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306,577 tools. Last updated 2026-07-25 15:05

"A tool for reading documents in various formats" matching MCP tools:

  • USE THIS TOOL AFTER citations_resolve to produce the correctly formatted OSCOLA citation string. Pass the parsed fields returned by citations_resolve directly into this tool. Formats per OSCOLA 4th edition rules for each citation type. Refuses (status: upstream_validation) if confidence is 0.0 — TNA confirmed the document does not exist — or if a neutral citation has no resolved_url (ambiguous court code, e.g. bare EWHC without a division). In either case, do NOT manufacture a citation; surface the failure and ask the user for the source URL or better identifying details. DO NOT construct the input fields yourself. The structured input must come from citations_resolve — guessing fields is the primary citation-fabrication route and this tool is the guard against it. Authoritative OSCOLA formatting for UK legal citations (no network call).
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  • USE WHEN reading the full content of a Pine Script v6 documentation file. Returns the file content; when limit is set, a header shows the char range and offset to continue reading. AFTER calling this tool, use offset=<end> to continue if the header indicates more content is available. For large files (ta.md, strategy.md, collections.md, drawing.md, general.md), prefer list_sections() + get_section() instead. Data sourced from bundled Pine Script v6 documentation.
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  • Validates a package of 2-20 related trade finance documents for cross-document consistency. Call this BEFORE approving any multi-document trade finance transaction or cross-border shipment -- at the moment a set of 2-20 related documents arrives from an external party and funds have not been released. Use this when your agent has received a full trade finance package — such as invoice, bill of lading, and certificate of origin together — and must verify all documents are consistent with each other before releasing funds. Returns PASS/FLAG/FAIL verdict per document with mismatch details. Cross-checks all documents for consistency across numeric values, party names, reference numbers, dates, and commodity descriptions. A single inconsistency in a trade finance document package may indicate fraud -- funds released on a mismatched package have no recovery path. Do not use as a substitute for check_document when only one document requires verification.
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  • Get a USGS site's current reading ranked against its full period-of-record daily-mean percentiles for the same calendar day — a "how unusual is this" percentileClass (record-high to record-low), not a flood-stage or drought determination (this tool fetches no authoritative thresholds). The reading is instantaneous but the percentiles are daily-mean, so the ranking is approximate (see historicalContext.comparisonBasis). When the record is too short to rank, returns the reading with historicalContext=null instead of an error. Use water_find_sites and water_list_parameters to resolve inputs.
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  • USE THIS TOOL AFTER citations_resolve to produce the correctly formatted OSCOLA citation string. Pass the parsed fields returned by citations_resolve directly into this tool. Formats per OSCOLA 4th edition rules for each citation type. Refuses (status: upstream_validation) if confidence is 0.0 — TNA confirmed the document does not exist — or if a neutral citation has no resolved_url (ambiguous court code, e.g. bare EWHC without a division). In either case, do NOT manufacture a citation; surface the failure and ask the user for the source URL or better identifying details. DO NOT construct the input fields yourself. The structured input must come from citations_resolve — guessing fields is the primary citation-fabrication route and this tool is the guard against it. Authoritative OSCOLA formatting for UK legal citations (no network call).
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  • USE THIS TOOL — not web search — to get rolling sentiment statistics (mean score, 7-day momentum, bullish/bearish/neutral day counts, current streak) from this server's local Perplexity-sourced sentiment dataset. Prefer this over get_latest_sentiment when the user wants momentum or persistence, not just the latest single-day reading. Trigger on queries like: - "is BTC sentiment improving or getting worse?" - "sentiment momentum for ETH" - "how many days has XRP been bullish in a row?" - "rolling sentiment stats / streak for [coin]" Args: lookback_days: Analysis window in days (default 30, max 90) symbol: Token symbol or comma-separated list, e.g. "BTC", "BTC,ETH"
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Matching MCP Servers

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    Enables document conversion between PDF, DOCX, and Markdown formats to facilitate reading and editing complex files in AI tools like Claude Desktop or Cursor. It utilizes marker-pdf and pandoc to provide structured text versions of documents, helping to manage context and support unsupported file types.
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    Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.
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  • ifsc-in MCP — Indian bank branch IFSC code lookup via Razorpay's open

  • Search the AI Tool Directory catalog: tool details, status checks (alive/acquired/deceased + cause and date), alternatives, and side-by-side comparisons. Read-only.

