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459,366 tools. Updated 2026-08-17 07:08

"Pictures of Thomas Pesquet" matching MCP tools:

  • Display the user's images inline — one or many. Users speak plainly and will NOT know asset ids; never ask for one, resolve it yourself. For "show me" or "show me my last image" call with NO arguments (shows the most recent image). For "show me my last 4 images / my last 10 pictures" pass count=N (returns a clean grid, up to 12). For a specific known image pass assetId. Renders a branded SwitchApp media card with a Download action per result; do not just print URLs. (Videos are not shown here — use list_my_videos and return the newest finished video's view_url, which plays.)
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  • Turn a TOPIC into a finished narrated explainer video. Writes a sectioned script, paints a BURST of pictures per section (about one every 1.5s — most of them one-detail edits of the frame before, so it reads as movement rather than a slideshow), narrates each section with TTS, holds each picture PERFECTLY STILL for its own slice of the narration (the motion is the CUT RATE, exactly as Higgsfield's stills pipeline does it — a slow move on a still shimmers), then composites the end card (and any on-screen text you asked for) with the Chrome+ffmpeg engine the ads use (text is never model-painted, so it never garbles). BURNED ON-SCREEN TEXT IS OFF BY DEFAULT — the narration carries the point and the pictures carry the story, so the film ships clean unless the user asks otherwise; `captions:true` adds held key points and `subtitles:true` adds narration-timed CAPS (see both). It is an image film WITH motion, not N video-model renders — that's what keeps it affordable. `style` picks the visual family: the default 'cinematic' is photoreal editorial; every other id is a STYLED, strictly non-photoreal look (illustrated / collage / clay / pixel …) that first renders ONE style-key image and then locks every scene to it, so the whole film holds one look. Cost at the default frame density: a ~130-credit hold for a 60s explainer on the default style, ~100 styled; `frameDensity:'lean'` roughly halves it and `'minimal'` (one picture per section) is ~30. All settle to the exact per-frame image + narration spend (a longer target = more sections = more). Takes SEVERAL minutes — one image render per frame; independent frames are painted concurrently, so it is far faster than the frame count suggests. Needs the writing model and a narration voice engine connected. NOT the tool for a short product ad — use render_ad or generate_video for those, and make_template_ad for the deterministic native formats.
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  • List the images the user ALREADY has in their Orivox media gallery -- uploads made on the editor's media page or through Orivox before -- as hosted URLs ready to use DIRECTLY in <img src> or apply_dom_ops set_attr. Check here FIRST whenever the user mentions "my images", their gallery, or pictures they already uploaded, before asking them to upload or send anything. role="logo" lists the logo folder, "content" the general image folder, "all" (default) both, newest first. Each entry carries url, file_name, width/height (null when unknown), and modified_at. Returns the newest `limit` images (default 24, max 500); truncated=true with a larger total means older images exist -- re-call with a bigger limit only when the user actually needs them. Use the urls exactly as returned -- never rewrite them through the a12 grammar. Read-only; changes nothing.
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  • "Show me photos from the Mars rover" / "Perseverance images from sol 1000" / "latest pictures from Mars" — raw images from NASA's Perseverance rover (Mars 2020), straight off the mars.nasa.gov feed. Filter by Martian sol and by camera. Returns image URLs at four resolutions, the sol, the UTC and Mars-local capture times, and the camera instrument. Keyless. Covers Perseverance only — Curiosity, Opportunity and Spirit have no live public image feed. Example: get_mars_photos({ sol: 1000, camera: "NAVCAM_LEFT" })
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  • Return live statistics about the Workers' Rights corpus: total number of court rulings in the research corpus, number of public attorney listings, number of monitored legal data sources, the date the corpus was last updated, and the distribution of case outcomes across the analyzed rulings. Use this to establish scale/credibility or to answer 'how much data do you have / how current is it'.
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  • Render a cheap multi-frame OVERVIEW of a scene as low-res jpeg thumbnails YOU CAN ACTUALLY SEE: each sampled frame comes back as an inline image content block (labeled with its scene time), alongside the machine-readable `{ frames: [{time, url, inline}] }`. Two modes: pass `times` (PREFERRED — you usually know the interesting moments: clip seams, animation midpoints, entrance ends) to get an EXACT thumbnail per requested time, rendered concurrently; or pass `frames` (default 8, max 24) for evenly-spaced sampling across the whole timeline (one image-sequence render at 1fps — integer-second granularity only). Sits between a single full-res frame check and picsart_media_export (full encode): use it to eyeball pacing, seams, and content presence across the WHOLE timeline before exporting, instead of checking single frames repeatedly. Auth is handled by the platform automatically — no token setup needed on your end. Validate the scene first. Inline images are best-effort under a total size/count budget: a frame that fails to download, is oversized, or falls outside the budget still comes back with its `url` and `inline: false` in the JSON — a partially-inlined sheet is a SUCCESS, not an error, because the render has already happened and been charged. Do not retry this call just to get the missing pictures (that re-charges the render) — open those urls instead.
