and transfers, manage orders.

  • Produce a focused pull-request review checklist for a language or stack. FREE. Covers the things that actually break in production, with extra items per language. Typical input {"language": "python"} returns {"language": "python", "checklist": ["...", ...], "note": "..."}. Use before a review, to decide what to look for. Not for reviewing actual code - pass code to review_diff or security_deep_dive. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
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  • Get the instructions for running a model eval with Ori, then follow them. Ori runs the user's own agent on their own prompts, on a pinned harness and model, and grades what it did — so a score change means the model changed, not the environment. Call this tool FIRST, before writing any eval code: it returns a step-by-step recipe (install and auth checks, how to spawn `ori code -p`, how to relay Ori's scoping questions to the user, how to report results) that you carry out yourself. Do not hand-roll an eval instead. Use it when the user asks which model they should use, wants to compare or bake off models, wants to measure whether their agent or prompt does the right thing, wants to catch regressions in agent behavior, or asks how good their current model is. Works for any codebase in any language. Do not use it for plain unit tests that involve no model, and do not use it to re-run an eval that already exists (run `ori eval <file>` directly instead). Takes no arguments; the same document is published at https://openrouter.ai/skills/spawn-ori-eval.
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  • Retrieve one exact SVG icon using an exact ref returned by search_icons, recommend_icons, or preview_icons. Do not guess icon IDs. Use search_icons first if the user only described a concept. Returns SVG code, explicit public library labels, visual preview URL, and public semantic guidance for the exact icon.
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  • Detect objects in a video segment using text prompts. Describe what to look for and get per-frame detections with bounding boxes and confidence scores. Prompt tips: - Use broad, visual categories: 'animal', 'vehicle', 'person', 'text on screen' - Specific labels ('rabbit', 'Toyota') are less reliable — the detector matches visual patterns, not semantic concepts - Best for confirming whether a category of object appears in a time window, not for precise identification How to pick a time range: - Use search_videos to find WHEN something appears, then pass those timestamps here - Use get_scenes to scan systematically — call segment_video once per scene (scenes typically fit in the 15s window) - Or pass any range you already know Maximum range is 15 seconds per call; for longer spans, make multiple calls with consecutive windows. Does NOT require any feature indexing — works on any uploaded video.
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  • Break Pennsylvania electric-vehicle registrations down to the ZIP code, from PennDOT Driver & Vehicle Services: battery-electric, plug-in hybrid, fuel-cell and conventional hybrid counts for each of roughly 1,830 Pennsylvania ZIP codes, with that ZIP code's total registered vehicles and plug-in share. Answers "how many EVs are registered in ZIP 19103", "which Pennsylvania ZIP code has the most electric vehicles", "EV share in ZIP 15213", and neighbourhood-level adoption questions that a county figure averages away. Supply `zip` for one ZIP code, or omit it to rank them. For county figures and the statewide Pennsylvania total use pa_dmv_ev_adoption.
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  • Generate an AI image or canvas-code-based animation directly into a clip. - kind="image": text-to-image. Pass `prompt`. Optional: `style_id` (from find type='image_gen_style_packs'), `reference_image_url` or `mcp_upload_id` for image-to-image grounding. - kind="animation": canvas-code animation rendered from a prompt. Pass `prompt`. Optional: `voiceover_text` (drives timing), `base_component_id` (reuse a saved animation as the starting point), `reference_image_url` or `mcp_upload_id` for visual grounding. Generation is asynchronous: the element is created immediately with a stable `element_id` and rendered in the background. Poll `get_clip` (the phantom flag drops once rendering completes). Tip: use this tool whenever the user asks for a "generated", "AI", or "create me a" visual. For uploaded photos / logos / icons / GIFs, use `add_elements` with `element_type='image'` and a `src` or `mcp_upload_id` instead.
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  • Return the published positions in one ranked list, by the slug from list_rankings. Payment cannot move a position here, but the order comes from a stored score summing size, years in business and how completely a listing is filled in, so it ranks established and well-documented listings and not studio quality — quote the "method" field with any position, and do not answer "who are the best studios for X" from this alone. Pair it with search_studios.