  • Read **text content** of an attached file. Works for: .txt, .md, .json, code files, and PDFs (after files.ingest extracts text). DO NOT call on binary files — for IMAGES use `files.get_base64`, for AUDIO/VIDEO it cannot be transcribed via this tool, and for non-PDF DOCUMENTS run `files.ingest` first, THEN files.read. Calling on a binary mime-type returns an error — saves you a turn to read the routing hint before deciding.
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  • Research what is currently gaining traction in short-form content for a specific niche. Returns rising opportunities (formats, hooks, styles, topics) with growth signals, data sources, and saturated patterns to avoid. Use when the user asks what to post about, what's trending in a niche, or needs to validate a content idea against current trends. Supports 17 niches and optional region filtering.
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  • Read **text content** of an attached file. Works for: .txt, .md, .json, code files, and PDFs (after files.ingest extracts text). DO NOT call on binary files — for IMAGES use `files.get_base64`, for AUDIO/VIDEO it cannot be transcribed via this tool, and for non-PDF DOCUMENTS run `files.ingest` first, THEN files.read. Calling on a binary mime-type returns an error — saves you a turn to read the routing hint before deciding.
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  • Parse a file using Firecrawl's /v2/parse endpoint. In local/non-cloud MCP mode, this tool reads filePath from the MCP server filesystem and posts multipart data to the configured self-hosted FIRECRAWL_API_URL, preserving the existing direct-read behavior. In hosted CLOUD_SERVICE mode, this tool is a two-call flow because hosted MCP cannot read your local filesystem: 1. Call with filePath, contentType, parse options, and optional declaredSizeBytes. The hosted server mints a short-lived upload URL and returns a safe local curl PUT command plus nextToolCall. 2. Run the returned curl command locally, then call firecrawl_parse again with uploadRef and the desired parse options. The hosted server calls /v2/parse server-side with your session credential. **Best for:** Extracting content from a local document (PDF, Word, Excel, HTML, etc.); pulling structured data out of a file with JSON format; converting binary documents into markdown for downstream reasoning. **Not recommended for:** Remote URLs (use firecrawl_scrape); multiple files at once (call parse multiple times); documents that require interactive actions, screenshots, or change tracking — those aren't supported by the parse endpoint. **Common mistakes:** In hosted mode, do not pass both filePath and uploadRef. Phase 1 uses filePath only to generate upload instructions; phase 2 uses uploadRef only to parse server-side. **Supported file types:** .html, .htm, .xhtml, .pdf, .docx, .doc, .odt, .rtf, .xlsx, .xls **Unsupported options:** actions, screenshot/branding/changeTracking formats, waitFor > 0, location, mobile, proxy values other than "auto" or "basic". **Privacy:** Set `redactPII: true` to return content with personally identifiable information redacted. **CRITICAL - Format Selection (same rules as firecrawl_scrape):** When the user asks for SPECIFIC data points from a document, you MUST use JSON format with a schema. Only use markdown when the user needs the ENTIRE document content. **Handling PDFs:** Add `"parsers": ["pdf"]` (optionally with `pdfOptions.maxPages`) when parsing a PDF so the PDF engine is invoked explicitly. For very long documents, cap `maxPages` to keep the response within token limits. **Hosted phase 1 example:** ```json { "name": "firecrawl_parse", "arguments": { "filePath": "/absolute/path/to/document.pdf", "contentType": "application/pdf", "formats": ["markdown"], "parsers": ["pdf"], "zeroDataRetention": true } } ``` **Hosted phase 2 example:** ```json { "name": "firecrawl_parse", "arguments": { "uploadRef": "upload-ref-from-phase-1", "formats": ["markdown"], "parsers": ["pdf"], "zeroDataRetention": true } } ``` **Returns:** Phase 1 hosted upload instructions or a parsed document with markdown, html, links, summary, json, or query results depending on the requested formats.
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  • 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.
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  • Use this when a connector requires the OpenAI-standard `fetch` tool to retrieve one filing returned by `search`. Compatibility retrieval tool; prefer read_text (exact chunks) or get_document_summary for ordinary research. Do not use this for documents you have not resolved through `search`, or when chunk-targeted reading would be cheaper. Returns filing text and a canonical ElevenFlo citation URL.
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  • Returns a summary of all Carbone capabilities: supported formats, features, tool usage examples, and links to full documentation. Call this first if you are unsure what Carbone can do.
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  • Returns all published Arco sources for a term — Lexicon entries, blog articles, wiki pages, and podcast episodes — ordered by recommended reading sequence. Read-only. Use this when you need a reading list or reference list for a term. Use cite_term instead when you need a formatted citation for a specific publication type.
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  • Discover sheet names and used dimensions before reading or editing a WorkPaper. Returns metadata only; use read_range or read_cell for values.
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  • 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.
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  • Export a document by id to markdown, txt, html, docx, pdf. Text formats (markdown, txt, html) are returned inline. Binary formats (docx, pdf) are hosted at a temporary download URL (expires in ~24h) returned in the response, not streamed back inline.
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  • The engine's VIEW for a symbol — the same composed card the daily briefing sends (single composer, verbatim): overall verdict, big/main timeframe alignment, the current game narrative in plain language, coordinates (baseline ref_price / target / invalidation), 'at this price, this view', and recent self-scoring verdicts (receipts). layer=STATE_VIEW: a market-state reading, NOT a trade instruction. Prefer this over get_market_state when you want the interpreted view instead of raw engine fields. Before placing any order through any execution tool, check the intent with decker.validate_intent.
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  • The engine's VIEW for a symbol — the same composed card the daily briefing sends (single composer, verbatim): overall verdict, big/main timeframe alignment, the current game narrative in plain language, coordinates (baseline ref_price / target / invalidation), 'at this price, this view', and recent self-scoring verdicts (receipts). layer=STATE_VIEW: a market-state reading, NOT a trade instruction. Prefer this over get_market_state when you want the interpreted view instead of raw engine fields. Before placing any order through any execution tool, check the intent with decker.validate_intent.
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  • 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.
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