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466,711 tools. Updated 2026-08-20 04:17

"Tools and Methods for Extracting Data from PDFs and Images" matching MCP tools:

  • Summarize document text into a prose summary and key points with citations. Use after document.extract_text or url.extract when you need a condensed understanding of a long document. For single-sentence Q&A, use url.qa instead. For extracting specific fields, use document.extract_structured. Typical workflow: document.extract_text/url.extract → document.summarize. Returns: { summary: string, key_points: string[], summary_cited: { value, confidence, citations[] }, key_points_cited: [{ text, citations[] }], truncated: boolean, strategy: "full"|"truncated"|"chunked" } Example prompts: - "Summarize this financial report and give me the key points." - "What are the main takeaways from this document?" - "Give me a concise summary of this 50-page report."
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  • 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.
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  • Submit a photo or PDF of a receipt for processing. Covers requests phrased as 'log this', 'log this receipt', 'save this receipt', 'expense this', or 'add this to my expenses', including when the user simply shares a photo of a receipt or invoice. The receipt image is validated, uploaded to cloud storage, and processed by AI to extract vendor, amount, date, tax, and category. The expense appears in the user's spreadsheet in about 1-3 minutes, and longer for PDFs or large batches. Handles images and PDFs, mixed together in one batch. TO SEND FILES (preferred, and required for PDFs): call this tool with filesToUpload listing every file the user gave you. It returns one signed upload URL per file. Upload them ONE AT A TIME with an HTTP PUT, telling the user which file you just finished and how many remain, then call this tool ONCE with uploadRefs for all of them — that processes the whole set as a single batch, like the ExpenseBot web app. Do not call this tool once per file. Only use the photo parameter for a single small image whose base64 you can reliably include in full — large base64 payloads are frequently dropped in transit, which silently loses the receipt. Optional note and tag values use the same receipt metadata path as ExpenseBot's camera, file uploader, and forwarded-email intake. The note is stored in the Notes column (L); the tag is stored in the Tag column (K). Batch defaults apply to every file, and each uploadRefs item may override either value for that file.
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  • Get product details (variants, options and images) by product ID(s). Arguments: productIds - array of product IDs to get details for (from 'search_products'). [IMPORTANT] Request only the products the user needs. A server-configured limit applies (default 20); requests over the limit are rejected with an error (retry with fewer IDs). option_values - resolve a specific variant by option/value IDs. Only valid with a SINGLE productId, and applied on the B2C storefront catalog. B2B buyers instead receive every variant (each with its option/value IDs) and pick the desired one from the returned list. channelId - optional; scopes the B2B catalog. Defaults to the channel resolved from the request. Returns: - products: array of products, each with: - variants: each carrying entityId, SKU, and options (optionId, optionLabel, valueId, valueLabel). - For B2B buyers, variants also include price, inventoryLevel, purchaseable, and bulkPricing. - Products not found are omitted from the array. Flow: - Call 'search_products' to get product IDs. - Call this tool with the product IDs to get variants, options and images. - Call 'add_item_to_cart' with results of 'search_products' and 'get_product_details' (variant) tools. - [IMPORTANT] If a product has variants you must specify which variant to add.
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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. Synchronous: the call blocks until generation finishes and returns 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 charged only on success, scaled to 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 getImageResults. Requires an API key (user scope). Credits: This endpoint consumes 0.5 credits per result.
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  • Download a PDF from a URL and extract all text content, page by page. Use this to read the full text of a specific document — for example, an annual report PDF linked from a search_filings result. Best combined with search_filings: use search_filings to locate the document, then parse_pdf_to_text for the full text. Do not use for PDFs that are already well-represented in the database — search_filings is faster and returns pre-ranked, relevant excerpts. Not suitable for scanned (image-only) PDFs without embedded text; those pages will be returned as "(no extractable text)". Args: pdf_url: Direct HTTPS URL to the PDF file, e.g. https://example.com/report.pdf. Must be publicly accessible; authentication-protected URLs will fail. Returns: All text from the PDF with "--- Page N ---" separators between pages. Returns an error string if the download fails, the URL does not point to a valid PDF, or the document exceeds the 60-second download timeout.
