"Generate Word documents" matching MCP tools:

• searchA

  Islam West Africa Collection (IWAC)A

  Search the Islam West Africa Collection across newspaper articles, Islamic publications, archival documents, academic references, audiovisual recordings, photographs, and the authority index (persons/places/organisations/events/subjects). Pass ONE concept or name — e.g. 'Tijaniyya', 'laïcité', 'Sheikh Gumi', 'pèlerinage'. Matching is accent- and case-insensitive; a multi-word query requires every word to appear somewhere in the item, so prefer a single concept per call. Write query strings and concept keywords in French for press/publication/document/index discovery even when the user's report language is not French. Academic references are multilingual, so try French and English title/abstract terms when relevant; metadata/filter labels remain French. Use the French transliteration of Islamic terms (Tabaski not 'Eid al-Adha', charia not 'sharia', Maouloud not 'Mawlid'). Returns {results:[{id,title,url,category}], ranking}; each result's `category` names its subset and the `ranking` field documents the ordering. Pass an id to `fetch` to read the full text. For filtered queries (by country, date, or newspaper) use the search_* tools instead.

  ConnectorNo auth

• word_createA

  local-mcpA

  Creates a new Word (.docx) document at `path` with the given text content (and an optional title rendered as the heading). Requires confirm=true — called without it, returns a preview of what will be written instead of creating the file. The path must be somewhere Local MCP can write; Desktop/Documents/Downloads may need a one-time Files-and-Folders grant (System Settings → Privacy & Security → Files and Folders). Returns {created, path}. For a OneDrive or Google Drive path use onedrive_write_file / gdrive_write_file; to append to an existing doc use word_append, to read one word_read.

  ConnectorNo auth

• verify_identityA

  Stipple — Document Verification & ExtractionA

  Run an Australian identity check over a SET of identity documents. A vision model reads each document (which ID it is, which fields it shows — name/photo/address/signature — and its issue date); a deterministic engine then tallies them against a scheme and reports whether identity is established, and exactly what's still missing if not. USE THIS WHEN someone needs to verify a person's identity from their documents — KYC / onboarding / "do these documents satisfy the 100-point check?" Pass ALL the person's documents together (a passport alone is 70 points; the check needs >= 100). `documents` is a list, each item ONE of: {"url": "https://..."} (public link, fetched server-side) or {"bytes_b64": "...", "filename": "passport.pdf"} (inline). Up to 10. `scheme`: "afp_100_point" (points, default) or "austrac_safe_harbour" (category combinations). Returns `{established, points/target or satisfied_path, documents[] (per-document: type, fields shown, whether it counted and why-not), reason, accepts, ...}`. This is identity COVERAGE, not a forgery judgment — run verify_document for authenticity. Documents are never stored. Costs 2 credit(s) per call.

  ConnectorNo auth

• list_canvasA

  AgentPlaybooksA

  List canvas documents in a workflow run. Canvas documents are collaborative markdown files that multiple agents can edit in parallel. Omit run_id to list documents across all runs. Read-only. Use read_canvas for content and get_canvas_toc for section IDs. There is no get_run; list_runs returns run records. Pass playbook_id as the UUID or GUID of the playbook this call should target.

  ConnectorNo auth

• word_appendA

  local-mcpA

  Appends text to the end of an existing Word (.docx) document at `path`, preserving the document's existing content and formatting. Requires confirm=true — called without it, returns a preview instead of modifying the file. Same file-access rules as word_create (Desktop/Documents/Downloads may need a Files-and-Folders grant). Returns {appended, chars_appended, path}. To create a new document use word_create; to read one use word_read.

  ConnectorNo auth

• search_documentsA

  OpenPublicaA

  Search adopted plan and budget documents, returning page-cited excerpts. Each hit's `text` is a short passage around the match, not the full page — call read_document_pages with the hit's `first_page` to read it in context. Every hit carries `first_page`/`last_page` and `source_url`. Quote those when citing: the page number is what makes the claim checkable against the city's own copy. This is word matching, not semantic search — try the terms a plan would actually use. Only currently-served documents are searchable, so an empty result is not evidence the government has no such policy; check list_government_documents for what is held and what could not be read. A hit with `document_complete: false` comes from a document with transcription findings. Verify it against `source_url` before quoting a number from it.

