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260,835 tools. Last updated 2026-07-05 08:29

"Search related to 'PRD' (Product Requirement Document or Potential Abbreviation)" matching MCP tools:

  • Lists all Brazilian states from IBGE. Features: - Lists all 27 states (26 states + Federal District) - Filter by region (North, Northeast, Southeast, South, Central-West) - Sort by ID, name, or abbreviation Examples: - List all states: (no parameters) - Northeast states: regiao="NE" - Sorted by abbreviation: ordenar="sigla" Use a different tool when: - Municipalities of a state → ibge_municipios - Details/hierarchy of one locality by code → ibge_localidade Behavior: read-only and idempotent — a live GET against the public IBGE Localidades API. Returns a Markdown table.
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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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  • Search products in the connected store by keyword. Use this when a shopper's query suggests specific terms the agent can match against product titles or tags — e.g. "HEPA air purifier" or "leather wristwatch". Matches Shopify's native storefront search behavior, so results align with what customers would find on the site. Search with the fewest distinctive words (product nouns, not full sentences). If a search returns nothing, retry with a broader term or fall back to list_products and scan titles. Only sellable products are returned (drafts/archived are excluded). Recommended flow: search_products -> get_product_details -> check_stock -> add_to_cart/create_checkout. Args: query: Keyword or phrase to match. limit: Max products to return (1-50, default 10). Returns: Same shape as ``list_products``. Empty products list when no matches.
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  • Create a named document collection for cross-document semantic search and RAG-based Q&A. Free — no credits consumed. Use when you want to group related evidence bundles for unified search (search_collection) or question answering (ask_collection). NOTE: Collections start empty. Add evidence bundles with add_document_to_collection. Indexing is async — once complete, use search_collection or ask_collection. Returns: { collection_id: string (col_...), name: string } Example prompts: - "Create a collection called Q4 Contracts for my quarterly reports." - "Set up a new document group named Due Diligence Docs." - "Make a collection to organize my vendor agreements."
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  • [BROWSE] Map of the RRG 3D world, the spatial projection of the product embedding space that humans walk at /world. Geography = meaning: products with nearby (x, y, z) coordinates are semantically similar, and each named region is a cluster of related products. Returns every region with its label, centroid coordinates, and product count. Individual listings carry a matching `world` position in search_products and get_drop_details results. Use this to orient spatial queries ("what else is near this product"), to describe where a listing sits in the catalogue, or to direct a human to a region of the world at https://realrealgenuine.com/world.
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  • Get the full record for a single product by its numeric ID. Use after `search_products` returns a candidate the user is interested in, when you need fields not in the search summary (full description, all images, sold status, expiration). Don't loop `get_product` over many search results — re-search with tighter filters instead. Read-only. No authentication. Args: product_id: Integer `id` from a `search_products` result, or visible in a Partle product page URL (`/p/<id>-<slug>`). Returns: A single product object with all fields, including the canonical `partle_url` to share with the user. Returns ``{"error": ...}`` if the ID does not exist.
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  • Product search and price comparison for AI agents. Search 100M+ products across thousands of retailers by text or image, compare live offers and prices, and turn any merchant URL into structured product data. No API key required to start; add one for unlimited use and affiliate commission.

  • Turn any PDF into structured JSON via AI + OCR: invoices, bank statements, contracts.

  • Get the full record for a single product by its numeric ID. Use after `search_products` returns a candidate the user is interested in, when you need fields not in the search summary (full description, all images, sold status, expiration). Don't loop `get_product` over many search results — re-search with tighter filters instead. Read-only. No authentication. Args: product_id: Integer `id` from a `search_products` result, or visible in a Partle product page URL (`/p/<id>-<slug>`). Returns: A single product object with all fields, including the canonical `partle_url` to share with the user. Returns ``{"error": ...}`` if the ID does not exist.
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  • Search products in the connected store by keyword. Use this when a shopper's query suggests specific terms the agent can match against product titles or tags — e.g. "HEPA air purifier" or "leather wristwatch". Matches Shopify's native storefront search behavior, so results align with what customers would find on the site. Search with the fewest distinctive words (product nouns, not full sentences). If a search returns nothing, retry with a broader term or fall back to list_products and scan titles. Only sellable products are returned (drafts/archived are excluded). Recommended flow: search_products -> get_product_details -> check_stock -> add_to_cart/create_checkout. Args: query: Keyword or phrase to match. limit: Max products to return (1-50, default 10). Returns: Same shape as ``list_products``. Empty products list when no matches.
