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533,861 tools. Updated 2026-09-08 11:10

"iPhone 16e camera review summary and table creation in Italian" matching MCP tools:

  • Generate one actor-grounded narrative first frame from one to four existing LetMeActForYou actor_ids plus location, wardrobe, pose, and composition. Uses actor headshots as image references and returns a stored image_url. For multi-shot continuity, first generate a wide scene reference, then pass its scene_frame_id as continuity_scene_frame_id while specifying a fresh camera setup in composition and fresh blocking in pose for every shot. Pass only the actor_ids that should be visible in that shot. Pass composition_reference_url to preserve a Blender previs frame's camera and blocking while replacing proxy geometry with actors and the finished set. Defaults to Gemini; pass provider='grok' to use Grok Imagine. Use this before animation when a close-up headshot is not enough.
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  • Lists the 10DLC Campaigns registered under the 10DLC Brand identified by `brand_id`, filterable by name, use case, status, mock flag, and creation date. Use to review or find Campaigns belonging to one specific Brand. Read-only; no side effects. Requires the `campaigns:read` scope, the 10DLC feature enabled for the account, and the `brand_id`; results are paginated with `per_page` from 1 to 100 (default 25) and `page` starting at 1.
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  • Capability manifest of the hosted runners: LAMMPS version, installed packages, and every style by category with gpu=true (KOKKOS-accelerated) or gpu=false (exists, but runs on the pod's CPU cores at the GPU rate). Default = compact summary; runner=lammps&full=true returns the whole style table. Use preflight_deck to check a specific deck.
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  • Find fashion brands using natural language, structured filters, or both. Best for queries like "Italian streetwear brands", "Scandinavian minimalist brands", "Japanese technical outerwear", "brands with avant-garde tailoring", or qualified similarity such as "brands like Rick Owens for technical outerwear". For a plain "brands like X" request, use find_similar_brands. Country adjectives ("Italian", "Scandinavian", "Nordic", "Japanese", "Iberian", "Benelux") are parsed server-side into shipping-origin filters; you don't need to translate them to ISO codes. `query` is optional — provide a query, structured filters, or both. Brand country/shipping signals are best-effort and separate from product availability.
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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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  • Translate a plain-language question into a candidate SQL query using pattern-matching against the live schema (no AI model — simple questions only: counts, averages, filtered selects on a named table). Returns the SQL without executing it, with a confidence score; low confidence means the table was guessed. Review the statement and tables_used, then run it with scalix_db_query. For complex questions, read scalix_db_schema and write the SQL directly.
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Matching MCP Servers

  • A
    license
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    maintenance
    An MCP server that enables interaction with local camera devices to capture and process images. It allows LLMs to access video devices with configurable settings such as resolution, orientation, and image format.
    1
    MIT

