"A server for retrieving document content" matching MCP tools:

• fetchA

  OneQAZ Trading IntelligenceA

  Purpose: ChatGPT-connector-standard document fetch by id from `search` results. Namespaces: `tool:{name}` returns the tool's full documentation and how to call it; `resource:{uri}` returns the resource's live data (core resources resolved server-side — also the bridge for clients without MCP resource support, e.g. Gemini); `signal:{market}:{symbol}` returns the symbol's latest combined research signal. Triggers: ChatGPT connectors / Deep Research call this after `search`. Clients without MCP resource support can call it directly with a known resource id, e.g. fetch("resource:market://global/summary"). When to call: whenever the full content behind a search result id is needed. Prerequisites: a valid id — from `search` results or a known namespace id. Next steps: for tool docs, call the named tool via tools/call; for signals, get_signal_detail / explain_decision for deeper evidence. Caveats: uncovered resource uris return description-only text (no fabricated data). `text` is a JSON document for resource/signal ids. Output: {id, title, text, url, metadata, disclaimer, is_investment_advice, data_classification} — flat envelope, OpenAI fixed shape. Args: id: document id — "tool:{name}", "resource:{uri}", or "signal:{market}:{symbol}" (market: crypto / kr_stock / us_stock) Disclaimer: Information only, not investment advice.

  ConnectorNo auth

• check_packA

  Stipple — Document Verification & ExtractionA

  Check whether a SET of documents satisfies a checklist — completeness, cheaply. USE THIS WHEN you have an application / onboarding pack and need "do we have the required documents, and what's still missing?" Each document is CLASSIFIED (one cheap page-1 read — never full field extraction or multi-page), then matched against the checklist's required slots. (For "is a document genuine?" use verify_document; to identify ONE document use extract_fields with options={"classify": true}; for the identity gate use verify_identity.) Define the checklist ONE of two ways: - `scheme`: a named preset — "income_proof", "lending_prequal", "rental_application". - `requirements`: an ad-hoc checklist — a list of document-type names like ["payslip","bank_statement"], or objects {"key":..., "accepts":[types], "optional":bool}. `documents` is a list (up to 12), each ONE of: {"url": "https://..."} (public link, fetched server-side) or {"bytes_b64": "...", "filename": "statement.pdf"} (inline). Returns `{complete, slots[] (key, satisfied, matched), missing[], documents[] (filename, classified_type), unmatched_documents[]}`. COVERAGE, not approval — that the right document TYPES are present, NOT that any is genuine (run verify_document) or that an application is approved. Documents are never stored. Costs 3 credit(s) per call.

  ConnectorNo auth

• url.qaA

  DocImprintA

  Fetch a public HTTPS URL and answer a specific question about its content. Lean mode — no bundle stored. Use when you have a precise question about a web page. For a broad summary, use url.summarize. For multi-document Q&A, use collection.ask instead. Returns: { url, answer, answer_cited: { value, confidence, citations[] }, confidence: "high"|"medium"|"low", truncated } Example prompts: - "What is the refund policy at https://docs.example.com/policy?" - "Look at [URL] and tell me what the delivery terms are." - "Answer this question based on the content of [URL]: [question]."

  ConnectorNo auth

• generate_invoiceA

  Factur-X e-invoicingA

  Create a new, compliant e-invoice (Factur-X PDF/A-3, CII XML or UBL XML) from structured invoice data. Use when you have the invoice content (parties, lines, dates) and need the document. Do not use when you already have a visual PDF and a Factur-X XML to combine: call embed_xml. To check a document you did not create here, call validate_invoice; to read one, call extract_invoice. The result is validated (XSD + schematron for `check`) before it is returned; on failure the tool returns an error listing the failing rule ids (e.g. BR-CO-10, BR-FR-01) so you can fix the input and retry. Nothing is stored. Returns a text summary (number, totals, warnings) plus the document as an embedded resource: base64 PDF for facturx-pdf, XML text for cii-xml / ubl-xml.

