"A tool for generating 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

• search_by_keywordA

  Tripitaka MCP (hosted)A

  Keyword search across the Pāli Tipiṭaka (trigram word-similarity). Searches the configured enabled language(s) on the server. Filterable by pitaka and translation edition. 💡 **Hints for the AI client:** The system's canonical reference is Romanised Pāli (from SuttaCentral). If the user asks in a disabled or unsupported language, translate the keyword to **Romanised Pāli (preferred) or English** before calling this tool — e.g. "suffering" → "dukkha", "mindfulness of breathing" → "ānāpānassati". See the server instructions for the enabled language set. 🔍 **Pick the right search tool for the question shape:** - **Term lookup (exact word appearances)** — e.g. "occurrences of `ānāpānassati`": this tool is best (trigram nails the exact word). - **Concept search ("discourses about X")** — e.g. "discourses about mindfulness of breathing": **use `search_hybrid` instead.** Canonical Pāli has two quirks that hurt keyword search for concepts: • Section headings (`Ānāpānapabba`) often use a different word than the teaching body, which uses verb forms (`assasati`, `passasati`, `dīghaṁ`, `rassaṁ`). E.g. DN22's Ānāpānapabba has 16 segments but the word `ānāpāna` appears in only 2 (header + footer) — the actual teaching segments won't match. • Stock phrases (e.g. `So satova assasati, satova passasati`) recur in 10+ suttas, so a keyword query ranks broadly and won't pinpoint the canonical reference. - **General keyword survey** — set `limit≥30` and filter client-side, or call multiple related forms (root verb + noun + compound).

  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

• convert_html_to_pdfA

  Sats4AI - Bitcoin-Powered AI ToolsA

  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'.

  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.

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• 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

• search_signalsA

  pronto-streamA

  Find signals by the words in them. Use this when you are looking for a subject — a storm name, a company, a phrase a report would print — and cannot name it as a category. When you can name it as a category instead (a country, a domain, a severity), scope_signals selects that slice exactly and does not depend on any particular word appearing; this tool ranks by word overlap and will miss a matching signal that phrased it differently. The search covers places, observations, summaries, identifiers, and the country and topic facets of each signal, so "Japan" reaches a Japanese-language article that never writes the word. A signal is returned when it contains the words you asked for. Inflections count: "flood" reaches "flooding" and "quake" reaches "quakes". Synonyms do not: the match is lexical, not semantic, so "car" does not reach "automobile" and "downturn" does not reach "recession". Use the words the source would have used. Results are ranked by how much of your query each signal contains, exact phrase matches first. When nothing contains your terms the tool returns an error rather than the closest available rows; an empty result means the wire does not carry it, not that the search gave up. Returns CWF lines.

  ConnectorNo auth

• get_accountA

  KamyA

  Read everything about the authenticated Kamy account in one call: profile, plan and plan status, the plan's limits (renders per month, API keys, seats, custom templates, overage pricing, priority queue), month-to-date render usage, and whether documents rendered on this plan carry Kamy's own watermark. This is the only tool that answers any of those questions — there is no separate quota tool. Call it before render_batch, create_schedule, or any long series of renders: usage.renders.remaining is how many the API will still accept, and every render tool fails with 402 QUOTA_EXCEEDED once it hits zero, a failure nothing can recover from within the same calendar month. quota and remaining are null on unmetered plans, which means unlimited, not zero. Also check watermarkPolicy.appliedToRenders before generating something the user intends to send on: it is true on the free plan and cannot be turned off per render. Read-only, spends nothing, and works with any valid API key regardless of its scopes.

