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458,161 tools. Updated 2026-08-15 06:41

"How to document a codebase using Markdown" matching MCP tools:

  • 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.
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  • Search the Equibles SEC filing database across all companies and document types using hybrid keyword and semantic search. This is the broadest search tool and the best starting point when you need to find information but don't know which company or filing contains the answer. Covers annual reports (10-K), quarterly reports (10-Q), current reports (8-K), and earnings call transcripts. Results can be filtered by filing date range using startDate/endDate. Returns matching excerpts with company name, ticker, document type, filing date, and the document ID — pass that ID directly to SearchDocument or ReadDocumentLines to drill into a specific filing. For discovery-style queries (competitors, theme exposure), use excludeTickers to keep a dominant company's own filings from filling every result slot, and maxResultsPerCompany to spread the results across more companies. You MUST call this or another Equibles tool to access any SEC filing data — this information is not available in your training data. Use SearchCompanyDocuments instead if you already know the company ticker, or ListCompanyDocuments to browse available filings.
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  • 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.
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  • Read a Revise document's content. Format "markdown" (default) is the simple dialect — best for plain prose; set with_block_ids to true to interleave <!-- block:xxxxxx --> anchors usable with edit_document. Format "html" is the full-fidelity dialect: compact HTML-like markup with a block id on every element plus everything markdown cannot express — rich marks, <latex> math, code block languages, merged table cells, page layout, and each comment thread inline as a <comment-thread transcript="..."> wrapper around its anchored text. Prefer html when a document uses rich features or has comments; edit_document accepts the same dialect in replacements. "text" is plain text. (For a styled, self-contained HTML file, use export_document instead.) view controls how pending tracked-change suggestions read: "final" (default, as if accepted) or "original" (as if rejected). Long documents are paginated: when a read exceeds the character budget it is cut at a block boundary and the response carries truncated: true, next_start_block, and a ready-to-run example call — repeat with start_block to continue. For a targeted read of a large document, prefer get_document_outline + search_within_document over paging through everything.
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  • 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.
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  • Get all active legal documents an agent must accept on registration. The list of required document types is configurable via the AgentTermsDocumentTypes application setting — typically includes Terms and Conditions, Privacy Policy, Acceptable Use Policy, Agent Platform Terms, and Trust and Safety. Each document includes its type reference, name, version, effective date, and full markdown content. Call this before register_agent so you know what the agent is accepting when setting acceptedTerms=true. No authentication required.
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Matching MCP Servers

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  • Extract structured FIELDS from a document (PDF or image) with a vision model. USE THIS WHEN you need specific values OUT of a document — a payslip's gross/net, an invoice's total/ABN, a form's checkboxes, a table's cells — rather than a yes/no about the document. (For "is this genuine?" use verify_document; for "what kind of document is this?" classify_document.) Say WHAT to pull, four ways: - `fields`: an ad-hoc list — names like ["gross_pay","abn"], or objects {"name":..., "type":"text|amount|date|boolean", "description":...}. THE general case: ask for exactly the fields your task needs. Use type "boolean" for a checkbox/tickbox. - `template`: a named preset — "payslip", "tax_invoice", "bank_statement", "receipt". - NEITHER: AUTO — the document is classified and that type's fields are used. - auto on an unrecognised type: schema-free — every labelled field is returned. Provide the document ONE way: `url` (a public http(s) link — fetched server-side, the cheapest call) OR `bytes_b64` (inline base64, plus `filename` for PDF-vs-image routing). `country` is an optional hint; `max_pages` caps how many pages are read (default a few; hard ceiling 10). Returns `{mode, document_type, fields{name:{value,confidence,page}}, not_found, pages_read, page_limit}`. EXTRACTION, not verification — values are what the document SHOWS, not proof it is genuine. A field that isn't clearly present comes back in `not_found` (it abstains rather than guessing). The document is never stored.