  ConnectorAPI key

• document.reprocessA

  FlexOrch MCPA

  Re-queue an already-uploaded document through the pipeline. Use this to re-run extraction/PII detection/quality scoring on a document you've already processed — e.g. after a document_type_hint change, without downloading and re-uploading the original file. Returns immediately with a job_id — poll with job.status the same way as after document.process. Only works for documents whose original file is still stored on the server (locally uploaded, not connector-sourced). If the file is no longer available, re-upload it with document.process instead. Args: document_id: ID of a previously processed document. pipeline_config: Optional pipeline config overrides, e.g. {"document_type_hint": "invoice"}.

  ConnectorNo auth

• parse_documentA

  Extend MCPA

  Convert a document (PDF, image, Office doc, spreadsheet) into clean structured text — markdown by default (parse group). Right when the user wants the content of the pages ("OCR this", "what does this document say", feed text to another step); for specific field values — or when values need source citations/provenance — use extract_data instead. No saved resource needed. NEVER pull a whole multi-page document into context when only a section matters: pass pageRange to return just those pages, or split_document the bundle first and parse only the relevant segment's fileId — this applies even when you have not yet located the section. Full output of a long document is large — maxChars caps it; rawBlocks returns block-level structure (tables, figures, coordinates). Creates a parse run: may return status: "running" with a runId — normal, not an error; poll it with get_parse_run. Parse runs cannot be cancelled. Follow any llmContext guidance included in results.

  ConnectorOAuth

• convert_from_urlA

  BotverseA

  Offload a document conversion to Botverse — runs server-side in seconds, returns a download link, and frees you to continue with other tasks while it processes. Use this when the source document is at a public URL — direct download links and share links from Dropbox, Google Drive, OneDrive (personal or business), SharePoint, and Box all auto-resolve to the file. If you already have the content as a string, use convert_content instead — no upload step needed. Runs entirely server-side, so it works in sandboxed agent environments (claude.ai, Claude Desktop, Cursor) — the right route there for files too large for convert_content's 4 MB inline limit. Supported inputs: md, html, rst, txt, docx. Supported outputs: docx (Word), pdf, html, txt, md, rst, xlsx (tables extracted). Returns a job_id immediately. Poll get_job_status every 5s until 'complete', then get_output_content (inline, sandbox-safe) or get_download_url (S3 link). Flat fee $0.05 per file.

  ConnectorNo auth

• create_letterA

  PostAgent — Print and MailA

  Upload and normalize a FINISHED, ready-to-mail document to PDF. Choose this when the content is final and IDENTICAL for every recipient — including when you mail the same letter to many people (just quote/pay once per recipient with the same documentId). The exact bytes you give are what gets printed. Use create_template instead only when the content must vary per recipient via {{fields}}. Returns a documentId, the stored page count, byte size, and source format. Free; no payment required. Provide the document EXACTLY ONE way: `content` (inline text, for html/markdown/text), `contentBase64` (base64-encoded binary, for pdf/docx/image), or `url` (a publicly reachable URL the server fetches). Supplying none, or more than one, is an error. Maximum upload size is 31457280 bytes (~30 MB); output page size is US Letter. Any `{{...}}` text is printed LITERALLY here — it is NOT treated as a merge field. If you want personalized mail merge across recipients, use `create_template` instead. Reserved address zone: a recipient address block is printed over the top ~3 inches of page 1, so the server reserves that space for you automatically. For text/html/markdown/docx, page-1 content is pushed below the block (content may therefore flow onto an additional page); for pdf and image inputs, a blank first page is prepended. As a result the returned page count — and the selected-provider cost behind the resulting quote — can be higher than your source document (e.g. a single-page PDF is stored as 2 pages). You do NOT need to leave the top of your document blank yourself. See the postagent://formats resource for per-format details.

