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590,439 tools. Updated 2026-09-20 01:20

"Extracting Images from Search Results" matching MCP tools:

  • Return the EXACT images the user chose on their upload link. Pass the token_id that request_image_upload_link returned. Call this after the user says they uploaded or picked their images: it returns files[], each with a hosted url and a source ("upload", "gallery", or "shared"), so you place PRECISELY the images they selected instead of guessing from the whole gallery. An empty files list means they have not chosen anything yet -- ask them to open the link and add images, or wait and check again. Read-only; changes nothing.
    ConnectorOAuth
  • Fetch and convert a Microsoft Learn documentation webpage to markdown format. This tool retrieves the latest complete content of Microsoft documentation webpages including Azure, .NET, Microsoft 365, and other Microsoft technologies. ## When to Use This Tool - When search results provide incomplete information or truncated content - When you need complete step-by-step procedures or tutorials - When you need troubleshooting sections, prerequisites, or detailed explanations - When search results reference a specific page that seems highly relevant - For comprehensive guides that require full context ## Usage Pattern Use this tool AFTER microsoft_docs_search when you identify specific high-value pages that need complete content. The search tool gives you an overview; this tool gives you the complete picture. ## URL Requirements - The URL must be a valid HTML documentation webpage from the microsoft.com domain - Binary files (PDF, DOCX, images, etc.) are not supported ## Output Format markdown with headings, code blocks, tables, and links preserved.
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  • Search the Metropolitan Museum of Art collection by keyword and optional filters. Returns the total match count and a page of matching object IDs, which met_get_object resolves to full records. Relevance is keyword-based, not semantic; department and geographic filters narrow results more than a longer query. The medium parameter maps to the classification field (pass "Paintings", "Drawings", etc., not material descriptions like "Oil on canvas"). Every filter draws on a partial upstream index, so a filtered search omits some objects whose own record satisfies the filter — the results are not exhaustive, and dropping the filter is what widens them. A filtered search is checked against the same query run unfiltered, so its results match the keyword; when that check is too costly to complete the page is returned unchecked and the response says so in its notice. isPublicDomain selects CC0-licensed images; hasImages also includes copyrighted works. isPublicDomain and isHighlight are opt-in filters that accept true only; the upstream index is unsound on the false arm. isOnView restricts results to works currently on display in a Met gallery.
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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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  • Search the web and get back ranked results with the page text already extracted, so there is no second call to fetch content. `query` is required. Returns `results[]` with `url`, `title`, `content` (the extracted excerpt), `score` and optionally `raw_content`, alongside `query`, `images`, `response_time` and `request_id`; set `include_answer` to also get a one-paragraph `answer`. Filter with `topic` (general/news/finance), `time_range` or explicit `start_date`/`end_date`, and trade cost against depth with `search_depth`. Measured at roughly 6 seconds for 2 results. This is the default choice for open-web research, and the only search here that returns ranked results and page text in one call. Reach past it when: you already know the URLs — `post_tavily_extract` is cheaper and exact; the query is a description rather than keywords — `post_exa_search` matches on meaning; you want a written answer rather than a list to iterate — `post_perplexity_sonar`; you want peer-reviewed papers — `post_scholar_search_scholar`.
    ConnectorOAuth
  • Get the full record for a single product by its numeric ID. Use after `search_products` returns a candidate the user is interested in, when you need fields not in the search summary (full description, all images, sold status, expiration). Don't loop `get_product` over many search results — re-search with tighter filters instead. Read-only. No authentication. Args: product_id: Integer `id` from a `search_products` result, or visible in a Partle product page URL (`/p/<id>-<slug>`). Returns: A single product object with all fields, including the canonical `partle_url` to share with the user. Returns ``{"error": ...}`` if the ID does not exist.
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  • Generate game-art images from a text prompt alone, selecting an image_type (e.g. sprite) and optionally art_style, perspective, and aspect_ratio. The job result is an array of image results, each with a url; request n (1-8) to control how many variations come back. Because it generates purely from text it takes no source image, so there is no upload size limit to trip. Credits are held when the job is accepted and refunded if it fails or is cancelled; the charge scales with the number of images produced. Use createImage to make new images from scratch; use generateWithStyle to match a reference image's art style, editImage to modify an existing image, and removeBackground to cut out a subject. Pass an optional request_id to tag the results so you can retrieve them later via listGenerations (type image). Async generation job: returns `{id, status}` - poll `getApiJob` (job and credit contract: see the server instructions). Credits: This endpoint consumes 0.5 credits per result.