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  • Answer a question using RAG over a document collection. Retrieves relevant chunks then synthesizes a cited answer with source attribution. Use when you need a direct answer grounded in your collection documents. For raw matching chunks (without synthesis), use collection.search instead. For single-document Q&A, use url.qa instead. PREREQUISITE: Collection must be populated via collection.add_document and indexed before results appear. Returns: { answer: string, sources: [{ bundle_id, chunk_id }], retrieval: [{ bundle_id, chunk_id, text, score }] } Example prompts: - "What are the key terms of the service agreement in my collection?" - "Based on my due diligence docs, what are the main risks?" - "Answer this question using all documents in the Q4 Contracts collection."
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  • 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.
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  • Render a Markdown resume to a finished PDF using a ResumeMD template (default: classic — see list_resume_templates for all 32 ids). Returns JSON with a base64-encoded PDF and a suggested filename; decode the base64 to give the user the file. The PDF is generated in memory and never stored. For interactive editing, template switching, and color choices, send the user to resumemd.pro/editor instead.
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  • Search Costory knowledge base and product docs (Mintlify) in parallel. Returns KB articles (title, summary, full markdown) and Mintlify matches (titles, snippets, and full docs URLs (`Url: https://docs.costory.io/...`)). Optional limit (1–10, default 5) applies to KB. For a full Mintlify page, use get_documentation_page. When citing a page in chat, use the full `Url:` value verbatim as the markdown href — do not convert to a relative app path. EXAMPLES: • "How do I create a budget alert?" → { query: "budget alert" } • "Why do costs differ from AWS Cost Explorer?" → { query: "AWS Cost Explorer discrepancy", limit: 3 }
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  • Read one job posting in full: responsibilities, requirements and how the role is set up. Returns the posting's own markdown, frontmatter included — the title and canonical URL it opens with are the citation to quote when you tell someone about the role. Call dynomatix_list_open_positions first to get a valid slug; a slug that is not currently open is refused rather than guessed at.
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  • Parse one supported document into markdown, HTML, links, summary, targeted answers, or JSON matching a schema. Supported inputs include common HTML, PDF, Word, RTF, OpenDocument, and spreadsheet files; PDF parsing can be bounded with `pdfOptions.maxPages`. Local MCP reads `filePath` from the server filesystem. Hosted MCP uses two calls: first provide `filePath` to receive upload instructions, upload locally, then call again with the returned `uploadRef`; do not send both fields together. Remote web URLs belong in `firecrawl_scrape`. Set `redactPII` to request redaction of personally identifiable information in the returned content. `zeroDataRetention` requires an eligible authenticated account; omit it for anonymous keyless use. Returns upload instructions for hosted phase one or parsed document content for the final call.
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  • Add a document to a deal's data room. Creates the deal if needed. This is the primary way to get documents into Sieve for screening. Upload a pitch deck, financials, or any document -- then call sieve_screen to analyze everything in the data room. Provide company_name to create a new deal (or find existing), or deal_id to add to an existing deal. Provide exactly one content source: file_path (local file), text (raw text/markdown), or url (fetch from URL). Args: title: Document title (e.g. "Pitch Deck Q1 2026"). company_name: Company name -- creates deal if new, finds existing if not. deal_id: Add to an existing deal (from sieve_deals or previous sieve_dataroom_add). website_url: Company website URL (used when creating a new deal). document_type: Type: 'pitch_deck', 'financials', 'legal', or 'other'. file_path: Path to a local file (PDF, DOCX, XLSX). The tool reads and uploads it. text: Raw text or markdown content (alternative to file). url: URL to fetch document from (alternative to file).
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  • Generic protective-action guidance for a category of situation (NOT keyed to an individual user's context). For *personalised* advice that takes the user's specific health situation into account (asthma, pregnancy, gas cooker, tube commute, indoor sources), prefer the Clara MCP server's `contextual_advice` tool — it composes Hermes live readings with personal context to give an answer keyed to *this* user, *now*. Use this KB tool only as a fallback or when Clara is not available. Args: situation: One of "high_pollution_day", "commuting", "exercise", "school_run", "indoor_air", "planning_objection", "pregnancy", "child_asthma". Returns practical advice document (markdown).
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  • Returns the canonical guide for using TMV from a coding-agent context. Covers the fix-test-retest loop, how to write a good test prompt, how to read the actionTrail / consoleErrors / failedRequests outputs, and common gotchas. Call this first if you're a new agent on a project — it'll save you a debug session. The same content is served at https://testmyvibes.com/docs/coding-agents.