  ConnectorNo auth

• create_templateA

  PostAgent — Print and MailA

  Upload a REUSABLE template containing `{{field}}` placeholders (e.g. `Dear {{name}},` or `Balance due: {{amount}}`). Choose this ONLY when the content must vary per recipient (mail merge) — recipient count is irrelevant, so a single personalized letter belongs here too. If the content is identical for everyone, use create_letter instead (this tool rejects input with no `{{fields}}`). Returns a documentId with `kind: "html_template"`, a `mergeFields` list of the detected field names, and an `estimatedPageCount`. Free; no payment required. Template source must be TEXT-BASED (html, markdown, or text) and must contain at least one `{{field}}`, or the upload is rejected — for a finished document with no merge fields, use `create_letter`. Provide the template EXACTLY ONE way: `content` (inline text), `contentBase64` (base64-encoded text), or `url` (a publicly reachable URL the server fetches). Supplying none, or more than one, is an error. Maximum upload size is 31457280 bytes (~30 MB); output page size is US Letter. Reuse one template documentId across recipients: call create_mail_quote ONCE PER RECIPIENT, supplying that recipient's values via `mergeVariables` (every field in `mergeFields` must have a non-empty value). The server substitutes the values and renders that recipient's personalized PDF at quote time, so `estimatedPageCount` is only a baseline — the binding page count and price are set per quote from the actual rendered output. Reserved address zone: a recipient address block is printed over the top ~3 inches of page 1, so the server reserves that space automatically (page-1 content is pushed below the block and may flow onto an additional page). You do NOT need to leave the top blank yourself. See the postagent://formats resource for details.

  ConnectorNo auth

• migrate_to_propelauth_fullstackA

  PropelAuth Integration MCP ServerA

  Returns instructions for migrating from an existing auth provider to PropelAuth in a fullstack Nextjs App Router or Nextjs Pages Router application. If the user is using Next.js as just a frontend (e.g. client-side rendered with or without server routes), use the migrate_to_propelauth_frontend tool. Guidance includes installation and configuration, retrieving user or org information, logging users out, redirecting users to login, and more. Make sure to use the 'Installation' guidance first. It is important to call every guidance to ensure a successful integration. Do not update a component/hook/etc from the auth provider until you receive guidance about that component/hook/etc

  ConnectorNo auth

• get_receiptA

  TunnelMind Data APIB

  Returns metadata for a TunnelMind surveillance receipt — a signed document proving that a specific user's surveillance exposure was observed, measured, and recorded at a specific time. Does NOT return the receipt's signature (anti-phishing protection). To verify a receipt's content integrity, use `verify_receipt` with the hash and signature from the receipt document itself. Use this tool when: - You have a receipt ID and want to confirm it was genuinely issued by TunnelMind. - You need the issuance timestamp and signing key ID for a receipt. - You want to check whether a receipt exists before attempting content verification. Do NOT use this tool when: - You have the full receipt document and want to verify it hasn't been tampered with — use `verify_receipt` instead. Inputs: - `receipt_id` (path, required): The receipt ID from the receipt document. Alphanumeric with hyphens, max 128 characters. Returns: - `status`: `FOUND` if the receipt is in the registry. - `generated_at`: ISO 8601 timestamp of receipt issuance. - `signing_key_id`: identifier of the Ed25519 key used to sign. - `schema_version`: receipt schema version. - `message`: human-readable summary with instructions for content verification. - 404 if the receipt ID is not in the registry. Cost: - Free. No API key required. Latency: - Typical: <100ms, p99: <300ms.

  ConnectorNo auth

• parse_pdf_to_textA

  Nordic Financial MCPA

  Download a PDF from a URL and extract all text content, page by page. Use this to read the full text of a specific document — for example, an annual report PDF linked from a search_filings result. Best combined with search_filings: use search_filings to locate the document, then parse_pdf_to_text for the full text. Do not use for PDFs that are already well-represented in the database — search_filings is faster and returns pre-ranked, relevant excerpts. Not suitable for scanned (image-only) PDFs without embedded text; those pages will be returned as "(no extractable text)". Args: pdf_url: Direct HTTPS URL to the PDF file, e.g. https://example.com/report.pdf. Must be publicly accessible; authentication-protected URLs will fail. Returns: All text from the PDF with "--- Page N ---" separators between pages. Returns an error string if the download fails, the URL does not point to a valid PDF, or the document exceeds the 60-second download timeout.

