"How to create documents in Confluence" matching MCP tools:

• analyze_title_documentsA

  Curagent Title RiskA

  Analyzes Florida real estate title documents and returns a structured risk report: a risk score (0-100, higher is safer) and level, findings with verbatim evidence from the documents and guidance on how to cure each one, and the Schedule B-I requirements extracted from any title commitment in the package. Accepts one or more PDF documents as base64 strings (deed, title commitment, mortgage, closing disclosure, survey, payoff letter, HOA estoppel, etc.), including a single PDF containing a whole closing package, which is split into its constituent instruments. Submitting several documents together also enables cross-document checks for contradictions in parcel ID, address, and party names. Uses one of your 3 free analyses (sandbox tier) or 1 credit (paid tiers). Florida properties only — call check_coverage first to confirm scope, and get_credit_balance to confirm available credits.

  ConnectorNo auth

• count-space-suggestionsA

  docuwriterA

  Use this when the user asks how many Autopilot/repository-sync suggestions are pending, snoozed, done, high-confidence, or waiting for review. Read-only: returns grouped counts without changing suggestions or documents. Optionally filter by numeric space_id.

  ConnectorOAuth

• create_cardA

  AgileHeroA

  Create a card on a project's kanban board. Only project_id and title are required. Omit list_id to put the card in the backlog; omit position to join the end of the queue (move_card documents the position contract). description is AgileHero Markup — never markdown or HTML; read get_ahm_spec first. epic_id and assignee uids must already exist (list_epics, list_project_users), while label names that do not exist yet are created on the project. estimation is Fibonacci complexity (0/1/2/3/5/8/13), not a time estimate. Checklists, links, attachments and card relations can all be supplied in this same call.

  ConnectorNo auth

• lemma_get_schemaA

  mcpA

  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

• build_knowledge_indexA

  agent4.ioA

  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

• create_payment_match_draftA

  mcpA

  FILES A PENDING DRAFT ONLY — NOTHING CHANGES UNTIL A HUMAN REVIEWS AND APPROVES IT IN TAOKEH. Propose how ONE bank line already posted as a customer payment (money in) or a supplier payment (money out) settles open invoices or bills — the owner's "this deposit paid these three invoices". An admin or bookkeeper reviews it and approves; only that tap allocates, exactly as Banking → Match → Save does, and the documents then read as paid. Pass `bankTransactionId` (a POSTED line from bank_review_queue with status "posted") and `allocations`: [{saleId, amount}] for money in, [{purchaseId, amount}] for money out, ringgit, adding up to the WHOLE line to the sen (the in-app pane's ±0.10 rounding allowance does not apply to a proposal). At most 50 documents. WHICH DOCUMENTS: only the ones Banking → Match offers this line — the open invoices of the customer the line is posted against (or, when that customer has none open, the invoices of the company's walk-in customer — the one the owner marked on its customer page, else a customer named 'CASH SALES'), or the supplier's open bills. A line with no customer at all is offered nothing. A document of ANY other party is refused, because no screen in Taokeh offers it: if the payment was posted against the wrong customer, or no customer, the owner unposts the line in Banking, sets the right customer, and posts it again — then file this. A refusal lists the documents the line can take, with their ids. ALSO REFUSED BY NAME, at filing and again at approval: a line not posted, not a customer/supplier payment, already matched (a match someone saved is never replaced), or on a foreign-currency account (the owner settles those in the app); a document not open; an amount over what a document still owes; a document dated AFTER the payment (an advance is allocated by hand); the same document twice; a pending match already filed for the line. If the line or a document changes before approval (paid, credited, re-tagged, matched), approval refuses and nothing is allocated. `note`: one short line for the owner saying how you know (the remittance, the customer's message).

