"Sublime Text" matching MCP tools:

• redact_text

  mcp

  Use this when scrubbing test/dev text: replaces each occurrence of the given terms with block characters (████). Provide `text` plus `terms` (a comma-separated string or an array of strings). By default it matches whole words only using Unicode boundaries (so "ann" will not match inside "annual") and is case-insensitive; set `caseSensitive` to match exactly, `wholeWords: false` to match substrings, or `fixedWidth: true` to hide each term's length behind a constant-width bar. Returns the redacted text and a replacement count, and never echoes the original terms. Deterministic: same input, same output. Truly sensitive text is better redacted client-side at clean.tools/text-redact/. Example: {text: "Contact Jane Doe", terms: "Jane Doe"} -> redacted "Contact ████████", redactedCount 1.

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• url.extract

  DocImprint

  Fetch a public HTTPS URL and return extracted text and page metadata. Lean mode — no evidence bundle stored, no bundle_id returned. Use for raw text extraction from web pages and online documents. Use url.summarize for summaries, url.qa for Q&A, url.translate for translation, document.extract_text for base64 file uploads. Returns: { url, title, word_count, text, final_url (after redirects) } Example prompts: - "Extract the text from https://example.com/report.pdf for me." - "Get me the raw content of this web page: [URL]." - "Pull the text from this online article so I can analyze it."

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• url.extract

  api

  Fetch a public HTTPS URL and return extracted text and page metadata. Lean mode — no evidence bundle stored, no bundle_id returned. Use for raw text extraction from web pages and online documents. Use url.summarize for summaries, url.qa for Q&A, url.translate for translation, document.extract_text for base64 file uploads. Returns: { url, title, word_count, text, final_url (after redirects) } Example prompts: - "Extract the text from https://example.com/report.pdf for me." - "Get me the raw content of this web page: [URL]." - "Pull the text from this online article so I can analyze it."

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• redact_by_text_range

  KDAN PDF

  Redact PDF text by specifying the exact text to remove on each line. MANDATORY WORKFLOW — follow every step in order before calling this tool: Step 1 — Retrieve line text: Call list_redactable_line_text and note the exact 'text' string and 'line_index' for every line you intend to redact. Step 2 — Identify the text to redact: Provide the exact substring to remove. The value must appear verbatim in the line's 'text' field. - Non-CJK text (e.g. English): whole-word matching is enforced. "the" will NOT redact text inside "then", "there", or "either". - CJK text (e.g. Chinese): substring matching — "王大明" will match wherever it appears in the line. Step 3 — Build the content payload: Group redaction targets by page. Each page entry contains a list of { line_index, text } pairs. Example: content = [ { "page_index": 1, "lines": [ {"line_index": 3, "text": "John Doe"}, {"line_index": 7, "text": "confidential"} ] } ] Step 4 — Verify and re-redact if needed: After this tool returns, you MUST call list_redactable_line_text again with the NEW job_id to verify that all intended targets have been removed. If any target text still appears in the result, call redact_by_text_range again immediately with the remaining targets. Repeat until all targets are gone — do NOT report success until the verification confirms zero remaining targets. Creates a NEW job_id (with parent_job_id linking to the source). After redaction completes, call 'view_pdf' with the new job_id to display the result.

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• document.extract_text

  api

  Extract plain text from a PDF or image (base64-encoded). Use when you need raw text for downstream AI analysis (summarization, claim checking, structured extraction). For documents at a public URL, use url.extract instead (no base64 encoding needed). Returns: { pages: number, text: string } Example prompts: - "Extract the text from this scanned contract so I can search it." - "Give me the raw text from this PDF document." - "OCR this image and return the text content."

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• get_maude_report

  Scite

  Fetch full details for a single MAUDE adverse event report by ID. Use this after `search_maude` when you need the complete record for a specific report, including the full narrative text (MDR text with text type codes), reporter information, device availability, patient treatment, and tags. The search tool returns truncated text snippets; this tool returns the full narratives which can be much longer. **Parameters:** - id: MAUDE report ID (e.g. `17343805`). Obtained from search_maude results. **Returns:** A detailed MAUDE report with full narrative text entries (with text type codes like "Description of Event or Problem"), reporter occupation, health professional flag, device medical specialty and availability, patient treatment, product problem flag, and tags.

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• export_search_csv

  MCP Market Russia

  Export search results as CSV text (UTF-8 with BOM, Excel-friendly). entity: 'companies' or 'projects' query: free-text search in name/description category, region: filter fields budget_max: for companies, cap on min_project_price limit: 1..2000 rows (default 500) Returns CSV text ready to save as .csv and open in Excel.

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• read_pdf

  docweave-mcp

  Read a PDF and return its text as markdown (or plain text). Accepts a public URL or base64 bytes. Extracts the embedded text layer; a scanned, image-only PDF returns a needs-OCR notice instead of empty text. Priced per document; retries with the same idempotencyKey never double-read. The canonical way for an AI agent to ingest a document's contents.

