"Tools and methods for extracting text from PDF files" matching MCP tools:

• prefetch_datasheets

  sheetsdata-mcp

  Trigger background datasheet extraction for multiple parts at once (up to 20). Non-blocking — returns immediately with the status of each part. Use this to warm up datasheets for a BOM before calling read_datasheet. Example: prefetch_datasheets(['TPS54302', 'ADS1115', 'LP5907']) If a part comes back 'no_source' on the first call, retry prefetch for that MPN once after 10-30s — the URL resolver is retriable and often finds a source on the second pass. If still 'no_source', use request_datasheet_upload + confirm_datasheet_upload to attach your own PDF (org-private). Part numbers must be specific MPNs (e.g. 'STM32F446RCT6', 'TPS54302DDCR') or LCSC numbers (e.g. 'C2837938'). Do NOT pass bare values ('100nF', '10K'), descriptions, BOM reference designators, test points, or board/module names — see the server instructions for the full rule set. When a BOM has values-only rows, use search_parts first to resolve each to an MPN. DATASHEET STATUS VALUES: - 'ready' — extracted and indexed; call read_datasheet, search_datasheets, or analyze_image. - 'extracting' / 'in_progress' / 'queued' / 'pending' — extraction running or scheduled. Poll check_extraction_status every 5-10s until 'ready' or 'failed'. Typical time: 30s-2min. - 'not_extracted' — known part but datasheet hasn't been fetched yet. Trigger it via prefetch_datasheets (cheapest) or by calling read_datasheet (auto-triggers on first read). - 'no_source' — we couldn't find a public datasheet URL for this MPN. First, retry prefetch_datasheets in 10-30s (the URL resolver re-runs and often finds a source on the second pass). If still 'no_source', the agent can upload the PDF manually via request_datasheet_upload + confirm_datasheet_upload (see those tools). Org-uploaded datasheets are private to the org. - 'unsupported' — PDF exists but can't be extracted (scanned image-only, encrypted, or corrupted). Upload a clean text-based PDF via request_datasheet_upload to override. - 'failed' / 'error' — extraction errored. The response includes the error reason. Retry via prefetch_datasheets or escalate to support. - 'rejected' — input wasn't a real MPN (bare value like '100nF', description, or reference designator). Fix the input and re-call. - 'deduplicated' — another part in the family already has this datasheet; same content is returned under the primary MPN.

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• document.summarize

  api

  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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• create_attachments

  ProWoDo

  Create an attachment on a company or one of its projects. Provide exactly ONE of: `text` (stored as a text/markdown file), `content_base64` (base64-encoded binary — `content_type` is required alongside it), or `link` (an http(s) URL, e.g. Google Drive/Figma/a web page). `file_name` is required for `text` and `content_base64`. Inline content (`text`/`content_base64`) is capped at 4 MB — for larger files, upload to Drive and pass the URL as `link` instead. `project_id` is optional: omit it to attach to the company itself rather than to a project. Allowed file types: images, PDF, plain text, CSV, Office documents and zip. Each attachment carries app_url, a deep link to its project's attachments page — null for company-level attachments, which have no dedicated page.

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• check_extraction_status

  sheetsdata-mcp

  Check the extraction status of one or more parts. Free. Each entry includes the current extraction step, elapsed seconds, and document ID. Use after prefetch_datasheets or after read_datasheet triggers a new extraction. Recommended polling cadence: every 5-10 seconds. Extraction typically takes 30s-2min for new parts, so polling faster than every 5s wastes calls. Stop polling once status is 'ready', 'failed', 'no_source', or 'unsupported'. DATASHEET STATUS VALUES: - 'ready' — extracted and indexed; call read_datasheet, search_datasheets, or analyze_image. - 'extracting' / 'in_progress' / 'queued' / 'pending' — extraction running or scheduled. Poll check_extraction_status every 5-10s until 'ready' or 'failed'. Typical time: 30s-2min. - 'not_extracted' — known part but datasheet hasn't been fetched yet. Trigger it via prefetch_datasheets (cheapest) or by calling read_datasheet (auto-triggers on first read). - 'no_source' — we couldn't find a public datasheet URL for this MPN. First, retry prefetch_datasheets in 10-30s (the URL resolver re-runs and often finds a source on the second pass). If still 'no_source', the agent can upload the PDF manually via request_datasheet_upload + confirm_datasheet_upload (see those tools). Org-uploaded datasheets are private to the org. - 'unsupported' — PDF exists but can't be extracted (scanned image-only, encrypted, or corrupted). Upload a clean text-based PDF via request_datasheet_upload to override. - 'failed' / 'error' — extraction errored. The response includes the error reason. Retry via prefetch_datasheets or escalate to support. - 'rejected' — input wasn't a real MPN (bare value like '100nF', description, or reference designator). Fix the input and re-call. - 'deduplicated' — another part in the family already has this datasheet; same content is returned under the primary MPN.

