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510,032 tools. Updated 2026-09-03 17:32

"A tool for reading PDF files" matching MCP tools:

  • Convert a PDF into structured content (tables, charts, formulas, headings, body text) using a two-stage pipeline (layout detection, then a vision-language model) rather than a single VLM call on the raw PDF -- calling a VLM on a raw PDF directly is a known-unreliable pattern for numeric tables. Measured accuracy (500-page real-world benchmark of government/corporate reports, ~51,000 table values checked): tables 95.2% digit-exact, body text 88.8%. This tool reads PDFs a VLM cannot read directly, including scanned pages and PDFs with corrupted/garbled text layers (common in older Japanese academic PDFs). For scanned Japanese documents the numbers hold up (99.4% on the same benchmark). For scanned Arabic, body text does NOT: characters are dropped mid-sentence and quantities can turn into different quantities, so body blocks from scanned Arabic are always flagged confidence:"estimated" -- tables in the same documents stayed exact in our measurement. Strong on Japanese-language documents specifically; the accuracy figures above were measured on Japanese material and are not a claim about every language. Chart values are extracted but are best-effort estimates (about 52% exact match, excluding axis tick labels) and are always flagged confidence:"estimated" in the result -- do not treat estimated chart numbers as authoritative. This is a PAID, ASYNCHRONOUS, per-page-billed operation: credits are reserved from the caller's PDFIntact balance before processing starts, and the response's _meta.credits_remaining shows the balance right after reservation. Processing takes real wall-clock time (roughly 7 seconds/page; a 500-page PDF takes about 42 minutes including a multi-minute cold start), so this tool returns a job_handle immediately without waiting -- call get_result with that job_handle to poll for completion instead of calling convert_pdf again. Always pass idempotency_key; reuse the exact same value if you retry the same request, otherwise retries can double-charge and double-process. Provide the PDF either as a public https URL (source.type="url", up to ~200MB) or inline base64 (source.type="base64", up to ~20MB) -- prefer the URL form for large files. Requires sign-in (OAuth): this session is not authenticated, so calling this tool will fail until the PDFIntact account is connected and authorized.
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  • 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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  • Drill into a specific URL after search surfaces it. Returns the extracted text content plus metadata. Internal routing: PDFs hit Anthropic Files API for OCR + structured extraction; HTML pages are fetched + text-extracted via readability-style stripping. Use for: verifying a verbatim quote from a Reddit thread, reading a primary source in full (earnings transcript, research paper), drilling into a vendor product page after search surfaced the URL. NOT for: discovering new URLs — use search/search_community/search_research first. This tool takes a known URL only. Optional max_chars 100-50000, default 8000. SSRF-protected: private IPs + localhost blocked.
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  • Convert HTML or Markdown to a pixel-perfect PDF. Returns JSON: { url } — a temporary download URL (valid ~1 hour). Great for generating invoices, reports, receipts, or formatted documents programmatically. Supports full HTML/CSS including tables, images (base64 or URL), and inline styles. For Markdown input, set format='markdown'. 50 sats per conversion. Use convert_file instead for converting existing files between formats (e.g., DOCX→PDF). Pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='convert_html_to_pdf'.
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  • List knowledge files and folders for this company (names, slugs, sizes, folders). search matches file NAMES only — not body text. Read a body with read_knowledge by slug. Always-on files live in canon/ (injected into chat and skill gen within a size budget); everything else is on-demand via read_knowledge. Use when discovering what knowledge exists before reading a file.
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  • Display an interactive PDF upload widget directly in the chat. Use this when the user wants to upload a local PDF file from their device. This is the standard upload method for MCP clients (e.g. Claude) where file attachments with download URLs are not available. Do NOT call upload_pdf when using this tool — the widget handles the upload automatically. The widget renders inline and the PDF viewer appears after the user selects a file. Do NOT call view_pdf after this tool; the widget manages the UI. Never tell the user the file is still uploading; the widget handles the spinner. After the user uploads via the widget and notifies you, call check_upload_status(session_id=<session_id>) to discover the uploaded file and its job_id before proceeding with any operation.
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  • Render a Markdown resume to a finished PDF using a ResumeMD template (default: classic — see list_resume_templates for all 32 ids). Returns JSON with a base64-encoded PDF and a suggested filename; decode the base64 to give the user the file. The PDF is generated in memory and never stored. For interactive editing, template switching, and color choices, send the user to resumemd.pro/editor instead.