  ConnectorNo auth

• create_extractorA

  Extend MCPA

  Create a saved, reusable extractor (extract group). Three starting points, mutually exclusive: config (inline schema — call get_documentation with https://docs.extend.ai/extraction/schema.md BEFORE writing one by hand), cloneExtractorId (copy another extractor's draft config), or generate (Extend writes the schema from 1-5 sample documents plus optional instructions; no docs needed); name alone creates an empty draft. The draft is the only mutable surface — edit it with update_extractor, freeze it with publish_extractor_version, run it with extract_data. Follow any llmContext guidance included in results.

  ConnectorOAuth

• combined_trends_toolA

  SantimentA

  Combined trends tool that fetches trending words, stories, and documents in parallel. This tool provides a unified view of all trending data - words with their documents and stories - in a single response across all crypto projects. ## When to use vs `trending_stories_tool` This is a superset of `trending_stories_tool`: same stories, plus trending words, their context and AI-generated bull/bear summaries. It calls an LLM, so it is slower and has a tighter per-tool rate-limit sub-cap than every other tool. If only trending stories are needed, call `trending_stories_tool` instead; set `include_words: false` / `include_stories: false` to drop a half that is not needed. Do not call both tools for the same question. ## Parameters - `time_period` - Time period for trending data (e.g., '1h', '6h', '1d', '7d'). Defaults to '1h' (last hour). - `size` - Number of items per category to return (max 30). Defaults to 10. - `include_stories` - Include trending stories in response. Defaults to true. - `include_words` - Include trending words in response. Defaults to true. ## Response - `trends` - Combined trending data containing stories and words. - `metadata` - Request metadata including time period, size, and included data types. - `errors` - Any non-fatal errors encountered during data fetching. ## Trending Data Structure ### Stories - `title` - Title of the trending story. - `summary` - Summary of the story. - `score` - Trending score. - `query` - Search query used to find the story. - `related_tokens` - List of related crypto tokens (format: "BTC_bitcoin"). - `bullish_sentiment_ratio` - Bullish sentiment ratio. - `bearish_sentiment_ratio` - Bearish sentiment ratio. ### Words - `word` - The trending word. - `score` - Trending score. - `slug` - Associated project slug (if word is project-related). - `summary` - AI-generated summary of discussions. - `bullish_summary` - Summary of bullish sentiment. - `bearish_summary` - Summary of bearish sentiment. - `positive_sentiment_ratio` - Positive sentiment ratio. - `negative_sentiment_ratio` - Negative sentiment ratio. - `neutral_sentiment_ratio` - Neutral sentiment ratio. - `positive_bb_sentiment_ratio` - Positive bull/bear sentiment ratio. - `negative_bb_sentiment_ratio` - Negative bull/bear sentiment ratio. - `neutral_bb_sentiment_ratio` - Neutral bull/bear sentiment ratio. - `context` - Related words that appear with this trending word. - `documents_summary` - AI-generated summary of related social media discussions.

  ConnectorNo auth

• generate_policiesA

  lexvibeA

  Generate the legal documents (privacy policy, terms of service and, if applicable, an AI disclosure) localized and tailored to the target markets (GDPR, UK GDPR, CCPA…). Returns Markdown drafts. Pass check_website's or check_store's suggestedAnswers as `answers` so the documents disclose the right processing. Anonymous remote generation is template-based and capped at 3 locales; AI-tailored, hosted and auto-updated documents require a LexVibe account (https://golexvibe.com).

  ConnectorNo auth

• SearchInsidersA

  equiblesB

  Search the tracked SEC corporate-insider set (directors, officers, 10% owners) by name. Search first requires every punctuation-independent whole query word in the filed legal name, then broadens to any whole word only when no strict row matches; a token inside a different word is not a match. Verified public-name aliases such as Jensen Huang resolve to the SEC owner identity. Returns CIK, role, latest filing company, and location, ordered by recent filing activity.

  ConnectorNo auth

• get_word_of_the_dayA

  Vocab VoyageA

  Use this when the user asks for today's word, a daily vocabulary nudge, or a single-word warmup. Returns today's deterministic Word of the Day (definition, part of speech, example, synonyms/antonyms), optionally scoped to a test family (isee, ssat, sat, psat, gre, gmat, lsat, general). Do not use for arbitrary lookups — call get_definition instead.

  ConnectorNo auth

• interlinearA

  orthotomeoA

  Returns a row-aligned reading view for every word in a verse (or one word, if word is given): original text, transliteration, gloss (via lexicon_lookup), grammar, and manuscript attestation stacked per word - the composed display shape for a study reading view, built on parse and lexicon_lookup rather than any new query. This is the most complete per-word view; use parse or attestation when you want only one of those facets.