  ConnectorOAuth

• create_payment_match_draftA

  Taokeh MCP serverA

  FILES A PENDING DRAFT ONLY — NOTHING CHANGES UNTIL A HUMAN REVIEWS AND APPROVES IT IN TAOKEH. Propose how ONE bank line already posted as a customer payment (money in) or a supplier payment (money out) settles open invoices or bills — the owner's "this deposit paid these three invoices". An admin or bookkeeper reviews it and approves; only that tap allocates, exactly as Banking → Match → Save does, and the documents then read as paid. Pass `bankTransactionId` (a POSTED line from bank_review_queue with status "posted") and `allocations`: [{saleId, amount}] for money in, [{purchaseId, amount}] for money out, ringgit, adding up to the WHOLE line to the sen (the in-app pane's ±0.10 rounding allowance does not apply to a proposal). At most 50 documents. WHICH DOCUMENTS: only the ones Banking → Match offers this line — the open invoices of the customer the line is posted against (or, when that customer has none open, the invoices of the company's walk-in customer — the one the owner marked on its customer page, else a customer named 'CASH SALES'), or the supplier's open bills. A line with no customer at all is offered nothing. A document of ANY other party is refused, because no screen in Taokeh offers it: if the payment was posted against the wrong customer, or no customer, the owner unposts the line in Banking, sets the right customer, and posts it again — then file this. A refusal lists the documents the line can take, with their ids. ALSO REFUSED BY NAME, at filing and again at approval: a line not posted, not a customer/supplier payment, already matched (a match someone saved is never replaced), or on a foreign-currency account (the owner settles those in the app); a document not open; an amount over what a document still owes; a document dated AFTER the payment (an advance is allocated by hand); the same document twice; a pending match already filed for the line. If the line or a document changes before approval (paid, credited, re-tagged, matched), approval refuses and nothing is allocated. `note`: one short line for the owner saying how you know (the remittance, the customer's message).

  ConnectorOAuth

• how-toA

  Fast.ioA

  Built-in product help — ask a natural-language "how do I…" question about Fastio and get a grounded, product-aware answer (or a short clarifying question) back in one call. EXPLAIN-ONLY / ADVISORY: it returns GUIDANCE TEXT and performs NO platform action (it will not create shares, move files, or change anything) — read the guidance, then act with the other tools. Answers are grounded in Fastio's own how-to knowledge AND phrased in terms of these MCP tools — they name the concrete `<tool> action="…"` calls to make — so prefer this over guessing endpoints or burning exploratory calls. For Q&A over YOUR uploaded files (RAG) use the `ai` tool instead — `how-to` answers questions about Fastio ITSELF. FREE and requires only an authenticated user (no org, no plan gate, no billing). Call action='describe' for the full action/param reference.

  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.

  ConnectorNo auth

• get_guideA

  Tu LugarA

  Curated TuLugar guides (general education, kept current): buying-process (step-by-step + documents), foreigners (rights + restrictions for non-Paraguayans), closing-costs (what fees exist), renting (contracts, deposits, garante), publishing (listing tips), airbnb (short-term rental basics). ALWAYS use this for "how does buying/renting work" / process / documents questions — the content IS in scope to share; only personalized legal advice is not.

  ConnectorNo auth

• get_guideA

  Tu LugarA

  Curated TuLugar guides (general education, kept current): buying-process (step-by-step + documents), foreigners (rights + restrictions for non-Paraguayans), closing-costs (what fees exist), renting (contracts, deposits, garante), publishing (listing tips), airbnb (short-term rental basics). ALWAYS use this for "how does buying/renting work" / process / documents questions — the content IS in scope to share; only personalized legal advice is not.

  ConnectorNo auth

• list_org_sourcesA

  agentleFSA

  Lists external CONNECTIONS (GitHub, Google Drive), NOT documents: for the documents in a folder, use list_org_docs. For each connected repository or Drive folder it shows where it writes and whether it is actually syncing. Call it after connecting something to confirm it worked, or when content you expected is missing and you want to know whether the source ran and failed or never ran at all. Sync is ONE-WAY, from the source into agentleFS, and it repeats: the source is polled and the destination folder is brought up to date. Documents you write here are not pushed back to the repository, and a connector-owned path refuses direct edits rather than having them silently overwritten on the next run.

