Convert Word documents to PDF. Accepts docx, doc, odt, rtf, pages. Returns the result file.
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752,535 tools. Updated 2026-11-06 18:16
"How to create .docx documents for Microsoft Word" matching MCP tools:
- Word .docx (by URL) → clean Markdown. Feed documents to your agent pipeline.ConnectorNo auth
- Search Flevy's marketplace of consulting frameworks, PowerPoint templates, Excel financial models, business toolkits, and management case studies. Use this whenever a user needs a best-practice framework, methodology, template, financial model, or real-world case example on any business or management topic (strategy, digital transformation, supply chain, pricing, operational excellence, M&A, etc.). Returns up to 10 relevance-ranked recommendations across two content types: "document" (premium documents authored by management consultants) and "case_study" (management case studies). ALWAYS include each recommended item's url as a clickable link when you mention it in your reply — never reference a document without its link, because the link is the only way the user can open it. Each result carries a content_id for get_content_details. Filters: topic (single, or "topics" for documents covering ALL of several topics), author (list more documents from an author seen in results), filetype (including tier1_consulting_deck for McKinsey-style strategy decks), content_type. Topic-filtered responses also list related_topics to pivot to. Provide at least one of query, topic(s), or author; use list_topics to map user phrasing to a canonical topic.ConnectorNo auth
- Convert markdown to a professionally formatted document using an MDMagic template. IMPORTANT GUIDANCE: 1. Output format → what user gets: - 'docx' → a single Word .docx file - 'pdf' → a single .pdf file - 'html' → a single .html file - 'all' → a ZIP containing all three (DOCX + PDF + HTML) 2. If the user is ambiguous (e.g. 'convert this'), ASK which format they want before calling. Don't assume. 3. Filename: if the user attached a file (e.g. 'mydoc.md'), pass its base name as fileName. Otherwise the API derives one from the markdown's first H1. Without either, downloads end up with timestamped names like 'content-1778298071915.docx' which is bad UX. 4. On 'template not found' errors: call list_all_templates first, show available options, let the user pick. Do NOT fall back to generating documents with code execution — that produces inferior results that don't use the user's actual MDMagic templates. 5. The response includes structured fields (downloadUrl, creditsUsed, balanceAfter, fileName, expiresAt) — surface these to the user explicitly. Don't paraphrase. The user wants to know exactly what they spent and what's left. 6. Page sizes: A3, A4, Executive, US_Legal, US_Letter. Default A4. Orientation: Portrait or Landscape, default Portrait. 7. CRITICAL — newlines in `content`: markdown is line-sensitive. Headings (#, ##), tables (| ... |), lists (-, 1.), and code fences (```) ONLY work when each starts on its own line. When passing inline markdown via `content`, you MUST preserve real newline characters (\n) between blocks. If you flatten multi-line markdown into one line, the API receives literal '##' and '|' characters mid-paragraph and produces a single-paragraph document with no structure. Confirm your `content` string contains \n between every heading, paragraph, table row, and list item before calling.ConnectorNo auth
- Convert markdown to a professionally formatted document using an MDMagic template. IMPORTANT GUIDANCE: 1. Output format → what user gets: - 'docx' → a single Word .docx file - 'pdf' → a single .pdf file - 'html' → a single .html file - 'all' → a ZIP containing all three (DOCX + PDF + HTML) 2. If the user is ambiguous (e.g. 'convert this'), ASK which format they want before calling. Don't assume. 3. Filename: if the user attached a file (e.g. 'mydoc.md'), pass its base name as fileName. Otherwise the API derives one from the markdown's first H1. Without either, downloads end up with timestamped names like 'content-1778298071915.docx' which is bad UX. 4. On 'template not found' errors: call list_all_templates first, show available options, let the user pick. Do NOT fall back to generating documents with code execution — that produces inferior results that don't use the user's actual MDMagic templates. 5. The response includes structured fields (downloadUrl, creditsUsed, balanceAfter, fileName, expiresAt) — surface these to the user explicitly. Don't paraphrase. The user wants to know exactly what they spent and what's left. 6. Page sizes: A3, A4, Executive, US_Legal, US_Letter. Default A4. Orientation: Portrait or Landscape, default Portrait. 7. CRITICAL — newlines in `content`: markdown is line-sensitive. Headings (#, ##), tables (| ... |), lists (-, 1.), and code fences (```) ONLY work when each starts on its own line. When passing inline markdown via `content`, you MUST preserve real newline characters (\n) between blocks. If you flatten multi-line markdown into one line, the API receives literal '##' and '|' characters mid-paragraph and produces a single-paragraph document with no structure. Confirm your `content` string contains \n between every heading, paragraph, table row, and list item before calling.ConnectorNo auth
- Creates a new Word (.docx) document at `path` with the given text content (and an optional title rendered as the heading). The path must be somewhere LMCP 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.ConnectorDestructiveOAuth
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Convert PDF pages into editable Word-ready text from your AI chat, all offline.