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Matching MCP Servers

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    An MCP server that lets AI clients search and retrieve Doctor of Credit articles, categories, and deals via flexible tools, interpreting article content at request time.
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    Chain of Draft Server is a powerful AI-driven tool that helps developers make better decisions through systematic, iterative refinement of thoughts and designs. It integrates seamlessly with popular AI agents and provides a structured approach to reasoning, API design, architecture decisions, code r
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Matching MCP Connectors

  • Returns contact information for Symbols of Wealth Studio — email, website, location, and how to engage. Use this when a user wants to actually reach out to or hire Symbols of Wealth Studio, rather than browse the full studio profile.
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  • Returns contact information for Symbols of Wealth Studio — email, website, location, and how to engage. Use this when a user wants to actually reach out to or hire Symbols of Wealth Studio, rather than browse the full studio profile.
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  • SEARCHES INSIDE ONE BOOK (requires book_id). PRIMARILY KEYWORD: it runs a lexical search over the book's pages plus a narrow scoped-semantic pass (top ~10), interleaved by relevance. PICK THIS when you know the wording you are looking for, or want every page of one book mentioning a term. → IF YOU ARE SEARCHING FROM A PARAPHRASE, a half-remembered line, or a modern restatement, USE search_concept INSTEAD — it is the meaning-matching tool and it searches the whole corpus, including translations whose vocabulary differs completely from yours (Thomas Taylor writes "energies" for energeia and "felicity" for eudaimonia, so a sensible modern paraphrase can miss his pages entirely while matching semantically). → To find the book first, use search_library or search_concept, then pass its book_id here. Each result carries score (0-1, normalised within this book) and found_by ("keyword", "semantic", or "both" — both is the strongest signal). Results flagged is_front_matter are the translator's or publisher's words rather than the author's, and are ordered last. Returns OCR and translation snippets with page numbers, ready to cite.
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  • Concise profile of one city: currency, tax shape (bracket count + top rate + payroll/national insurance), headline costs (rent / groceries / transit / childcare), safety-net values (parental leave, vacation, universal healthcare), and data freshness. Lighter than compare_cities; use when the user is asking about one place rather than a comparison. On parental leave, quote safety_net.parental_leave_summary rather than building your own sentence: some countries (Ireland, Australia, the UK, Czechia, part of Sweden) pay a flat weekly cash sum instead of a share of salary, so parental_leave_paid_pct is 0 or partial for them and stating it alone would wrongly call their leave unpaid. Read-only, no side effects; returns a text summary plus structured JSON.
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  • Batch lookup of safety-net values for 1 to 20 cities at once: parental leave weeks + how it is paid, universal healthcare flag, vacation days, public holidays, plus each city's safety_net dimension score (0-100) for relative strength. This is the only tool that accepts many cities in one call: use it to line several places up on family / leave / healthcare benefits. On parental leave, quote parental_leave_summary rather than composing your own line from parental_leave_paid_pct: Ireland, Australia, the UK, Czechia and part of Sweden pay a flat weekly cash sum instead of a share of salary, so their headline percentage is 0 or partial and reading it alone would wrongly call their leave unpaid; Germany pays a percentage up to a monthly cap (parental_leave_capped) and pays nothing at all above a household-income ceiling. Check parental_leave_basis (percentage / flat / capped / mixed / unpaid) before making any claim about pay. For one city's full profile (tax shape + costs + safety net together) call get_city_summary instead; for a two-city head-to-head that includes cost-of-living use compare_cities. Read-only, no side effects; returns a text summary plus structured JSON.
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  • Summary of live flight activity over a named region — aircraft count, country-of-registration breakdown, average altitude, and airborne vs on-ground split. Built for "is this airspace still operating" questions (airspace closures, conflict zones, strait and corridor traffic). Keyless. Supported regions: Iran, Israel, Syria, Ukraine, Russia, Taiwan, North Korea, South China Sea, Yemen, Strait of Hormuz, Taiwan Strait, Red Sea, Saudi Arabia, Gulf of Aden, Lebanon.