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Matching MCP Servers

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    Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.
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    GPL 3.0
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    Provides MCP tool adapters for Bioconductor methods like limma, DESeq2, and fgsea, enabling statistical analysis of omics data through containerized R execution. It serves as a bridge between MCP clients and bioinformatics tools for reproducible research workflows.
    Apache 2.0

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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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  • Summarize document text into a prose summary and key points with citations. Use after document.extract_text or url.extract when you need a condensed understanding of a long document. For single-sentence Q&A, use url.qa instead. For extracting specific fields, use document.extract_structured. Typical workflow: document.extract_text/url.extract → document.summarize. Returns: { summary: string, key_points: string[], summary_cited: { value, confidence, citations[] }, key_points_cited: [{ text, citations[] }], truncated: boolean, strategy: "full"|"truncated"|"chunked" } Example prompts: - "Summarize this financial report and give me the key points." - "What are the main takeaways from this document?" - "Give me a concise summary of this 50-page report."
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  • Fetch a public HTTPS URL and return its content translated into a target language. Lean mode — no bundle stored. Use when you need to understand web content in a different language. For extracting raw untranslated text, use url.extract instead. Returns: { url, translated_text, target_lang, truncated } Example prompts: - "Translate https://example.de/artikel into English for me." - "Translate this German article into Spanish: [URL]." - "Fetch [URL] and give me the French translation."
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  • Generate a video from 1-5 reference images and a text prompt (references-to-video). Unlike createVideo, which animates a single source image, this composes a new scene that borrows characters, objects, and style from the reference images. Each image can be a URL or base64. Synchronous: the call blocks until rendering finishes and returns the video URL and its actual duration in seconds. Choose the output shape with `aspect_ratio` ("default" lets the model decide). The chosen `model` and `duration` must be compatible (incompatible combinations return HTTP 400). Credits are charged only on success, based on the produced duration and never more than the duration you requested. Pass an optional `request_id` to tag the result so you can locate it later via `getVideoResults`. Related tools: `createVideo` for image-to-video, `editVideo` to modify a generated video. Requires an API key (user scope). Credits: cost varies by model and duration (credits/sec): Eagle 1.5/s, Eagle with Audio 2/s; see this endpoint's full pricing table in the API docs.
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  • Extract structured transaction data from a contract at a URL. Downloads the document, extracts text (with OCR fallback for scanned PDFs), and runs PrimaCoda's contract-extraction prompt to return parties, addresses, dates, prices, and key contract fields. Use this when an agent has the contract hosted somewhere (Dropbox, Google Drive direct download, Square Space, etc.) and wants to skip the upload step. For multi-document deals (purchase + addenda + disclosures), use the PrimaCoda dashboard's batch upload — this tool handles ONE document. Args: pdf_url: Direct download URL for the contract (PDF, DOCX, TXT, or image). Must be reachable from the PrimaCoda server. Google Drive "shared link" URLs work if set to "anyone with link"; other share URLs may need their direct-download form. api_key: Your PrimaCoda MCP API key (starts 'pck_').
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  • Compare two screenshots — a baseline/expected capture and a live/current capture of (nominally) the same screen — using a perceptual pixel-diff. Returns the similarity score and changed-pixel count as text, AND returns the baseline, live, and diff images as images you can view directly, so YOU judge whether any flagged difference is a real regression (layout shift, missing/broken element, wrong color/theme, wrong or garbled text, unexpected new content) or just benign noise (dynamic content like timestamps/ads/carousels, anti-aliasing, rendering noise) — this tool does not make that call for you. Provide either two raw base64 images, or a review_id (from list_visual_reviews) to pull a stored baseline instead of re-fetching it.