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  • Get the full record for a single product by its numeric ID. Use after `search_products` returns a candidate the user is interested in, when you need fields not in the search summary (full description, all images, sold status, expiration). Don't loop `get_product` over many search results — re-search with tighter filters instead. Read-only. No authentication. Args: product_id: Integer `id` from a `search_products` result, or visible in a Partle product page URL (`/p/<id>-<slug>`). Returns: A single product object with all fields, including the canonical `partle_url` to share with the user. Returns ``{"error": ...}`` if the ID does not exist.
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  • Search 200,000+ historical illustrations, emblems, engravings, diagrams, AND 24,000+ artworks (paintings, prints, sculptures). Filter by type, subject, figure, symbol, year. Results interleave two collections: illustrations extracted from book pages (each with a page number and book link) and standalone museum artworks (type: "artwork"). The first few results also return as inline images YOU can see. Hosts that support MCP Apps render an in-chat image gallery for this tool automatically; on other clients images may sit inside the collapsed tool-result view, so never tell the user images are "rendered above" unless the gallery appeared — describe what you see and give each image's url link instead. Every image_url is public and stable — an HTML page that references them directly works in any online browser. If images.length is 0, read the note field — an empty result under a book_id filter means that book has no EXTRACTED images yet, not that the physical book has no plates. A broad query can match tens of thousands (read total): narrow with type/subject/symbol/iconclass or page with offset instead of raising limit. On museum-artwork results, a title_is_descriptive flag means the title is an AI description of the picture rather than a title the work was published under — cite such a record by its source_record_title, never by the descriptive one (#4288).
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  • Google Images search for AI agents at $0.010 per call, from the same Serper.dev source as /web/search. Send a query, get back compact JSON: top image results with position, title, image URL, source page link and dimensions. Tune with num (1-10 results), country and language (2-letter codes). Zero results is a valid, honest answer. Pay per call in USDC on Base, no account, no API key.
    ConnectorNo auth
  • Returns one page of pins from a board URL, with a cursor to page. Board pins carry a third field subset, different from both search results and pin detail: node_id, link, domain, rich_summary, seo_url, board and auto_alt_text among them. Measured at 104 KB for 16 pins; trim=true cuts it to 28 KB, keeping per pin id, title, description, link, domain, board, pinner, alt_text, rich_summary and reaction_counts. Board URLs come from board.url on search results — relative, like /agkelsey/the-apartment/, so prefix https://www.pinterest.com — or from get_pinterest_user_boards. For a user's board list rather than one board's pins, use get_pinterest_user_boards.
    ConnectorOAuth
  • Returns one page of pins from a board URL, with a cursor to page. Board pins carry a third field subset, different from both search results and pin detail: node_id, link, domain, rich_summary, seo_url, board and auto_alt_text among them. Measured at 104 KB for 16 pins; trim=true cuts it to 28 KB, keeping per pin id, title, description, link, domain, board, pinner, alt_text, rich_summary and reaction_counts. Board URLs come from board.url on search results — relative, like /agkelsey/the-apartment/, so prefix https://www.pinterest.com — or from get_pinterest_user_boards. For a user's board list rather than one board's pins, use get_pinterest_user_boards.
    ConnectorOAuth
  • Returns one page of pins from a board URL, with a cursor to page. Board pins carry a third field subset, different from both search results and pin detail: node_id, link, domain, rich_summary, seo_url, board and auto_alt_text among them. Measured at 104 KB for 16 pins; trim=true cuts it to 28 KB, keeping per pin id, title, description, link, domain, board, pinner, alt_text, rich_summary and reaction_counts. Board URLs come from board.url on search results — relative, like /agkelsey/the-apartment/, so prefix https://www.pinterest.com — or from get_pinterest_user_boards. For a user's board list rather than one board's pins, use get_pinterest_user_boards.