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• get_part_details

  sheetsdata-mcp

  Get full details for a specific electronic component by manufacturer part number (MPN) or LCSC number. Returns specs, pricing, and stock from all configured providers, plus the cached datasheet summary if available. Includes datasheet_status and available_sections when ready. Set prefetch_datasheet=true to trigger background extraction — no extra charge. Use after search_parts to drill into a specific result. The part_number must be a specific manufacturer part number (e.g. 'TPS54302DDCR', 'STM32F446RCT6') or LCSC number (e.g. 'C2837938'). Do NOT pass bare component values ('100nF', '10K'), descriptions ('buck converter'), or reference designators ('R1', 'U3'). DATASHEET STATUS VALUES: - 'ready' — extracted and indexed; call read_datasheet, search_datasheets, or analyze_image. - 'extracting' / 'in_progress' / 'queued' / 'pending' — extraction running or scheduled. Poll check_extraction_status every 5-10s until 'ready' or 'failed'. Typical time: 30s-2min. - 'not_extracted' — known part but datasheet hasn't been fetched yet. Trigger it via prefetch_datasheets (cheapest) or by calling read_datasheet (auto-triggers on first read). - 'no_source' — we couldn't find a public datasheet URL for this MPN. First, retry prefetch_datasheets in 10-30s (the URL resolver re-runs and often finds a source on the second pass). If still 'no_source', the agent can upload the PDF manually via request_datasheet_upload + confirm_datasheet_upload (see those tools). Org-uploaded datasheets are private to the org. - 'unsupported' — PDF exists but can't be extracted (scanned image-only, encrypted, or corrupted). Upload a clean text-based PDF via request_datasheet_upload to override. - 'failed' / 'error' — extraction errored. The response includes the error reason. Retry via prefetch_datasheets or escalate to support. - 'rejected' — input wasn't a real MPN (bare value like '100nF', description, or reference designator). Fix the input and re-call. - 'deduplicated' — another part in the family already has this datasheet; same content is returned under the primary MPN.

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• create_powersource_docs

  Heista

  Build a complete creative intelligence profile from internal brand documents — creative briefs, brand guidelines, product specs, customer research, competitive analysis. Takes any mix of file_ids (from a previous upload), document_urls (public PDF/DOCX/TXT/MD links, up to 10), or documents_inline (base64-encoded files with filename), plus an optional context_url for layering live brand context (colors, fonts, current messaging) and optional idempotency_key. Returns a job_id; poll with get_powersource. Output shape is identical to create_powersource_url: identity, offer, selling points, voice, buyer profile, tensions, angles, emotional arcs, ctas, narrative. Use this when the user says "I have a brief", "here's my brand guidelines", "use this document", drops a PDF / DOCX / strategy deck, or when the truth lives in internal materials rather than the public website. The pipeline reads text only — convert PDFs to markdown before submitting via documents_inline when possible. Costs 100 credits. Do NOT use for URL-only scans — use create_powersource_url. For URL + docs combined (highest fidelity, triangulates public messaging against internal strategy), use create_powersource_full.

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• parse_pdf_to_text

  Nordic Financial MCP

  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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• document.summarize

  DocImprint

  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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• url.translate

  api

  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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• get_site_files

  Just Publish

  Read the files of a site you already published, so you can make a targeted edit instead of rebuilding the whole site from memory. Returns a complete manifest (every file's path, size, content-type, sha256) plus the contents of the text files (HTML/CSS/JS/etc). Also returns the site's current `version` — pass it back to update_site_file so you don't overwrite a newer change. Pass `paths` to fetch only specific files; omit it to get all text files. Requires site_id + edit_token.