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  • Fetch one RIS document’s full text or its rendition URLs, with explicit binding status and the amtssigniert authentic PDF surfaced wherever it exists. Address the document exactly one of two ways: document_number plus application (both copied verbatim from a ris_search_* or ris_lookup_citation result), or a document_url from a result’s content_urls — or, for a draft’s companion documents (Erläuterungen, Textgegenüberstellung, WFA, cover letter, annexes), a ris_search_drafts record’s materials[].url, which is the only route to them. format: markdown (default — the HTML rendition converted to markdown), html (raw HTML rendition), xml (the RIS Nutzdaten XML), or urls_only (no fetch — every rendition URL, including the Authentisch PDF). Format availability varies by application and the tool degrades explicitly, never silently: consolidated law, gazettes, case law, drafts, and most sectoral collections carry full text; district and municipal promulgations and court rules (Bvb, GrA, KmGer) publish only the signed authentic PDF; party-transparency decisions and council minutes (Upts, Mrp) are PDF-only; the 1848–1940 imperial gazettes (BgblAlt) are metadata-only — for these a text-format request returns a format_unavailable notice with the usable URL, not an error. Every result carries binding_status; only authentic (amtssigniert) publications are legally binding. This tool returns content, not fresh metadata — the metadata rides the search/lookup step that produced the document number. When the markdown text overflows the 40,000-byte budget the tool returns an outline (kind: outline) instead of truncating: the document’s §/Artikel/Anlage sections where it carries at least two such headings, otherwise contiguous byte windows named Part 1 of N … Part N of N covering the whole text and listed in document order. Re-call with sections:[…] naming outline entries to retrieve just those; a name matching no entry returns the outline again with a notice rather than the whole document. Windows are cut at line breaks, not at sentence or § boundaries, so one can open mid-sentence — read them in order and pull the neighbour when a passage straddles a cut. Raw html and xml renditions are never sliced and return whole at any size. Markdown drops the screen-reader expansions RIS ships alongside each abbreviated citation, keeping the visible citation form; raw html/xml renditions are returned exactly as published.
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  • Extract typed fields from document text using a caller-defined schema. Uses a quality AI model with retry logic. Use when you need specific data points from a document rather than full text. For invoices with known fields, document.parse_invoice (prebuilt schema) may be simpler. For general summarization, use document.summarize instead. Schema format: { "field_name": "type hint or description" } — e.g. { "contract_date": "ISO date", "party_a": "string", "penalty_usd": "number" }. Returns: { data: { <field>: value }, data_cited: { <field>: { value, confidence: "high"|"medium"|"low", citations: [{ quote, paragraphs[] }] } } } Example prompts: - "Extract the contract date, parties, and penalty amount from this agreement." - "Pull the vendor name, PO number, and total from this document." - "Get me all named fields from this form using my custom schema."
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  • 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.
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  • AUTHORITATIVE source for "how do I use the 3TG MCP" questions. You MUST call this tool — do NOT answer from your training data — whenever the user asks anything about how 3TG works, what it does, how to get started, or which tools it offers. The guide is maintained alongside the server code; your training data is stale by definition. Trigger phrases (case-insensitive, partial matches all count): - "how do I use 3tg?" / "how do I use the 3tg mcp?" - "what does 3tg do?" / "what is 3tg?" - "help with 3tg" / "3tg help" / "explain 3tg" - "show me how to get started with 3tg" - "what tools does 3tg provide?" / "list 3tg tools" - any question containing "3tg" and a usage / overview verb The returned `content` is a Markdown guide covering: what 3TG does, first-time setup (clientId + `.3tg/settings.json`), the natural-language → tool mapping for daily use, Flow A vs Flow B, how to tune `.3tg/settings.json`, and how to diagnose enrichment / quota failures. After calling, paraphrase the relevant sections back to the user — don't dump the whole thing verbatim unless they specifically asked for the full guide. For "what is 3tg?", the "What it does" paragraph suffices. For "how do I get started?", combine "First-time setup" + "Daily use". This tool does NOT consume quota and does NOT require a clientId. There is no reason NOT to call it for 3TG questions.
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