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  • Use to find where something appears across a board's text files in ONE call, instead of reading files one by one: give a literal string (a net name, a reference designator, a part number, a footprint) and get back the file, line number and matching line for each hit. Optionally restrict to a file extension with path_suffix. Matching is literal and case-insensitive, not a regular expression. Prefer read_schematic for how a design is wired and query_design for a file's structure; use this when you need to locate something by name.
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  • Converts a document to markdown or plain text: pass a public URL or the file itself as base64, and get back the content with headings, tables and lists preserved, at a fraction of the tokens that rendered pages cost. Use it when a harness has no native reader for the format — .docx, .xlsx, .odt and .numbers rarely have one — when a document is only a URL away, or when a long PDF's text matters and its layout does not. Handles PDF (.pdf), Word (.docx), Excel (.xlsx, .xlsm, .xlsb, .xls), OpenDocument (.odt, .ods), Apple Numbers, CSV, HTML, XML, and plain-text formats such as .txt and .md. The format is detected from magic bytes, not trusted from the file name, so a PDF served from a .php URL still converts. Two honest limits: a scanned PDF with no text layer has nothing to extract (this is conversion, not OCR), and legacy binary .doc and .ppt files are not readable — resave them as .docx or .pptx. Images are refused rather than described. Documents up to 10 MB.
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  • Parse one supported document into markdown, HTML, links, summary, targeted answers, or JSON matching a schema. Supported inputs include common HTML, PDF, Word, RTF, OpenDocument, and spreadsheet files; PDF parsing can be bounded with `pdfOptions.maxPages`. Local MCP reads `filePath` from the server filesystem. Hosted MCP uses two calls: first provide `filePath` to receive upload instructions, upload locally, then call again with the returned `uploadRef`; do not send both fields together. Remote web URLs belong in `firecrawl_scrape`. Set `redactPII` to request redaction of personally identifiable information in the returned content. `zeroDataRetention` requires an eligible authenticated account; omit it for anonymous keyless use. Returns upload instructions for hosted phase one or parsed document content for the final call.
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  • Convert any document to another format without storing a template. Supports 100+ input/output format combinations: Office documents, PDFs, images, web pages, spreadsheets, and more. The source file can be a local path, a URL, or a base64 string. Carbone tags are PRESERVED, not resolved: converting a template keeps every {d.field} intact, so this is also how you proof a template in another format (DOCX template → PDF, or DOCX → ODT while it stays a template). Use render_document instead when you need data injection ({d.field} tags resolved), translations, or batch generation. Common conversions: DOCX → PDF (file: "report.docx", convertTo: "pdf"; add converter: "I" for the fastest DOCX→PDF path), XLSX → PDF (file: "data.xlsx", convertTo: "pdf"), PPTX → PDF (file: "slides.pptx", convertTo: "pdf", converter: "O" for best fidelity), HTML → PDF (file: "page.html", convertTo: "pdf", converter: "C" for full CSS/JS rendering), DOCX → HTML (file: "doc.docx", convertTo: "html"), XLSX → CSV (file: "sheet.xlsx", convertTo: "csv"), PDF → PNG (file: "doc.pdf", convertTo: "png"), PPTX → PNG (first slide as image), MD → PDF (file: "readme.md", convertTo: "pdf").
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  • Get a USGS site's current reading ranked against its full period-of-record daily-mean percentiles for the same calendar day — a "how unusual is this" percentileClass (record-high to record-low), not a flood-stage or drought determination (this tool fetches no authoritative thresholds). The reading is instantaneous but the percentiles are daily-mean, so the ranking is approximate (see historicalContext.comparisonBasis). When the record is too short to rank, returns the reading with historicalContext=null instead of an error. Use water_find_sites and water_list_parameters to resolve inputs.
