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308,390 tools. Last updated 2026-07-28 05:59

"A tool to extract or read text and images from PDFs" matching MCP tools:

  • extract_document

    Sats4AI - Bitcoin-Powered AI Tools

    Extract text from PDFs and images as clean Markdown. Uses Mistral OCR — handles complex layouts, tables, handwriting, multi-column documents, and mathematical notation. Preserves document hierarchy in structured Markdown. 10 sats/page. Pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='extract_document' and quantity=pageCount for multi-page PDFs.
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  • extract_claims

    groundcheck

    PURPOSE: Split text into independently checkable ATOMIC factual claims — the cheap first step of a verification loop (extract -> ground -> attest). Returns {claims: [...], count, input_sha256} plus a signed receipt bound to the input hash. GUIDELINES: Call when you want to see WHICH claims a document makes before paying to ground them, to budget a verification pass (extract everything, then verify_claim only the claims that matter to your decision), or to prove later exactly which claims were pulled from exactly which text (the receipt binds both). Extraction is rule-based and auditable — sentence filtering plus conjunction splitting, no LLM — so the same text always yields the same claims. Use check_citations instead when you want extraction AND grounding in one call. PARAMETERS: text — the prose to decompose. max_claims — 1..50, default 20. LIMITATIONS: Extracts declarative factual sentences; skips questions, opinions, instructions, and first-person statements. Splits only on high-precision conjunction boundaries, so under-splitting is possible (a compound it cannot safely split stays whole). Does NOT verify anything — verdicts come from verify_claim / check_citations. Paid per call (x402), cheapest tool on this server. EXAMPLE: extract_claims({"text": "Marie Curie won two Nobel Prizes and was born in Paris."}) -> {count: 2, claims: ["Marie Curie won two Nobel Prizes", "was born in Paris."]}
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  • compare_pdfs

    KDAN PDF

    MANDATORY for all document comparison requests. Compare two PDFs side-by-side. When the user asks to compare, diff, or find differences between two PDFs, you MUST call this tool — NEVER attempt to compare documents using text analysis. Displays an interactive side-by-side visual diff widget with colored highlights: red = deleted, yellow = replaced, green = inserted. The widget IS the comparison result — do NOT re-summarize the differences after calling. Before calling, confirm both job_ids exist via check_upload_status.
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  • get_pdf_info

    KDAN PDF

    Use this when you need to read the text content of each page to decide which pages to delete. Returns page count and a text preview of every page. Use for text-based identification: table of contents, blank pages, cover page, etc. For visual content (logos, images, photos), use get_pdf_page_images instead.
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  • image_alt_text_pack

    Friday Seller Tools

    A deterministic alt-text, SEO-caption, and filename pack for up to 12 supplied marketplace gallery image descriptions. PAID SKILL: $0.25 USD per call; this server never runs paid work for free, and calling this tool returns payment instructions only. Pay per call with x402 (POST https://friday-seller-tools-production.up.railway.app/v1/marketplace-images/alt-text-pack and settle the 402 challenge in USDC) or buy with a card at https://friday-seller-tools-production.up.railway.app/buy?service=image_alt_text_pack. Free sample output: https://friday-seller-tools-production.up.railway.app/v1/examples/image_alt_text_pack.
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  • page-extract

    URL to clean article markdown/text + metadata and links. Deterministic. $0.001/call via x402.

  • extract

    Web content extraction for AI agents. Pay per call with x402 (USDC on Base). No API key.

  • watermark_detect

    studiomcphub

    Detect and extract invisible DCT watermark from an image. Returns the embedded text payload if found. FREE. (FREE)
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  • match_voice

    hooklayer

    Extract a creator's voice DNA from reference samples and rewrite a draft in their style. Requires at least 3 reference samples (video URLs or text). Returns voice profile (energy, humor, vocabulary, signature phrases), reusable prompt instructions, and the rewritten draft. Use when the user wants to write in another creator's style or match a specific voice.
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  • web_url_reader

    Inferventis — Financial Data, News & Web MCP

    Fetches any public web page and returns clean, readable plain text stripped of HTML, navigation, scripts, advertisements, and boilerplate. Returns the page title, meta description, word count, and main body text ready for analysis or summarisation. Use this tool when an agent needs to read the content of a specific web page or article URL — for example to summarise an article, extract facts from a page, verify a claim by reading the source, or convert a web page into plain text to pass to another tool. Pass article URLs returned by web_news_headlines to this tool to read full article content. Do not use this tool to discover current news headlines — use web_news_headlines instead. Does not execute JavaScript — best suited for standard HTML content pages. Will not work with paywalled, login-protected, or JavaScript-rendered single-page applications.
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  • files_read

    DialogBrain

    Read **text content** of an attached file. Works for: .txt, .md, .json, code files, and PDFs (after files.ingest extracts text). DO NOT call on binary files — for IMAGES use `files.get_base64`, for AUDIO/VIDEO it cannot be transcribed via this tool, and for non-PDF DOCUMENTS run `files.ingest` first, THEN files.read. Calling on a binary mime-type returns an error — saves you a turn to read the routing hint before deciding.
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  • files_get_base64

    DialogBrain

    Download one or more files server-side and return their content as base64-encoded strings. Use this to inspect images, PDFs, or any binary file attached to messages when you cannot access presigned S3 URLs directly. Supports up to 5 files per call, max 15 MB each. For large files batch in groups of 1-2 to avoid oversized responses.
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  • messages_send

    DialogBrain

    Send a message to a thread, channel, or contact. Supports Telegram, Email, LinkedIn, and other connected channels. For LinkedIn posts (comment_thread kind), this posts a comment on the post. Can automatically resolve recipients and channels when not specified. Can send files/images/documents as attachments — pass `attachments=[file_id, ...]` with integer file IDs obtained from collections.list_files, search.files, or files.search. `text` is optional when attachments are provided.
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  • web_fetch

    DialogBrain

    Fetches a single URL and returns its content. Use this when you have a specific URL in mind — for example, after web.search returns a link you want to read, or when the user pastes a URL. Modes (extract): - 'auto' (default): picks the right mode based on response content type. - 'markdown': for HTML pages; returns cleaned markdown plus the page <title>. - 'text': for JSON/XML/plaintext APIs; returns the raw decoded body. - 'file': for images, PDFs, audio, video, archives, or any binary — ingests the bytes into the user's file storage and returns a file_id you can pass to messages.send (to send as an attachment), agents.add_file (to add to agent knowledge), or files.read. Use web.fetch (not files.upload) when you need the file_id immediately for the next tool call — files.upload(source_url=…) is async and won't have the file ready in the same turn. Use web.search (not web.fetch) when you don't have a specific URL yet and need to find one.
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  • list_my_assets

    switch

    Return asset METADATA only (id, truncated prompt, model, created date), newest first. This does NOT display images and must NOT be used to show pictures — if the user says "show me / display my last image(s)", call show_media instead (it renders them; pass count=N for several). Use list_my_assets only when you need ids/metadata for another tool (e.g. move_asset) or a plain text list.
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