Matching MCP Connectors

  • Concise English Wikipedia summaries — paid per call (x402/credits), 1 tools

  • Capture photos remotely from mobile devices via S3-backed upload URLs

  • Ring the human's iPhone, speak the question aloud, and return what they say. Waits up to ~30s; if the result comes back status "ringing", follow up with poll_result. On a local client, read `to` from `~/.aiphone/config.json` → `user_number`; this hosted server cannot read that file itself. `to` is the 10-digit /call-me app number, not a real phone number. Pass a previous session_token to stay in the same thread on their phone.
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    Destructive
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  • Compare all Italian regimes side by side at one revenue level. Runs forfettario (5% & 15%), ordinario, and ordinario + impatriati through the deterministic engine and returns them sorted by net income (best first), each with its full breakdown and eligibility. Args: revenue_eur: Gross annual revenue in EUR. coefficient: Forfettario coefficiente di redditività (0.40–0.86); omit for the professional-services default (0.78). cost_ratio: Deductible costs as a fraction of revenue (0–1) for the ordinario regimes.
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  • Record the user's verified-purchase review of how a UFP order turned out. YOUR JOB IS TO STRUCTURE THE FEEDBACK: turn what the user actually said into stars (1-5 overall) and facet scores — "the cut was sloppy" -> quality, "parts arrived 2 days late" -> timeliness, "wrong color" -> accuracy. Keep the optional comment to a short factual summary of their words; never embellish. ALWAYS draft the review (stars, facets, comment) and confirm it with the user BEFORE calling this tool — e.g. "I'll rate this 2 stars with timeliness 1 because it arrived 2 days late — send it?". One review per order: submitting again updates the existing review. Use list_orders first if you need to resolve which order they mean.
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  • Full metadata for one Flevy item, by content_id from search_content (e.g. "doc-1234" or "case-567"). Documents return the author with their credentials (headline, bio, LinkedIn, profile URL; pass the author name to search_content's author filter to list more of their documents), full description, editor summary, AI summary, and editorial review when available, page/slide count, price, FlevyPro inclusion, management topics, ranking badge, and the number of slide deep dives available. Case studies return the client situation, TL;DR, and summary. Call this before recommending an item so you can describe it accurately and cite the author's credentials, and share the returned flevy.com URL.
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  • Retrieve WHOIS registration data: registrar, creation/expiry dates, nameservers, status. Use to verify domain ownership, age, expiration; for full audit use domain_report. Free: 30/hr, Pro: 500/hr. Returns {domain, whois: {registrar, creation_date, expiry_date, updated_date, name_servers, status, raw_length, error}, summary}.
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  • Verify a photo's authenticity from a RAW camera file and its JPEG export. Provide the files as attachments (raw_file = the camera RAW such as .CR2/.CR3/.NEF/.ARW/.RAF/.ORF/.DNG, image_file = the exported .jpg/.png), inline as raw_base64 + image_base64 (small files), or — for large files without attachments — call create_verification_upload first and pass the returned raw_object_key + image_object_key. Returns a verification id; poll get_verification for the result. Counts against the monthly quota (free tier: 5/month).
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  • Pre-flight security verdict for an MCP server invocation. Judges BOTH server-level reputation AND the server's dependency graph (npm/pypi) against the DugganUSA threat-intel corpus (1.13M+ IOCs, Shai-Hulud + typosquat + LOLBin families). Returns BLOCK / ADVISORY / REVIEW / ALLOW with severity, evidence, dep-graph summary, and HMAC-signed response. REVIEW means we hold NO RECORD of this server -- not that it is safe. Treat REVIEW as do-not-proceed-blindly: a brand-new attacker-published server looks exactly like this. ALLOW is only returned when we actually resolved the server and scanned its dependency graph; check known_to_us and dep_graph.scanned to confirm. Use this BEFORE invoking any other MCP server tool, especially ones installed from outside the official MCP Registry.
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  • Delete a table. The request requires the 'name' field to be set in the format 'projects/{project}/instances/{instance}/tables/{table}'. Example: { "name": "projects/my-project/instances/my-instance/tables/my-table" } The table must exist. You can use `list_tables` to verify. Before executing the deletion, you MUST confirm the action with the user by stating the full table name and asking for "yes/no" confirmation.
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    Destructive
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  • Search every Agentorist vertical at once — the answer to "what's on?". Use this when the user's request spans verticals or doesn't clearly name one ("what's on tonight", "anything to do in Boston?", "Friday night plans"). For specific single-vertical queries ("movies tonight", "Italian restaurants"), `search_all` auto-narrows to the hinted vertical so you don't waste calls. Returns `results_by_vertical` keyed by movies/events/local, plus `total_count` and `bookable_total` for quick summaries.
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  • Returns WSDOT highway camera locations, descriptions, and image URLs. Camera images are copyright WSDOT — only metadata and image URLs are returned, not image bytes. Filter by state route ("I-90", "90", "SR 520", or "520" all work), WSDOT region, or milepost range. Results are ordered by cameraId and paged — pass offset/limit to page through the full set (the notice reports the next offset).
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  • Answers "is there a decibel meter app", "best decibel meter app for iPhone", "how do I measure sound with my iPhone", "what is Decibel Shield". Facts and the App Store link for Decibel Shield - dB Meter, the iOS sound level meter app behind this data: features, pricing, requirements. Use only when someone wants to measure sound with a phone or asks about the app itself — for noise data, use the other tools.
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  • Pick up an existing quote that was started in a previous session or on a different platform. The customer supplies a quote ID. Verification: if the same authenticated user (OAuth user_id matches across sessions), no extra verification is needed; otherwise the customer needs to provide an email code that was sent at quote start. Returns the current status, a summary of what's collected so far, and whether rate options are already available to review.
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  • List the canvas tables (faostat_xxxxxxxx) staged by faostat_query_observations and faostat_commodity_profile, each with its source tool, the query parameters that produced it, creation/expiry timestamps, row count, and column schema. Call this before faostat_dataframe_query to discover the exact table and column names to reference in SQL. Tables are listed newest-first and paged: pass `name` to describe one table outright, or page with `offset` + `limit` — when the response reports `truncated`, pass the returned `nextOffset` to fetch the rest.
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  • Capture the RAW camera frame — no perspective warp, no crop to the calibrated screen quad. Use this to see exactly what the camera sees before any correction, e.g. when troubleshooting why take_screenshot looks wrong, or before adjusting corners with get_corners/set_corners.
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  • Refine an existing layer to a NAMED area the server resolves from OpenStreetMap — a street corridor ("Broadway from Arbutus Street to Main Street"), a place ("Mount Pleasant"), or an intersection surroundings. Pass names only, never coordinates; unresolvable names return a clarification with real nearby candidates instead of guessed geometry. Emits ordinary undoable ops (filter / new layer + camera) and a grounded summary like "kept 37 of 150 features". Costs 1 credit when a mutation lands; clarifications are refunded.
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