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  • Create a NEW architecture diagram from a graph that YOU author, and get back a shareable, editable canvas URL plus a rendered SVG and Mermaid. You produce only the SEMANTICS — nodes, the groups (VPC/cluster/...) they live in, and the directed edges between them. You do NOT lay anything out: never send x/y/position/pinned. A deterministic layout engine computes all geometry and an icon layer picks the pictures from each node's kind. kind.catalog is one of aws | gcp | azure | k8s | saas | generic, each with rich per-catalog kind.types (e.g. aws:lambda, gcp:bigquery, azure:cosmos_db, k8s:deployment, saas:kafka): - "aws" (api_gateway, lambda, s3, rds, dynamodb, sqs, bedrock, kinesis, fargate, eventbridge, aurora, ...). - "gcp" (compute_engine, gke, cloud_run, cloud_sql, spanner, firestore, bigquery, pubsub, dataflow, vertex_ai, ...). - "azure" (virtual_machine, aks, app_service, functions, blob_storage, sql_database, cosmos_db, service_bus, event_hubs, key_vault, ...). - "k8s" (pod, deployment, statefulset, daemonset, job, cronjob, service, ingress, configmap, secret, hpa, ...). - "saas" for hosted third-parties (redis, postgresql, mysql, mongodb, kafka, stripe, twilio, auth0, github, cloudflare, ...). - "generic" primitive when nothing branded fits: service, database, cache, queue, user, external_system, storage, gateway, function, note. - "generic" FLOWCHART kinds for processes/flowcharts: process, decision, terminator, data, document, subprocess. edge.kind is one of: request, response, async_event, data_flow, dependency, network, generic. WORKED EXAMPLE — a user hitting an API in a VPC that talks to Postgres: { "title": "Web API", "domain": "cloud_architecture", "graph": { "groups": [{ "id": "g_vpc", "label": "VPC", "type": "vpc" }], "nodes": [ { "id": "n_user", "label": "User", "kind": { "catalog": "generic", "type": "user" } }, { "id": "n_api", "label": "API", "kind": { "catalog": "aws", "type": "api_gateway" }, "parentId": "g_vpc" }, { "id": "n_db", "label": "Postgres", "kind": { "catalog": "aws", "type": "rds" }, "parentId": "g_vpc" } ], "edges": [ { "id": "e1", "source": "n_user", "target": "n_api", "kind": "request" }, { "id": "e2", "source": "n_api", "target": "n_db", "kind": "data_flow" } ] } } Returns { diagramId, url, svg, mermaid, version }. Give the user the url — opening it shows the same diagram on an editable canvas (anonymous; it's theirs to claim by signing in). To change the diagram afterwards, use get_diagram then edit_diagram.
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  • Count Washington State vehicle registration transactions — original registrations and renewals processed by the Department of Licensing (Washington DMV) — for one fiscal year or one calendar month, broken down by county of the registered owner, county where the transaction happened, fuel type, use class, or month. Answers "how many vehicle registrations did King County process in fiscal 2026", "monthly registration volume in Washington", "diesel registration transactions by county", and "which Washington counties process the most registrations". Each transaction is an event, so a county with 1.9 million transactions in a year has far fewer vehicles than that; for the size of Washington's registered electric fleet use wa_dmv_ev_population.
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  • Browse transcriptions hierarchically Returns a hierarchical browse of available page transcriptions. Mirrors `/transcripties/lijst/`. Three modes, depending on the supplied filters: * No filter — top-level list of source archives ordered by total transcription count (descending). * `archive_code` — list of all archive numbers (archieftoegangen) within that archive, ordered by archive number. * `archive_code` + `archive_number` — list of all inventories within that archive number, ordered by inventory number. The order of items is fixed and cannot be overridden. Results are always returned in full (no paging).
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  • Get autocomplete suggestions for Danish word prefixes. Useful for discovering Danish vocabulary or finding the correct spelling of words. Returns lemma forms (dictionary forms) of words. Args: prefix: The beginning of a Danish word (minimum 3 characters required) max_results: Maximum number of suggestions to return (default: 10) Returns: Comma-separated string of word completions in alphabetical order Note: Autocomplete requires at least 3 characters to prevent excessive results. Example: suggestions = autocomplete_danish_word("hyg", 5) # Returns: "hygge, hyggelig, hygiejne"
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  • Get full details of a Cochrane systematic review by PubMed ID. Returns the complete abstract, authors, publication info, MeSH terms, and conclusions of a Cochrane review. Use PMIDs from search_reviews results. Args: pmid: PubMed ID of the review (e.g. '35658166').
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  • "CWEs derived from / under [N]" / "child weaknesses of [CWE]" / "more specific variants of [X]" — list immediate children of a CWE in the relationship tree. CWE is hierarchical; e.g. children of CWE-119 (memory bounds) include CWE-787 (out-of-bounds write) and CWE-125 (out-of-bounds read).
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  • What is the shape of one metric? Returns histogram buckets (count + share) plus summary stats. Metric: one of lcp, inp, cls, fcp, ttfb (field CWV), or a scalar technique path when available. Filter: same as get_metrics (device, cms, framework, cdn, provider). No group_by — call get_metrics with group_by to compare segments, then get_histogram per segment if needed.
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