  ConnectorAPI key

• list_documentsA

  AgenticBooksA

  Lists the organisation's captured documents (each row is one stored artifact — a PDF/image attachment or a rendered email body), newest first. status tells you where each is in the evidence pipeline: processing (being extracted), matched (attached to a transaction — matched_event_id says which), awaiting_transaction (no matching bank debit yet; re-checked nightly), match_ambiguous (a PROPOSAL awaiting a decision — proposal.candidate_ids are the possible transactions and proposal.reason says why it was not auto-attached: multi_candidate, fx_band, dkim_fail, or first_sender — the sender domain has no previously confirmed evidence in this org yet, so confirming once establishes continuity for future auto-attaches), extraction_failed, too_large, unsupported. Resolve proposals by calling attach_document with the right candidate. Results are the NEWEST `limit` rows (max 200); total_count may exceed files.length — narrow with the status filter to reach older rows. Documents NEVER create bookings — they are evidence attached to the bank record.

  ConnectorOAuth

• products_deleteA

  ViewPrinterA

  Delete a product. Its accounts stay connected and belong to no product afterwards. Refused while it has campaigns. Its knowledge documents and gathered research are deleted with it, so this is refused while it has any unless confirm_discard is true — read the refusal, which says how many would go, before confirming.

  Connector

  Destructive

  OAuth

• 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

• word_appendA

  Local MCPB

  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.

  Connector

  Destructive

  OAuth

• get_revenue_summaryA

  invoicevistaA

  Use this when someone asks how much they invoiced or were paid in a period, like last month. Returns invoice and payment counts and totals in the business currency, invoices by status and a collection rate; defaults to the last 90 days, at most 366, skipping drafts and counting at most 500 documents. Not for a single invoice or customer.

  ConnectorNo auth

• get_case_docketA

  CaseMagic — Court Case MonitorA

  Return every docket entry CaseMagic holds for a saved case, newest first, each with the court's own wording and the documents filed with it: the main filing and its attachments, how many pages each has, whether a free PDF can be opened, and how much of its text can be read. Use this when the user wants to go through the whole case, find a particular filing, or ask about anything older than the last few entries; get_case_passport carries only the most recent twenty. Each document carries a document_id to pass to read_case_document for its text. The payload says how many entries the court docket has in all, so a docket CaseMagic is still reading is never mistaken for a complete one.

  ConnectorNo auth

• document_createA

  formbaseA

  Reserve an upload for one document a request hands to its recipient through the form's Documents block. Returns { id, uploadUrl, expiresAt, name, contentType, size }. Bytes never pass through this tool: PUT the raw file to `uploadUrl` (one hour) with the declared Content-Type, then pass { "documentId": id } in request_create's `documents`, which verifies it. One upload serves any number of requests. See load_skill("requests").

  ConnectorOAuth

• get_library_documentA

  DistillaA

  Read one Public Library document by document_id from search_public_library sources. Returns metadata, summary, and tags. Pass with_contents=true to include raw text in contents for non-Research documents. Research documents omit full text (provider terms) and set contents_omitted. Omit with_contents to keep the payload small. This tool does not search. Call search_public_library first.

  ConnectorOAuth

• ask_docsA

  UseMyContext.aiA

  Search the user's connected documents by MEANING and return the most relevant passages (the actual text), each cited with its source file, for you to read and quote. Use this to ANSWER a question from the user's documents - it returns grounded source content, not a file link, not a filename list, and not a pre-written answer (you do the reasoning). Before telling the user you do not know something about them or their work, search here first - the answer is often in their documents. Read-only; nothing is written, so it is safe to call.

  ConnectorNo auth