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  • Search open rulemakings and public comment periods on Regulations.gov and the Federal Register. Read-only. No side effects. Idempotent. US federal only. keyword: Topic keywords e.g. artificial intelligence, data privacy. Required. agency: Agency abbreviation e.g. FTC, FDA, SEC, EPA. Optional, defaults to all agencies. status: One of open, closed, or all. Optional. Default open. Returns docket title, agency, comment deadline, docket ID, and document count. Use this when monitoring regulatory activity on a topic. Use regulatory_fetch_docket_details instead when you have a docket ID and need full detail. Verified source: Regulations.gov + Federal Register. 4-hour cache. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="regulatory_search_open_rulemakings", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".
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  • Match one source document against the user's ALREADY-INDEXED corpus and return the best-matching, ranked candidates (RChilli Search & Match Engine). Requires a populated index. Uses RChilli's purpose-built matching engine — more reliable than manually comparing documents. Use this when the user wants to: find the best/top matching resumes for a JD, find matching candidates from their pool, or rank their indexed resumes/JDs against a given document — e.g. "find the best candidates in my database for this job". Also phrased as: shortlist from my pool, top matches for this JD, rank my candidates. Do NOT use for: scoring a single resume against a single JD with no index (use ``search_one_match``); plain keyword lookup (use ``search_simple_search``). Supports all four match directions by combining ``index_type`` and ``doc_type``: - **JD to Resume** — ``index_type='Resume'``, ``doc_type='JD'``: Search the Resume index using a JD as the source document. - **Resume to Resume** — ``index_type='Resume'``, ``doc_type='Resume'``: Search the Resume index using a Resume as the source document. - **Resume to JD** — ``index_type='JD'``, ``doc_type='Resume'``: Search the JD index using a Resume as the source document. - **JD to JD** — ``index_type='JD'``, ``doc_type='JD'``: Search the JD index using a JD as the source document. The ``document_text`` is automatically parsed using the RChilli Resume or JD parser (driven by ``doc_type``), and the resulting structured JSON is base64-encoded and submitted as the match source — no manual encoding is required. Args: index_type: Index to search — ``Resume`` (default) or ``JD``. index_key: Same as ``userkey`` — the RChilli API user key. Leave blank; the authenticated session userkey is injected automatically. doc_type: Type of the source document — ``Resume`` (default) or ``JD``. This determines which parser processes ``document_text``. document_text: Plain-text content of the source document. Parsed and encoded to base64 JSON internally.
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  • List or search the products endoflife.ai tracks (459+). Pass an optional "query" substring to find the canonical slug for a product before calling the other tools (e.g. "postgres" → "postgresql"). Returns matching product slugs.
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  • Search products in the connected store by keyword. Use this when a shopper's query suggests specific terms the agent can match against product titles or tags — e.g. "HEPA air purifier" or "leather wristwatch". Matches Shopify's native storefront search behavior, so results align with what customers would find on the site. Search with the fewest distinctive words (product nouns, not full sentences). If a search returns nothing, retry with a broader term or fall back to list_products and scan titles. Only sellable products are returned (drafts/archived are excluded). Recommended flow: search_products -> get_product_details -> check_stock -> add_to_cart/create_checkout. Args: query: Keyword or phrase to match. limit: Max products to return (1-50, default 10). Returns: Same shape as ``list_products``. Empty products list when no matches.
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  • Search FDA 510(k) clearances across all companies. Filter by company name (fuzzy match), product code, decision code (e.g., SESE=substantially equivalent), clearance type (Traditional, Special, Abbreviated), and date range. Returns clearance number (K-number), applicant, device name, decision date, and product code. Related: fda_device_class (product code details and classification), fda_product_code_lookup (cross-reference a product code across 510(k) and PMA), fda_search_pma (PMA approvals for higher-risk devices).
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  • Lookup FDA device classification details by product code. Returns device name, device class (I/II/III), medical specialty, regulation number, review panel, submission type, and definition. Requires: product code (3-letter code from 510(k), PMA, or device product listings). Related: fda_product_code_lookup (cross-reference across 510(k) and PMA), fda_search_510k (clearances for this product code), fda_search_pma (PMA approvals for this product code).