  ConnectorNo auth

• docraptor_create_documentA

  docraptorA

  Generate a PDF or Excel document from HTML (document_content) or a URL (document_url). Exactly one of document_content / document_url is required. By default the document is HOSTED and the tool returns a { download_url } you can fetch — ideal for agents (no large binary in the response). Set hosted:false to get the raw document back as base64, or async:true to enqueue a job and poll docraptor_get_document_status. IMPORTANT: real documents consume account credits (billed). Set test:true to generate a FREE, watermarked document while developing. DocRaptor API: POST /docs.

  Connector

  Destructive

  No auth

• search_meetingsA

  archiveA

  Which of the 1,422 published town meeting documents contain a word — every board, 2025 onward. Returns the board, the date and a citable URL for each. AN EMPTY RESULT MEANS THE WORD IS NOT IN THE INDEXED DOCUMENTS, which is not the same as nobody having said it: the archive starts in January 2025. It matches words exactly, so plurals are separate terms — search "jersey" and "jerseys" both.

  ConnectorNo auth

• auteng_docs_recentA

  AutEng MCP - Markdown Publishing & Document Share LinksA

  Browse the public recents feed of shared documents. No authentication required. Returns recently shared public documents, newest first. Args: page: Page number (default 1) limit: Items per page (default 20, max 100)

  ConnectorNo auth

• auteng_docs_recentA

  AutEng MCP - Markdown Publishing & Document Share LinksA

  Browse the public recents feed of shared documents. No authentication required. Returns recently shared public documents, newest first. Args: page: Page number (default 1) limit: Items per page (default 20, max 100)

  ConnectorNo auth

• search_context_docsA

  ALM X++ MCP ServerA

  WHEN: the user asks about business/functional context that lives OUTSIDE the D365 code KB -- specs, functional design docs, mapping sheets, contracts, meeting notes, screenshots' captions -- anything an admin uploaded via the admin portal's 'Context Documents' library (PDF, Word .docx, Excel .xlsx/.xlsm, CSV, plain text/Markdown/JSON). Does NOT search X++ code or AOT objects -- use search_d365_code / get_object_details for that. Triggers: 'what does the spec say about...', 'check the mapping document for...', 'cherche dans les documents de contexte', 'according to the functional design'. An excerpt containing a 'Image N' marker has a picture the text cannot convey (a diagram, a screenshot): call again with includeImages=true to receive those pictures inline.

  ConnectorNo auth

• get_entity_infoA

  dannetA

  Full JSON-LD of a DanNet resource: a synset ("synset-3047"), word ("word-11021628") or sense ("sense-21033604"), given bare or prefixed ("dn:synset-3047"), or an external resource by prefix ("ili:i76470", "ontolex:LexicalConcept"). Properties use prefixed names (wn:hypernym, ontolex:isEvokedBy, ...); language-tagged values are {"@value": ..., "@language": ...}.

  ConnectorNo auth

• list_congressional_document_typesA

  Congressional DocumentsA

  List the kinds of congressional documents that can be searched (hearings, committee reports, committee prints, House/Senate documents, Congressional Record), what each contains, and what this source does and does not cover. Call this when unsure which doc_type answers a question.

  ConnectorNo auth

• add_sync_pointA

  CluesoA

  Insert one sync marker on a clip's transcript. Use this when: - The user is explicit about WHERE the camera should pause / cut (e.g. "sync the word 'submit' to 4.2s of the demo"). - `auto_sync` ran but missed a step you care about. How matching works: - `word`: case-insensitive, punctuation-stripped. The first match in the transcript is used unless `occurrence > 1`. - `occurrence`: 1-indexed — pass 2 to target the SECOND time that word appears, 3 for the third, etc. Required when the word repeats. - `timestamp_seconds`: clip-relative seconds. When the clip has run TTS already (`generated_timestamps` present), the server inverse-maps this to original-recording seconds automatically. Constraints: the clip MUST be a video clip with a source recording (otherwise the frame thumbnail can't be extracted). The transcript must already contain the word — if not, you'll get `word_not_found` with a 200-char excerpt of the transcript to help you retry.

  ConnectorNo auth

• export_documentA

  sendpageA

  Get a downloadable PNG image, PDF, or Word (.docx) file of a document already published to SendPage. Use this when the user wants a file copy — to attach, print, or hand over — not just the link. Returns a URL to fetch the file. PNG and PDF are free (free-tier documents carry a small watermark); Word export requires Pro.

  ConnectorNo auth