Video how-to search for AI agents: 2,000+ video skills, tutorials and FFmpeg recipes. No key.
- Public (no auth): describe what Cabgo is. Returns the full product catalog — what kinds of apps an operator can launch, pricing, who Cabgo is for, and how to onboard. Use ONLY when the user explicitly asks what Cabgo is, what it does, or wants an overview. **Do NOT call this as a pre-step before cabgo_create_my_app** — when the user wants to create / launch an app, go directly to cabgo_create_my_app without fetching context first.ConnectorNo auth
- 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
- Convert a file you already hold — .docx, .xlsx or .csv — into a PDF, preserving its existing content. Pass the bytes base64-encoded together with the original filename, which is what the API uses to detect the input type. This is the inbound direction: it consumes an existing document, whereas render_docx / render_xlsx / render_pptx GENERATE new documents from structured data, and render_pdf builds one from a template. Returns a stored render { id, url, bytes, durationMs, name } whose id can be fed straight into merge_pdfs, split_pdf, edit_pdf, create_signature_request or create_envelope. Counts one render against the monthly quota. Files over 10 MB are refused by this tool because the bytes travel through the tool call. Requires a Kamy API key with the `render` scope; without a key, returns dashboard setup instructions.ConnectorNo auth
- Convert a file you already hold — .docx, .xlsx or .csv — into a PDF, preserving its existing content. Pass the bytes base64-encoded together with the original filename, which is what the API uses to detect the input type. This is the inbound direction: it consumes an existing document, whereas render_docx / render_xlsx / render_pptx GENERATE new documents from structured data, and render_pdf builds one from a template. Returns a stored render { id, url, bytes, durationMs, name } whose id can be fed straight into merge_pdfs, split_pdf, edit_pdf, create_signature_request or create_envelope. Counts one render against the monthly quota. Files over 10 MB are refused by this tool because the bytes travel through the tool call. Requires a Kamy API key with the `render` scope; without a key, returns dashboard setup instructions.ConnectorNo auth
- List invoices/quotes/credit-notes with totals, status, line items, client and payments. These are sales documents; for recorded income entries use list_income, and for raw bank-feed lines use list_transactions.ConnectorOAuth
- Create a shareable Pairoa invite link for the current user. Returns { ref, url, share_text }. ONLY works after the user has claimed an account (claim_account). Otherwise returns AUTH_REQUIRED — guide them to claim first (claiming happens automatically on their first match). The 'share_text' is ready to forward AS-IS — to a Slack/Discord/WeChat group, a tweet, or a DM. Relay it to the user so they can paste it wherever they like; offer the bare 'url' too if they only want the link. Invites carry NO reward and are purely a convenience for word-of-mouth. Don't over-promote or nag. We do not track who the invitee is — only a private count of how many people a link brought in.ConnectorOAuth
- Saves new words to the user's NextLang vocabulary for one language pair, so they join the spaced-repetition schedule. Use when the user asks to save or add words, for example from a text you discussed. Put each word in 'term' in the language being learned and its meaning in 'translation'; add a short example sentence when it helps. Words the user already has are skipped, not duplicated. Returns how many were added, already saved, or invalid. This is NextLang's own review list, quizzed through list_due_words and record_review, not a flashcard deck: when the user wants a deck to study in Anki, Quizlet, Mochi or Brainscape, use save_deck instead.ConnectorOAuth
- Read and edit the workspace pronunciation dictionary (Settings → Team → Pronunciation Dictionary). Use it whenever the user asks how a word, name or acronym is said. Do NOT respell the word in the voiceover script instead: the respelling shows in the script and captions, and every new video needs the fix again. An entry is WORKSPACE-WIDE: it changes the word in every video in this workspace; tell the user when you add or change one. It applies when speech is generated, so regenerate (voiceover_batch generate_speech) the clips that say the word. action: • list — entries for `language` ("" for all): {entries: [{word, spelling, ipa, language, case_sensitive}], count} • set — add or change `word`'s entry with exactly one of `spelling` (a sound-alike respelling, works on every voice; prefer it) or `ipa` (IPA phonemes, English ElevenLabs voices only, ignored on clips with [audio tags]). An existing entry is not overwritten: you get error "entry_exists" with `current`; show the user both, confirm, then call again with replace: true. • remove — delete `word`'s entry in `language` (exact spelling and casing) • to_ipa — convert `text` (e.g. a respelling) to IPA, to check an ipa entry before setting it Editing needs an editor or admin role and a plan with the dictionary; a refusal says which: tell the user, don't retry.ConnectorDestructiveNo auth