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  • Upload multiple PDF files from ChatGPT file attachments. Use this when the user provides multiple file attachments in ChatGPT. Downloads each PDF from its signed URL and stores it. Returns session_id and a list of job_ids. Like upload_pdf, this ONLY works on hosts that resolve chat attachments for you (ChatGPT). On Claude and other MCP clients, call create_upload_page instead. Never invent or guess a download_url or file_id. MANDATORY WORKFLOW before calling this tool: 1. ALWAYS call check_upload_status FIRST — even if you think the files are new. 2. Only include files confirmed absent from check_upload_status. If ALL files are already uploaded, skip batch_upload_pdf entirely and reuse the existing job_ids. 3. Reuse job_ids from already_uploaded — do NOT re-upload those files. Skipping step 1 and calling batch_upload_pdf directly is FORBIDDEN. After batch_upload_pdf completes: if the user requested a comparison, call 'compare_pdfs' with the returned job_ids immediately.
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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. Use the photo parameter for one image or PDF attached in ChatGPT. MCP clients that cannot supply file references may use photoBase64 for one small image; use the upload flow for large files or batches. 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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  • Convert HTML and CSS to a PDF document using the WeasyPrint rendering engine. Supports every PDF/A archival level, PDF/UA accessibility and the PDF/X print standards. Best for professional documents: invoices, reports, certificates, contracts, and accessible documents. Also produces **fillable PDF forms** — set pdfForms to true. Send a complete HTML document including <html>, <head> with <style>, and <body> tags. Page geometry comes from the document's own CSS @page rule unless paperSize or orientation is set explicitly. Returns a temporary download URL for the generated PDF (valid for 30 minutes). Requires a paid PdfBroker.io plan (Starter or above). EU-first defaults: A4 paper, Portrait orientation when neither the document nor the caller says otherwise.
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  • Step 4 of the Tango working agreement (work in the open). Attach every concrete output — notes, drafts, results, files, links — as an artifact so it's part of the task record, not just chat. Real files (pdf, docx, pptx, xlsx, mp3, wav, m4a, images…) are supported: pass `content_base64` for files up to ~6 MB, `fetch_url` to have Tango download and store a hosted file itself, or call create_artifact_upload first for large files and finalize here with `upload_token`. `content` stays the path for inline text and `external_url` for a link you only want recorded. Reference artifact ids in complete_task's evidence_artifact_ids. If a lease is active, Tango attributes the artifact to the lease holder. Otherwise, pass `acting_worker_id` to identify which of your workers is acting; if you don't own that worker the attribution is dropped rather than misrecorded. Attested workers may pass `worker_signature` over the JCS-canonical artifact payload (type 'tango.artifact'); an invalid signature rejects the call and nothing is stored. Delegated workers are signed for automatically.
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  • Prepare a paid PDF render from arbitrary Handlebars-flavoured HTML. Use only when no starter fits (one-off layouts, custom branding). Prefer render_template_to_pdf when a starter matches. Validates your HTML and returns the exact, ready-to-execute HTTP request to run against pdfzen's render endpoint — POST /v402/render/pdf (x402, $0.006 USDC on Base, no API key) or POST /v1/render/pdf (pdfzen API key). pdfzen renders are executed over HTTP, not streamed in-band over MCP; this tool is the bridge.
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  • Upload assets for PowerPoint (.pptx) generation: company template, logo, image, or document — or AI-generate an image. Purposes: • logo — company logo for chrome (PNG/JPG/SVG, max 5MB) → logo_id • image — image for the Image component (max 10MB) → asset_id • theme — company template PPTX → theme_id; slides with it render NATIVELY on the template (masters/layouts/chrome) • generate_image — AI-generate via `prompt` → asset_id ($0.05) • translate — PPTX to translate → deck job_id ($0.02/slide; requires `target_language`) • pdf — PDF → editable slides; pass `target_language` to also translate • recreate — image OF a slide → editable PPTX slide ($0.10; honest annotate/preserve fallback, refusals free). Use `image` to just place a picture Files >3MB (pdf/translate/theme) — and recreate on chat hosts — omit `data`: a drop-zone appears in the result card; bytes never pass through the agent.
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  • Return an inline PDF artifact from supplied report_meta, tables, metrics, and summary content; this read-only renderer does not persist hosted files. Use this only when a structured report payload already exists; use report_docx_generate for editable Word output or compliance_edd_report to build the memo first.
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  • Create a FreeSign envelope from a PDF SHA-256 hash. Do not send PDF bytes. The created envelope is NOT yet session-bound — the browser that opens the returned signing_url generates an ECDSA P-256 keypair locally and POSTs the public JWK to /api/envelopes/{id}/session-bind before any protected request will succeed. AI agents calling this tool just hand the signing_url to a human, who continues in a browser.
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