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• convert_html_to_pdf

  Sats4AI - Bitcoin-Powered AI Tools

  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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• scaffold_service

  @imqueue

  READ-ONLY: returns generated source code as text and writes nothing to disk, creates no project and runs no command. Generates an idiomatic @imqueue/rpc service (an IMQService subclass with @expose()d, JSDoc-typed methods) plus a bootstrap that starts it. Provide the methods you want, or omit them for a starter template. Any non-primitive parameter or return type also gets a types.ts with the required @classType()/@property() declarations — without those the generated client types it `any`, which compiles. Use create_service (local install only) if you want files actually written.

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• pdf_merge

  APICK

  Merge two PDF files into one. 두 개의 PDF 파일을 순서대로 하나의 PDF 파일로 합쳐 반환합니다. PDF 형식의 파일만 허용됩니다. [호출당 2포인트]

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• deploy_app

  AppDeploy

  Deploy or update a website or web app to get a public URL. Text files only in files[]. files[] must be a JSON array, even for one file. Example: files: [{"filename":"src/App.tsx","content":"..."}]. Never pass a bare string or a single file object. Use files[] for inline text edits and diffs, not for copying large existing local file contents into tool params. Never inline or base64-encode binary assets/resources in files[]; use upload_assets first for images, fonts, media, PDFs, archives, and other client-supplied file assets, then pass upload_id. Inline deploy_app text payloads MUST be compact. For JavaScript/TypeScript/JSX/TSX string literals, use single quotes wherever valid. Keep inline HTML/CSS/JS/TS diff from/to values single-line wherever valid; do not include newline characters unless required for valid syntax. Template files from get_app_template are auto-included as the baseline — use diffs[] to modify them; content is otherwise only for entirely new files. New apps: tests/tests.txt is the intentional template-file exception and must be sent as a complete content replacement. New apps: set app_id to null, provide app_name, description, app_type, frontend_template, and features. Updates: provide existing app_id, features, and either changed files/deletePaths or upload_id. If upload_id is provided, do not also send files[] or deletePaths[]; the upload manifest owns all text changes, diffs, and delete operations. Rules: do not add @appdeploy/client or @appdeploy/sdk to package.json (platform-injected). SPAs must use HashRouter. Frontend must never import @appdeploy/sdk; backend must never import @appdeploy/client. Frontend must use api from @appdeploy/client for backend calls, never fetch() or axios. If frontend realtime is used, @appdeploy/client websocket usage is ws.connect() only; do not call ws.subscribe/ws.publish/ws.send directly on ws. After deploy, poll get_app_status every 5s until status is 'ready' or 'failed'. If get_app_status returns QA/e2e/runtime errors, attempt automatic fixes and redeploy up to 3 times before asking the user for guidance.

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• convert_content

  Botverse

  Convert a document inline — pass the content directly as a string (or base64 for binary inputs like .docx). PREFERRED route for documents, and the one to use in sandboxed agent environments (claude.ai, Claude Desktop, Cursor): it runs entirely server-side, so it never needs the S3 upload those sandboxes block. Limit: up to 4 MB of content — already huge (a 500-page book is ~1 MB of text). For anything larger, use convert_from_url with a public URL. Supported inputs: md, html, rst, txt (plain text), docx (base64). Supported outputs: docx (Word), pdf, html, txt, md, rst, xlsx. Returns a job_id — poll get_job_status until 'complete', then get_output_content (inline bytes, sandbox-safe) or get_download_url (S3 link). Flat fee $0.05 per file. TIP: if you have shell access and are NOT sandboxed (e.g. a local coding agent), the `botverse` CLI (`npx botverse convert <file> --to <fmt>`) is faster for local files — it streams from disk instead of re-emitting the content through the model.