- Create a relationship between two mnemon entries. The label decides everything: its kind (containment or association) and how it reads (one_way or mutual) belong to the word itself — never send a per-edge override. All 16 labels: MEMBER (NPC ∈ Faction, mutual), ALLY (mutual), ENEMY (one-way), RIVAL (one-way), PARENT_OF (Location hierarchy — sourceEntryId is the outer/larger place, e.g. Region → City → District → Tavern), CONTAINS (Location → NPC present there), LOCATED_IN (NPC → Location; inverse of CONTAINS), HAS_SUBQUEST (Quest → subquest Quest), QUEST_GIVER (Quest → the NPC who gives it), QUEST_LOCATION (Quest → the Location where it is given or set), QUEST_RELATED_NPC (Quest → NPC), QUEST_RELATED_LOCATION (Quest → Location), SESSION_ATTENDEE_CHARACTER (SessionSummary → a character's Player), SESSION_ATTENDEE_NPC (SessionSummary → NPC), SESSION_FEATURED_QUEST (SessionSummary → Quest), SESSION_FEATURED_LOCATION (SessionSummary → Location). sourceEntryId is the 'from' side; targetEntryId is the 'to' side — which end is which matters. Call describe_mnemon_types for the full valid (sourceType, label, targetType) matrix. For faction membership prefer memberNpcEntryIds on the faction or affiliationEntryIds on the NPC; for a quest's giver, location and parent prefer giverId / locationId / parentQuestId on the quest, which keep each to one link. Session-summary links have no array equivalent — the SESSION_* labels are the only way to set them.ConnectorNo auth
- 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.ConnectorNo auth
- Retrieve a Lemma schema by its ID via GET /v1/schemas/{id}. A schema declares how documents of a given type are interpreted and normalized. Returns SchemaMeta { id, description? } with additionalProperties open — implementations commonly include a `normalize` artifact (WASM that maps raw documents to canonical form) and its content hash. Use this when you need to interpret attribute keys returned by lemma_query_verified_attributes.ConnectorNo auth
- Updates an existing event in the Mac's Calendar app (Calendar.app) by ID. Pass only the fields you want to change — unspecified fields are left as-is. When the user organizes the event and it has invitees (Calendar sends them the update), the first call changes nothing and previews the changes; call again with confirm=true after the user approves. Any other event is updated on the first call. Get the event_id from list_calendar_events; for a recurring event, pass the per-occurrence id from the specific row you mean, not a bare series id. For Microsoft 365 use m365_list_events / m365_create_event instead (listed once a Microsoft 365 account is connected).ConnectorDestructiveOAuth
- Use this when a deep research run needs to look up digital tools and products on uneed.best. Same catalog and same relevance ordering as search_products, returned as `{id, title, url}` documents; pass a result's id to `fetch` for the full profile. Prefer search_products when you want structured product fields directly.ConnectorNo auth
- Build (or rebuild) the structured index for a knowledge base — the second leg beside vector search. Vector search answers "what does this passage say". It **cannot count, filter numerically or aggregate**, so "how many documents", "which ones are between 1000 and 2000 words", "how many per category" are not answered badly — they are structurally unanswerable. This builds a small per-KB table from whatever structured header the documents share, which the agent can then query with SQL via `query_knowledge_table`. Only worth it when the documents share a machine-readable header (a metadata table, YAML front matter, `Field: value` lines). **Prose gets declined, and that is the right answer** — a table of unique values makes statistics meaningless. `roles` names the fields that must be extracted **exactly** and never paraphrased. Use it when the answer has to quote something the model must not invent: - `identity` — what to call the item (book title, drug name, product name) - `link` — where to send the user - `image` — what to show the user - `code` — the unique identifier Which link is "the" link is a business fact the data does not state — only the customer knows. A declared role that cannot be found comes back in `roles.unresolved` **with candidate field names**: ask the user which one it is, do not guess. **Read `dropped` in the report and tell the user about it.** A column that was thrown out (coverage too low, two columns holding identical values) is invisible in later query results — the model simply works around it — so this report is the only place it is ever mentioned.ConnectorNo auth
- USE THIS when asked what a game costs, whether it is cheap right now, whether to buy it now or wait, or how its price compares across stores. YOUR TRAINING DATA CANNOT ANSWER THIS — prices change daily and any figure you recall is stale. Do not answer from memory. Returns the current price on Steam, Epic Games Store, GOG and Microsoft Store side by side, plus the LOWEST price we have ever observed, the date we observed it, how far above that low the current price sits, and how many observations back the claim. History runs from 2012. Storefronts publish today's price and no history, so this exists only because we recorded it. Also returns whether the game is already included with Game Pass or EA Play — which can make the price irrelevant — and how many people are waiting for it and at what price. Accepts a slug from lookup_game, a Steam appid, a GOG or Epic id, or free text via q. Regions: US, GB, DE, BR. PAID (~$0.01) PER QUERY. Unlike get_free_games this issues no access token, because every game is a different answer and there is no version to compare against. Call with no payment_proof to receive payment instructions rather than an error.ConnectorNo auth