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• list_change_requests

  PinAppAI

  List change requests for a project with filters + cursor pagination. Defaults to include=['change_requested'] (highest-signal subset). Returns digest fields per row (including element_kind=text|mixed|field|null and suggested_text — a literal text replacement on text/field picks); no inline images at this tier (token-cheap by design). Use get_change_request for full detail + screenshots.

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• fluxink-mcp-chatgpt-recognize-image

  fci-mcp

  FluxInk image text recognition. Extract text from an EXISTING image (file upload, URL, or base64) the user provides. Higher accuracy than built in vision for tightly packed text, multi language documents, math, and LaTeX. Returns per region confidence and detection coordinates. Use this when the user uploads, attaches, or shares an image containing text they want extracted (screenshot, photo, scanned document, receipt, sign, whiteboard, book page, photographed handwritten notes). Use this when the user wants a photographed math expression or chemistry formula converted to LaTeX. Use this when the user references an image and asks to read, transcribe, or digitize the text in it. Do NOT use this when the user has NOT provided an image yet. Do NOT use this when the user wants to draw or handwrite something fresh (call show_handwriting_canvas instead). Do NOT use this when the request is a plain text question, summary, or explanation with no image attached. The language parameter selects the recognition mode. en is English text (default). zh is Chinese text. paddle is multilingual or mixed text. formula is mathematics. latex returns raw LaTeX markup. After returning results, present the extracted text clearly and offer follow up actions like translation, summarization, or editing.

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• add_elements

  Canvs

  Creates elements on a canvas. Creates a new canvas if room_id is omitted, or adds to the existing canvas if room_id is provided. Use cases: wireframes, UI mockups, freeform illustrations, standalone shapes, and manual layouts that Mermaid does not cover well. For diagrams Mermaid can express, use add_elements_from_mermaid instead. Element types: rectangle, ellipse, diamond, arrow, line, freedraw, text, image. Rich text: the text field supports limited HTML for text elements and rectangle/ellipse/diamond shape labels. Supports the rich-text plugin HTML subset: <b>/<strong>, <i>/<em>, <u>, <br>, <div>/<p>, <ul>/<ol>/<li>, <a href>, <font color>, and <span style="color, background/background-color, font-size, font-family">. Use textAlign for left/center/right alignment; avoid unsupported HTML/CSS. TEXT IN SHAPES: use containerId on text element pointing to shape id. ARROWS: Position at EDGE of source shape. Auto-bound within 30px. Colors: strokeColor, backgroundColor (hex).

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• translate

  MapleFlow

  Translate text between 75+ languages with auto-detection. Supports dynamic pricing based on text length.

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• lookup_qr_code

  GoCreative Agent API

  Generate a QR code data URL for arbitrary text. Pass ?text=... as query. Use for print, signage, ticketing agents. Example call: {"query_string": "text=https://api.gocreativeai.com"} Cost: $0.005–$0.05 USDC on Base per call.

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• read_brand_document

  Heista

  Read one indexed brand document. Returns the indexed metadata (doc_type, summary, key_topics, entities, key_quotes) plus the document content, routed by mime: text/markdown, text/plain, text/csv are inlined as text; application/pdf and other text-shaped mimes return an Anthropic Files API file_id (attach via document source { type:"file", file_id } on the next turn); DOCX/PPTX/XLSX return a requires_code_execution marker (caller must enable code_execution_20260120 and attach via container_upload). Use AFTER list_brand_documents to pick the right document. Free, read-only.

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• twitter_transcript

  captapi

  Extract tweet text as transcript text. Costs ~1 credit; cached results are free, failures are never charged.

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• get_change_request

  PinAppAI

  Full detail for one change request. Returns the CR (including element_kind=text|mixed|field|null and suggested_text — a literal text-replacement the reviewer typed when picking a text/field element), plus related[] (other CRs on the same selector + same page) so you can detect patterns from a single fetch. Set include_image=true to embed the screenshot inline as an MCP image content block. When suggested_text is non-null on a text/field pick, paste it verbatim — do not interpret or rewrite. When element_kind=mixed, the element contains more than text (icons/images/structure) — rely on the comment + screenshot, not just the visible text.

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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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• get_voices

  Text to Speech Voiceover

  Retrieves a comprehensive list of available Text to Speech voices used for generating audio voiceovers. You must call this tool first to obtain the required voice object before you can generate any Text to Speech audio. You can optionally filter the voices by providing a Language_code.

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• search_documents

  UAPDrop Research Archive

  Full-text search of the declassified UAP/UFO document archive (Project Blue Book, FBI Vault, national archives, and other government releases). Searches title, summary, incident text, tags, and extracted PDF text. Covers documents only: witness interviews, documentaries and commentary live in the video corpus — run search_videos as well when researching a person, incident or topic.

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• base64_decode

  Agent Bits

  Decode a Base64 string into UTF-8 text and report invalid payloads as errors when recovering embedded credentials, tokens, or transport-encoded content. Use when: - Decode this Base64 string to UTF-8 text - Recover plain text from a Base64-encoded payload - Check whether a Base64 string is valid and decode it Do not use when: - Encode plain text to Base64 (use base64_encode) - Decode percent-encoded URL components (use url_decode) - Decrypt ciphertext—Base64 decoding is not decryption

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