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• search_parts

  sheetsdata-mcp

  Search for electronic components by part number, description, or keyword. Start here — this is the best entry point for finding components. Queries all configured providers in parallel. Results are merged by MPN with indicative pricing and stock from each source. Each result includes datasheet_status so you know which parts have datasheets available for read_datasheet. Best with specific part numbers or keywords (e.g. 'STM32F103', 'buck converter 3A'). For spec-based discovery in natural language, use search_datasheets instead. When the calling org has a private parts library, matching org-uploaded parts are appended to the results with source='private_library' and any tags the team has applied — including private parts whose MPN, manufacturer, description, type, category, or tag matches the query. DATASHEET STATUS VALUES: - 'ready' — extracted and indexed; call read_datasheet, search_datasheets, or analyze_image. - 'extracting' / 'in_progress' / 'queued' / 'pending' — extraction running or scheduled. Poll check_extraction_status every 5-10s until 'ready' or 'failed'. Typical time: 30s-2min. - 'not_extracted' — known part but datasheet hasn't been fetched yet. Trigger it via prefetch_datasheets (cheapest) or by calling read_datasheet (auto-triggers on first read). - 'no_source' — we couldn't find a public datasheet URL for this MPN. First, retry prefetch_datasheets in 10-30s (the URL resolver re-runs and often finds a source on the second pass). If still 'no_source', the agent can upload the PDF manually via request_datasheet_upload + confirm_datasheet_upload (see those tools). Org-uploaded datasheets are private to the org. - 'unsupported' — PDF exists but can't be extracted (scanned image-only, encrypted, or corrupted). Upload a clean text-based PDF via request_datasheet_upload to override. - 'failed' / 'error' — extraction errored. The response includes the error reason. Retry via prefetch_datasheets or escalate to support. - 'rejected' — input wasn't a real MPN (bare value like '100nF', description, or reference designator). Fix the input and re-call. - 'deduplicated' — another part in the family already has this datasheet; same content is returned under the primary MPN.

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• firecrawl_parse

  firecrawl-mcp

  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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• get_filing_extract_meta

  ca-rate-filings

  Lists **what's in** each extracted artefact for a filing — section counts, item names, and the page each item came from — without returning any of the bulky factor tables, descriptions, or rate rows themselves. **Call this FIRST**, before `get_filing_extracts`, for any "what does this filing contain" question. It costs a fraction of the tokens and tells you which file + which section you need to pull in detail. `get_filing_extracts` is then the targeted second call once you know the SERFF + file + section that actually answer the user's question. Use this when the user asks: - "What forms does this filing include?" / "List the form numbers in TSIS-134726605." - "How many exclusions does it carry? What are they called?" - "What rate tables are in this filing, and which PDF page are they on?" - "List the discounts / endorsements / coverages this filing offers." - "Where in the source PDF is the territory rate table?" - Any "how many", "what are the names of", or "which page is X on" question about a filing's extracted artefacts. Wrong surface for: - Anything that needs the actual numeric content (factor values, full rate rows, full exclusion text). Call `get_filing_extracts` instead, narrowing `files` to just the one(s) you discovered here. Whitelist (same as `get_filing_extracts`): - `calculations.json` — example rate-calculation walk-throughs. - `coverages.json` — coverage definitions (perils, limits, applicability). - `deductibles.json` — deductible options + factors. - `discounts.json` — discount / surcharge schedules. - `endorsements.json` — optional endorsements / riders. - `examples.json` — worked policyholder rating examples. - `exclusions.json` — coverage exclusions + the conditions they apply to. - `extraction_summary.json` — structured filing-overview fields. - `final_rating_calculation.json` — canonical rating expression. - `forms.json` — policy form numbers + types. - `rates_data.json` — base rates + rate-table headers. - `underwriting_guidelines.json` — eligibility / UW rules. Per item the tool returns `{ name, source_page? }`. The item name is picked from whichever identifying field exists (`name` → `form_number` → `id` → `key` → `code` → `coverage` → `label` → `title`). `source_page` is the page in the source PDF where the item was extracted from, when the pipeline recorded one. `rates_data.json` items additionally carry `source_file` — the source PDF the rate table lives in — when the filing has a single source PDF. Multi-source filings get `source_file_note` flagging the limit (per-item `source_file` on non-rate extracts needs a pipeline-side change, deferred). Args: `serff` (required), `files` (optional — pass a subset of the whitelist to narrow; omit for all 12). Returns: `{ serff, files: { "<name>": { file_name, filing_ref?, confidence?, sections: { "<key>": { count, items: [...] } }, total_items } }, count, skipped }`.

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• batch_upload_pdf

  KDAN PDF

  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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• voice_intelligence_run

  StackFast FractWin Expert Brain

  Run the voice intelligence orchestrator over any input: an uploaded or recorded audio/video file (base64 in file), a public audio or video URL (audio_or_video_url), a PDF (pdf), an image (image), or raw text/notes (text and/or notes). Provide exactly ONE input carrier — audio_or_video_url, file, pdf, image, or text/notes. The input is normalized to a transcript via the existing transcription rails, then three composed outputs are returned: a condensed summary (with action items, decisions, and a next step), a full-verbatim polished actual script (filler removed, wording preserved, never paraphrased; call sources return a masked summary instead), and an authority report (content flywheel plan, plus an owner-facing business report when business context is provided). All outward outputs are mask-gated.

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