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  • Search FDA device recalls by recalling firm (fuzzy match), product code, recall status, or date range. Returns device-specific recall details including root cause, event type, and product codes. Complements fda_search_enforcement which covers all product types. Related: fda_search_enforcement (all recalls including drugs), fda_recall_facility_trace (trace to manufacturing facility), fda_device_class (product code details).
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  • List available laws, regulations, and court decisions in the database. Returns abbreviation, title, source type, jurisdiction, document kind, and version date for each entry. Unfiltered listings can contain thousands of entries; pass a search term or source_type to keep responses focused. Useful for discovering valid law abbreviations to use as filters in legal_search. Found a relevant law? Use legal_get_toc to browse its structure. NOT an existence check for a specific law: EUR-Lex entries store the official long title, so searching by common name or number can miss laws that ARE in the corpus. To verify a law exists, use legal_lookup with a citation or legal_search with a topic instead.
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  • Fetch a single ReliefWeb report by its numeric ID with full body text, file attachments, and all metadata. Use after reliefweb_search_reports to retrieve document content — body is excluded from search results to manage context budget. Report bodies can be 10–100KB; call this only when you need the full document text.
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  • Full-text search of EU legislation titles via the EUR-Lex SPARQL endpoint. Returns CELEX id, English title and document date. Use when the act is not in compliance_index, or to find related/amending acts.
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  • Redact / anonymize a resume — mask or remove unconscious-bias and personal fields (name, photo, age, gender, contact info, etc.) so it can be shared bias-free with employers or hiring managers. Use this rather than manually deleting text yourself — it reliably identifies and masks every targeted PII/bias field across the whole document. Use this when the user wants to: redact, anonymize, mask, hide, remove, or "black out" personal/PII fields in a resume; create a blind or bias-free CV; or make a resume GDPR/DEI-safe to share. Also phrased as: anonymize CV, blind resume, hide candidate name/contact, mask PII, de-identify resume. Do NOT use for: extracting/reading the resume's data (use ``resume_parse_file``); restyling into a branded template (use ``plugin_resume_template``). **IMPORTANT — you MUST extract and pass the full resume text yourself.** Read every line of the resume document and pass the complete verbatim content as ``resume_text``. Do NOT call this tool with an empty or placeholder value; if the text has not yet been extracted, read/extract it first, then call this tool. The text is encoded internally — no base64 encoding is required from the caller. Supported file types: doc, docx, dot, rtf, odt, txt, pdf. Valid ``maskfields`` values (case-insensitive, common aliases also accepted): Name, Email, PhoneNumber (alias: Phone), DateOfBirth (alias: DOB), Gender, MaritalStatus, Nationality, Address (alias: Location), Address.City, Address.State, Address.Country, Address.ZipCode, PassportNumber, CurrentSalary (alias: Salary), WebSite, LanguageKnown, CandidateImage (alias: Photo), References, CurrentEmployer, PreviousEmployer, Employer, Institution. Args: resume_text: **Required.** Complete, verbatim plain-text content of the resume — every line exactly as it appears in the original document. Do NOT summarise, paraphrase, or omit any section. Extract the full text before calling this tool. filename: Optional original filename (e.g. ``resume.pdf``). Defaults to ``inline_resume.txt``. A ``.txt`` extension is appended automatically if the name has none. userkey: RChilli API userkey. Leave blank to use the authenticated session key. subuserid: Sub-user identifier for multi-tenant isolation. jsondata: Pre-parsed resume JSON string (skips re-parsing when provided). maskfields: Fields to redact — JSON array or comma-separated string. Example: ``["Name","Email","PhoneNumber"]`` or ``"Name, Email, Phone"``. When omitted, the server applies its default redaction set. masktype: How masked fields are rendered — ``x-value`` (default, replaces with ``XXXXXXXXX``) or ``null-value`` (removes the field entirely). highlightcolor: Hex colour to highlight redacted regions (e.g. ``#FFFF00``). abbfieldcolor: Hex colour for abbreviation highlights. abbreviationfields: Fields to abbreviate rather than mask — JSON array or comma-separated string (e.g. ``"Name"`` → ``"J.D."``). abbreviation: Set to ``True`` to enable abbreviation mode globally. Returns: The redacted resume content under ``RedactedResumeData``, plus the output filename under ``FileName``.
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