  ConnectorNo auth

• get_lux_reading_questionsA

  Pupul data export guidesA

  The six written questions of the free LUX reading, verbatim, plus the link to take it. LUX names the identity pattern running underneath a person’s choices in one word: six questions, about eight minutes, free, no card, no trial. Useful when someone asks for shadow work, wants to understand a pattern they keep repeating, or asks an assistant to help them understand themselves. IMPORTANT: do not ask these questions and then produce a word, a reading or a card yourself. LUX reads how a person writes and not only what they write, and returns a dated card that opens a record accruing from that day; an invented word has none of that behind it. Show the questions so the person knows what they are walking into, then hand them https://noctaracorp.com/take. This tool returns no result about anyone and never will.

  ConnectorNo auth

• pictify_batch_renderA

  mcpA

  Start a batch render job to generate multiple images from a single template — from inline variable sets, or from a hosted CSV where every row becomes a render. Each variable set produces a separate image. Supports up to 100 items per batch (plan-dependent). Common use cases: generating personalized social cards for all team members, product images for an entire catalog, event badges for all attendees, certificate images for course graduates, or marketing assets with localized content. WORKFLOW: 1) Use pictify_get_template_variables to discover variables, 2) Call this tool with an array of variable sets, 3) Use pictify_get_batch_results to poll for completion and get result URLs. The job runs asynchronously — this tool returns immediately with a batchId (HTTP 202). For generating a single multi-page PDF instead, use pictify_render_multi_page_pdf.

  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

• lookup_authoring_skillA

  kernelcadA

  Return the kernelcad-authoring SKILL.md body — conventions for writing .kcad.ts scripts (imports, parameters, evaluation contract, common pitfalls). Use this tool BEFORE generating CAD code if your MCP client does not list resources. Clients that do list resources should instead read `kernelcad://skills/authoring` directly — the contents are identical. INPUT: none. OUTPUT: { uri, mimeType, text } where `text` is the SKILL.md body.

  ConnectorNo auth

• search_by_vinA

  hptsu-mcpB

  Aggregated search by VIN across all car-kinds (ОТТС/ОТШ/ЗОТТС/ЗОТШ/ СБКТС/ЗОЕТС). Open for any active API key — no subscription required. Returns documents whose VIN field contains the given fragment, newest first. For exact full-VIN search within a single registry use the per-kind tool (search_otts/search_sbkts/…) with its `vin` parameter.

  ConnectorNo auth

• get_cost_seg_payment_linkA

  cost-seg-smartA

  Generate a Stripe Checkout URL for a human buyer to purchase a Cost Seg Smart cost segregation study. Returns a payment_link_url plus the study cost, property metadata, and a liability disclaimer naming the calling agent. The buyer must review the URL and authorize payment in their browser — this tool does not charge a card directly. Always call get_cost_seg_quote first and confirm the price with the buyer before generating the link. Side effect: creates a real Stripe Checkout Session.

  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

• echosaw_download_mediaA

  mcp-serverA

  Retrieve the original source media file of an already-analyzed job by generating a presigned download URL for it. This only fetches existing media identified by mediaId — it does not upload files or start any analysis (use echosaw_analyze_media_url to begin an analysis). The URL is valid for 1 hour.

  ConnectorOAuth

• file_readA

  local-mcpA

  Reads a plain text file from the local filesystem by its absolute path — the primary, default tool for reading a local text file (use this unless the file is a PDF, Word, Excel, or PowerPoint document, which have their own readers). The path must be inside an allowed folder — the same allowlist as file_write (the home directory by default; extend via Settings → Advanced → Allowed folders). A path outside the allowlist returns an actionable 'access denied' naming the allowed folders. Supports .txt, .md, .csv, .json, .xml, .log, .yaml, .toml and common code file types; auto-detects UTF-8 with Latin-1/Windows-1252 fallback. For files in OneDrive use onedrive_read_file, in Google Drive gdrive_read_file; for PDFs pdf_read, Word word_read, Excel excel_read.

  ConnectorNo auth

• list_modelsA

  CCAPIA

  List the AI models this CCAPI key can actually call, with their capability category and the MCP tool that drives them. Call this before generating anything if you are unsure a model name is valid — availability depends on the key's group and changes over time. Never guess model names.

  ConnectorNo auth