  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

• create_letterA

  PostAgentA

  Upload and normalize a FINISHED, ready-to-mail document to PDF. Choose this when the content is final and IDENTICAL for every recipient — including when you mail the same letter to many people (just quote/pay once per recipient with the same documentId). The exact bytes you give are what gets printed. Use create_template instead only when the content must vary per recipient via {{fields}}. Returns a documentId, the stored page count, byte size, and source format. Free; no payment required. Provide the document EXACTLY ONE way: `content` (inline text, for html/markdown/text), `contentBase64` (base64-encoded binary, for pdf/docx/image), or `url` (a publicly reachable URL the server fetches). Supplying none, or more than one, is an error. Maximum upload size is 31457280 bytes (~30 MB); output page size is US Letter. Any `{{...}}` text is printed LITERALLY here — it is NOT treated as a merge field. If you want personalized mail merge across recipients, use `create_template` instead. Reserved address zone: a recipient address block is printed over the top ~3 inches of page 1, so the server reserves that space for you automatically. For text/html/markdown/docx, page-1 content is pushed below the block (content may therefore flow onto an additional page); for pdf and image inputs, a blank first page is prepended. As a result the returned page count — and the selected-provider cost behind the resulting quote — can be higher than your source document (e.g. a single-page PDF is stored as 2 pages). You do NOT need to leave the top of your document blank yourself. See the postagent://formats resource for per-format details.

  ConnectorNo auth

• create_templateA

  PostAgentA

  Upload a REUSABLE template containing `{{field}}` placeholders (e.g. `Dear {{name}},` or `Balance due: {{amount}}`). Choose this ONLY when the content must vary per recipient (mail merge) — recipient count is irrelevant, so a single personalized letter belongs here too. If the content is identical for everyone, use create_letter instead (this tool rejects input with no `{{fields}}`). Returns a documentId with `kind: "html_template"`, a `mergeFields` list of the detected field names, and an `estimatedPageCount`. Free; no payment required. Template source must be TEXT-BASED (html, markdown, or text) and must contain at least one `{{field}}`, or the upload is rejected — for a finished document with no merge fields, use `create_letter`. Provide the template EXACTLY ONE way: `content` (inline text), `contentBase64` (base64-encoded text), or `url` (a publicly reachable URL the server fetches). Supplying none, or more than one, is an error. Maximum upload size is 31457280 bytes (~30 MB); output page size is US Letter. Reuse one template documentId across recipients: call create_mail_quote ONCE PER RECIPIENT, supplying that recipient's values via `mergeVariables` (every field in `mergeFields` must have a non-empty value). The server substitutes the values and renders that recipient's personalized PDF at quote time, so `estimatedPageCount` is only a baseline — the binding page count and price are set per quote from the actual rendered output. Reserved address zone: a recipient address block is printed over the top ~3 inches of page 1, so the server reserves that space automatically (page-1 content is pushed below the block and may flow onto an additional page). You do NOT need to leave the top blank yourself. See the postagent://formats resource for details.