    ConnectorOAuth
  • Upload images directly to Metadata platform library to create image creatives. Downloads images from provided URLs and uploads them to the platform. REQUIRED STEP IN AD CREATION WORKFLOW: This tool MUST be called between generate_brand_creative and create_update_image_ad. **WORKFLOW INTEGRATION:** This tool is part of the ad creation workflow and should be used: 1. BEFORE creating ads with create_update_image_ad (which requires imageLibraryId/creativeID) 2. IN COMBINATION with generate_brand_creative to create AI-generated images first, then upload them 3. When you need to upload existing images from external sources **COMMON WORKFLOWS:** - Upload existing images → Get imageLibraryId → Use in create_update_image_ad - Generate image with generate_brand_creative → Download generated image → Upload with this tool → Use in create_update_image_ad - Batch upload multiple creative assets for campaign preparation **IMPORTANT:** The returned image ID (imageLibraryId/creativeID) is REQUIRED when creating ads. Every ad needs a creative asset, so you must upload images first before calling create_update_image_ad. REQUIRED PARAMETERS: - images: Array of image URLs to upload IMAGE REQUIREMENTS: - URLs must be valid and publicly accessible - Supported formats: PNG, JPG, JPEG, GIF, WebP, and others - Images will be downloaded and then uploaded to platform - Filenames with spaces will have spaces replaced with underscores EXAMPLES: Single Image: upload_image([ "https://my-bucket.s3.amazonaws.com/images/sample-image.png" ]) Multiple Images: upload_image([ "https://my-bucket.s3.amazonaws.com/images/logo.png", "https://example-assets.s3.us-west-2.amazonaws.com/photos/banner.jpg", "https://content-bucket.s3.eu-west-1.amazonaws.com/uploads/hero image.webp" ]) RESPONSE FORMAT: Returns array of objects for each image: [ { "url": "https://original-url.com/image.png", "name": "image.png", "id": 12345, "success": true }, { "url": "https://failed-url.com/bad.png", "name": "bad.png", "id": null, "success": false, "error": "Download failed: Connection timeout" } ] ERROR HANDLING: - If one upload fails, others will continue - Each result includes success status - Failed uploads include error message - Successful uploads include platform image ID USE CASES: - Upload creative assets before creating ads - Import images from external sources - Batch upload multiple campaign images - Migrate images from other platforms
    ConnectorAPI key
  • List hosted images owned by the caller, with optional filters. ``source`` filters by upload origin: ``"upload"`` for directly uploaded images, ``"generated"`` for images created via the image generation tools. Omit to return all sources. ``visibility`` filters by access level: ``"public"`` or ``"private"``. Omit to return both. Pagination: pass ``next_cursor`` from a previous response as ``cursor`` to retrieve the next page. Returns ``{items: [...], next_cursor: str | null}``.
    ConnectorOAuth
  • Search your library by prompt substring (metadata only — id, prompt, date). Optional folderId scopes to one folder. Only your own assets are returned. This does NOT display images; to show/display results to the user, pass their ids to show_media.
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  • Use this to get full details for a quote. Returns complete attribution, sources, and metadata. When to use: User wants more details about a quote from search results. Use the short_code from previous results. Examples: - `quote("abc123")` - get details for quote with short_code - `quote("xyz789", response_format="detailed")` - with full metadata - `quote("abc123", include_relations=True)` - with translations and variants
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  • Semantic (vector) search across documents in a collection. Returns ranked text chunks with relevance scores. Free — no credits consumed. Use when you need raw matching chunks from a collection. For a synthesized cited answer from the same context, use collection.ask instead. PREREQUISITE: Collection must be populated via collection.add_document and async indexing must complete (poll job.status) before results appear. Returns: { results: [{ bundle_id, chunk_id, text, score: number (0–1), title? }] } Example prompts: - "Search my Q4 Contracts collection for mentions of liability cap." - "Find the clause about data retention in my due diligence docs." - "Search for revenue numbers across my quarterly reports."
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  • Semantic (vector) search across documents in a collection. Returns ranked text chunks with relevance scores. Free — no credits consumed. Use when you need raw matching chunks from a collection. For a synthesized cited answer from the same context, use collection.ask instead. PREREQUISITE: Collection must be populated via collection.add_document and async indexing must complete (poll job.status) before results appear. Returns: { results: [{ bundle_id, chunk_id, text, score: number (0–1), title? }] } Example prompts: - "Search my Q4 Contracts collection for mentions of liability cap." - "Find the clause about data retention in my due diligence docs." - "Search for revenue numbers across my quarterly reports."
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  • Retrieve the full contents of a single item from the user’s memory by its id. Ids come from `search` results. Use this when a search result looks relevant and you need the whole record rather than the excerpt.
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  • Search the results archive — completed-match RESULTS from 1968 through 2022: ATP and WTA, main draws, qualifying and the ITF/futures tiers. Winner/loser-shaped records with final score, seeds and ranks AT THE TIME of the match. Use this for historical questions ("Borg's Wimbledon finals"); the archive ends 2022-12-31 where our own results (get_recent_results) begin. Requires the BASIC plan or any History plan.
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