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  • Get term info for a VFB or anatomy ontology entity (VFB_*, FBbt_*, etc.). THIS IS THE QUERY DISCOVERY TOOL: the response's "Queries" array lists the valid query_type values that run_query accepts for this entity. ALWAYS call get_term_info before run_query unless you already obtained the query_type from a previous get_term_info call in this conversation. Returns: SuperTypes (classification), Tags (data flags like has_image, has_neuron_connectivity), Queries (valid query_types for run_query), RelatedTools (other MCP tools applicable to this entity, with default_args ready to copy — e.g. get_hierarchy with subclass_of for cell types or part_of for nervous-system regions), Images (keyed by template brain ID), Publications, Synonyms. Supports batch — pass an array of IDs to fetch in parallel; batch results are returned as a JSON object keyed by ID. To build VFB browser URLs from the Images field: https://v2.virtualflybrain.org/org.geppetto.frontend/geppetto?id=<VFB_ID>&i=<TEMPLATE_ID>,<IMAGE_ID1>,<IMAGE_ID2> — id= sets the focus term and i= lists images for the 3D viewer (template ID must be first in i= to set the coordinate space).
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  • Get your agent's real mailing address beta endpoint when the account has explicit beta access: street address + mailbox number for approved accounts. For generally available inbound context, use list_inbound_forwarding_addresses instead; that returns a private intake alias for scans, PDFs, photos, provider notices, and notes from addresses the operator already uses.
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  • Start a batch render job to generate multiple images from a single template — from inline variable sets, or from a hosted CSV where every row becomes a render. Each variable set produces a separate image. Supports up to 100 items per batch (plan-dependent). Common use cases: generating personalized social cards for all team members, product images for an entire catalog, event badges for all attendees, certificate images for course graduates, or marketing assets with localized content. WORKFLOW: 1) Use pictify_get_template_variables to discover variables, 2) Call this tool with an array of variable sets, 3) Use pictify_get_batch_results to poll for completion and get result URLs. The job runs asynchronously — this tool returns immediately with a batchId (HTTP 202). For generating a single multi-page PDF instead, use pictify_render_multi_page_pdf.
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  • Fetch the FULL TEXT of a biomedical paper from PubMed Central (the open-access subset) by PubMed ID. PREFER OVER get_abstract when you need methods/results/discussion, not just the abstract — "read the full paper", "what methods did <PMID> use", "extract details from the paper". Resolves the PMID to its PMC id and returns the article body text (capped ~40k chars). Only open-access articles are in PMC — returns has_full_text:false (use get_abstract) otherwise.
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  • Test a regular expression pattern against an input string and return all matches with their index positions and named capture groups. Use for validating user inputs, extracting structured data from text, or debugging regex patterns. Supports flags g, i, m, s, u, y. The match runs in an isolated thread with a 500 ms budget: a pattern that blows up (catastrophic backtracking, e.g. "(a+)+$") comes back as redos_detected:true — a real ReDoS verdict on your pattern — instead of hanging.
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  • Create a Revise document from a LOCAL file (docx, md, txt, html; PDFs/images not yet supported) without a Revise account and without putting its bytes in your context. Returns a one-time upload_url and a ready-to-run curl command — run the curl to stream the file. The curl response contains url (give it to your user — they view the document and create a free account to keep it, in one step) and edit_token (your Bearer token for future edits). For a public http(s) URL or a tiny inline file, use import_document instead. The document is private and deleted after 7 days if unclaimed.
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  • Fetch one engine reference catalog. Catalogs (cheap, cacheable per session): - 'operators' — comparison operators for condition expressions - 'execution-modes' — entry/exit anchors and fill algorithms, with the validity matrix by market type - 'stop-types' — stop-loss types, re-entry modes, and their parameters - 'sizing-methods' — position-sizing methods and their parameters - 'bar-frequencies' — supported bar frequencies and the signal x execution validity matrix (which combinations are allowed) - 'sections' — the full metric catalog: every statistic's stable id, display label, section, and description - 'sampling-modes' — Monte-Carlo resampling modes, each with its status and parameters Fetch the relevant catalog BEFORE building a strategy or config; build only from values it lists — never guess parameter names or frequencies.
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