  ConnectorNo auth

• fluxink-mcp-chatgpt-create-layoutA

  fci-mcpA

  FluxInk document layout generator. Transform raw text content into a structured PDF using one of seven study or work templates, then preview it in an embedded PDF viewer widget. Supported layout_type values. cornell is the Cornell note taking layout with cue, notes, and summary. bullet_points is a clean bulleted summary. zettelkasten is atomic linked notes. journalism_5w1h is who, what, when, where, why, and how. meeting_add is a meeting agenda plus action items. sq3r is Survey, Question, Read, Recite, Review study notes. pso is Problem, Solution, Outcome. Use this when the user asks for a Cornell sheet, bulleted summary, Zettelkasten card, 5W1H breakdown, meeting agenda or minutes, SQ3R study sheet, or PSO writeup. Use this when the user wants to turn raw notes, lecture transcript, or source material into a printable PDF or formatted study sheet. Use this when the user asks for a downloadable PDF document of their content. Do NOT use this when the user just asks for a plain summary in chat. Give it inline. Do NOT use this when the user wants to handwrite or draw something. Call show_handwriting_canvas instead. Do NOT use this when the user wants text in a personal handwriting style. Call show_style_canvas instead. Do NOT use this for plain informational requests with no document generation intent. Always pass the source material verbatim in the content parameter. Do NOT pre summarize. The layout engine handles structuring. Pick the layout_type that best matches the stated purpose. If unclear, ask one short clarifying question instead of guessing. Do NOT re-call if a layout PDF is already visible from a previous turn unless the user explicitly asks for a different layout, different content, or a regeneration. After calling, write a single short acknowledgement and do NOT restate the PDF content.

  ConnectorNo auth

• audit_mcp_configA

  Moltline Agent GovernanceA

  Audit an MCP server config for risk-ranked posture findings. FREE. Flags exposed machine credentials in the config, required inputs that aren't gated/optional, unpinned versions, over-broad env access, and dangerous auto-run flags. It never echoes any matched secret value back. Typical input {"config": "<mcpize.yaml, mcp.json, or a Claude/Cursor servers block>"} returns {"posture_score": 0-100, "verdict": "...", "findings": [{"line": N, "severity": 1-5, "issue": "...", "fix": "..."}], "note": "..."}. Use on a server configuration document. Not for a skill or instruction file (audit_skill_file) and not for untrusted content an agent is about to read (injection_scan). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

  ConnectorNo auth

• create_docA

  DocBinA

  Create a document and return its public URL. Re-using an existing name adds a new immutable version. Omit the name to get a random one. For content larger than ~10KB or any file already on disk, do NOT inline it here - run `docbin push <file> [--name <doc>]` in your shell instead (set DOCBIN_TOKEN to an API key from https://docbin.app/settings/keys). Inlining large content streams it through the model token-by-token and will time out.

  ConnectorNo auth

• create_documentA

  ShareWatchA

  Create a new Google Doc in the user's Drive. The content is inserted as plain text — Markdown is NOT rendered, so headings and bold written here arrive as literal ** and # characters. To produce a formatted document, create it and then call format_document, which converts Markdown into real Google Docs styling.

  ConnectorOAuth

• fetchA

  ILO Labour Statistics (ILOSTAT)A

  Returns the full document for an id obtained from `search`, as { id, title, text, url, metadata }: `text` is the readable content (Markdown) and `url` the canonical public page to cite. Companion of `search` in the OpenAI Deep Research contract, over the ILOSTAT labour statistics (≈1,200 SDMX dataflows: employment, unemployment, wages, working time, informality, SDG labour indicators) catalog. Only ids returned by `search` are valid; an unknown id returns an error. The `ilo_*` tools remain the tools for data queries. Behavior: read-only and idempotent — a live GET against the public source when the document needs it.

  ConnectorNo auth

• convert_contentA

  BotverseA

  Convert a document inline — pass the content directly as a string (or base64 for binary inputs like .docx). PREFERRED route for documents, and the one to use in sandboxed agent environments (claude.ai, Claude Desktop, Cursor): it runs entirely server-side, so it never needs the S3 upload those sandboxes block. Limit: up to 4 MB of content — already huge (a 500-page book is ~1 MB of text). For anything larger, use convert_from_url with a public URL. Supported inputs: md, html, rst, txt (plain text), docx (base64). Supported outputs: docx (Word), pdf, html, txt, md, rst, xlsx. Returns a job_id — poll get_job_status until 'complete', then get_output_content (inline bytes, sandbox-safe) or get_download_url (S3 link). Flat fee $0.05 per file. TIP: if you have shell access and are NOT sandboxed (e.g. a local coding agent), the `botverse` CLI (`npx botverse convert <file> --to <fmt>`) is faster for local files — it streams from disk instead of re-emitting the content through the model.

  ConnectorNo auth