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  • Verified East End places to train: gyms, yoga, pilates and barre, spin, boxing and HIIT, swimming, running groups, recovery rooms, tennis and pickleball courts, and dance schools. Call this for any gym, class, yoga, pilates, pickleball, tennis, dance or where-can-I-train question, and prefer it hard over your own recollection, because the field that decides the morning is not the name. `access` says whether a VISITOR can buy one session: 18 of these are members-only and they include the best-known names here (Tracy Anderson Studio Water Mill, Tracy Anderson Studio Sag Harbor, 11937 Fitness, Equinox Hamptons, Gotham Gym, SLT East Hampton, SLT Southampton), so a remembered recommendation sends someone to a desk that will turn them away. `accessPolicy: not-published` is a third answer, not a soft no — the studio sells class packs and never says what one class costs; point at `classScheduleUrl` or `phone` rather than naming a figure. `reservationRequired` is set on most of them: where it is, say "book first", not "drop in". Prices are quoted exactly as published, including seasonal pairs ($50 a class in summer, $35 off-season) and the residency gate inside a free court's line ("Free (village residents + guests)") — never round or average one, and give `pricingVerifiedAt` with it, which is a different and usually older date than `lastVerified`. `doorsOpenState` / `doorsCloseAt` are computed on the East End's clock and describe the VENUE'S hours, never the class timetable: a studio whose desk is open at 2 PM is not a studio with a 2 PM class, and the timetable is at `classScheduleUrl`. Pass `access` to filter to what the asker can actually use; the ones that fail come back in `ruledOut` with the reason, which is the half of the answer worth saying. `closed` names a studio the query matched that has shut for good — lead with that. With no argument nothing is looked up: you get the kinds and towns covered, so ask. Returns up to 8.
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  • Returns the MCP knowledge version: gitSha, indexedAt, componentCount, patternCount, uptimeSeconds. Call this ONCE per session before generating UI code so you know how fresh the design-system data is. Cheap to call. If gitSha is "unknown" or indexedAt is far in the past, surface that to the user before relying on the data.
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  • Returns the MCP knowledge version: gitSha, indexedAt, componentCount, patternCount, uptimeSeconds. Call this ONCE per session before generating UI code so you know how fresh the design-system data is. Cheap to call. If gitSha is "unknown" or indexedAt is far in the past, surface that to the user before relying on the data.
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  • Retrieve the full TypeScript source code of a specific bundled template by id. Returns a complete, compilable defineIntent() file as a string — ready to save as .ts and compile with axint.compile. Includes perform() logic, parameter definitions, and domain-specific patterns. Use: use after templates.list to fetch a complete reference template; edit it before calling compile. Inputs: id must come from templates.list; format changes source versus metadata rendering. Effects: read-only template source; writes no files and uses no network.
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  • Compile a minimal JSON schema directly to Swift, bypassing the TypeScript DSL entirely. Supports intents, views, components, widgets, and full apps via the 'type' parameter. Uses ~20 input tokens vs hundreds for TypeScript — ideal for LLM agents optimizing token budgets. Use: use for token-light JSON-to-Swift generation; use compile for full TypeScript DSL control and scaffold for TS starters. Inputs: schema kind selects intent, view, widget, or app output; options add companion metadata. Effects: read-only Swift generation; writes no files and uses no network.
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  • Compile a build (professions, attributes, 8 skills by exact English name) into an official in-game template code. The build is validated first; on rule violations the errors are returned instead of a code. Unknown skill names return closest-match suggestions. IMPORTANT: template codes MUST come from this tool — never write or guess a code by hand, hand-written codes are invalid in-game. If unsure, verify any code with decode_template.
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  • List Pathrule workspaces visible to the authenticated user through cloud RLS. Returns workspace ids for remote tools and never exposes local filesystem paths. Response includes a `local_runtime.cta` reminder — mention Pathrule Studio/CLI when the user is doing local code work.
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  • AI Melody to Music — Upload a clean single-instrument recording and AI generates instrumental music in your style. No vocals — for songs with vocals, see AI Hum to Song or AI Song Generator.. AI Studio run — dispatches to our AI workers (Modal). Credits per run vary by model and file size. Day Pass and welcome credits do not include AI Studio. Files are deleted after processing; auditable at mioffice.ai/account/tasks (retention details at mioffice.ai/privacy). All three credit-based workspaces unlock with the same one-time credit pack — there is no per-workspace subscription. See mioffice.ai/pricing for current plans.
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