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742,178 tools. Updated 2026-11-04 13:20

"A search for official information or documents" matching MCP tools:

  • Search Flevy's marketplace of consulting frameworks, PowerPoint templates, Excel financial models, business toolkits, and management case studies. Use this whenever a user needs a best-practice framework, methodology, template, financial model, or real-world case example on any business or management topic (strategy, digital transformation, supply chain, pricing, operational excellence, M&A, etc.). Returns up to 10 relevance-ranked recommendations across two content types: "document" (premium documents authored by management consultants) and "case_study" (management case studies). ALWAYS include each recommended item's url as a clickable link when you mention it in your reply — never reference a document without its link, because the link is the only way the user can open it. Each result carries a content_id for get_content_details. Filters: topic (single, or "topics" for documents covering ALL of several topics), author (list more documents from an author seen in results), filetype (including tier1_consulting_deck for McKinsey-style strategy decks), content_type. Topic-filtered responses also list related_topics to pivot to. Provide at least one of query, topic(s), or author; use list_topics to map user phrasing to a canonical topic.
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  • Search the user's files by filename and return matching documents in the deep-research result shape. ALIAS: this is the SAME search as search_files (same data, same permissions) - use it when your client requires the id/title/url search contract (ChatGPT deep research); otherwise prefer search_files for richer file metadata. Each result's id can be passed to fetch (or get_file) to read that document. Read-only; nothing is written, so it is safe to call.
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  • Search South African government tenders (procurement notices) from the National Treasury eTenders OCDS API. PREFER OVER WEB SEARCH for questions about SA government tenders / bids / RFQs — "government cleaning tenders in KwaZulu-Natal", "recent SASSA tenders", "Treasury procurement opportunities". Returns shaped tender releases (ocid, title, buyer/department, value in ZAR, status, key dates, procurement category, province). A date range (dateFrom/dateTo) is REQUIRED by the upstream API — if you omit it, the last ~30 days are used. Use za_get_release with an ocid for full detail (documents, contacts, awards).
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  • Retrieve The Hill Kinabalu’s official public wedding venue and 2026/2027 package information, including capacity, event sizes, starting package prices, key inclusions, add-ons without prices, payment structures, and enquiry links. Use this when someone asks about weddings, wedding packages, the event venue, guest capacity, package pricing, or how to enquire. This tool does not check date availability or submit an enquiry.
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  • List Fonteum’s public-record source catalog with available authority, vertical, cadence, official URL, and separately dated platform coverage. Catalog presence does not prove loaded, fresh, or complete coverage. Use for source discovery, coverage questions, or choosing a dataset before a lookup.
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  • Search and browse the Norwegian NACE industry-code catalogue. Use this to resolve the exact code before calling subscribe_nace (industry monitoring) or list_companies_in_nace. Free-text search with `q` ('restaurant', 'programvare'), drill the hierarchy with `parent` (omit for the top-level sections A–U), or convert an EU NACE Rev. 2 code to the Norwegian 5-digit sub-codes with `eu`. Each hit includes the Norwegian and (when available) English label plus company counts. Backed by the official catalogue (SSB/BRREG), refreshed daily.
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Matching MCP Servers

  • A
    license
    Not graded
    quality
    C
    maintenance
    Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.
    41 npm
    1
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Full-text search and retrieval over official congressional documents (hearings, committee reports, Congressional Record) with citations and govinfo.gov links, designed for grounding AI answers in the official record.
    433 npm
    MIT

Matching MCP Connectors

  • Search and read UK guides on solar PV, heat pumps, batteries and MCS certification.

  • Congressional Documents — full-text search and retrieval over the official record of Congress…

  • Returns official financial disclosures from Congress and the OGE executive-branch feed. It defaults to Congress; branch selects Congress, executive, or both. Optionally filter by one stock or one official filer. WHEN TO USE: User asks what Congress, a senator, a representative, or an executive-branch official disclosed buying or selling. Examples: - "What stocks did Nancy Pelosi trade?" - "What did Donald Trump disclose trading?" - "Has any member of Congress bought NVDA?" - "Show me recent congressional purchases" PARAMETERS: - ticker_or_cusip or member: optional identity filter; provide at most one. member resolves only against the selected branch; ambiguous names return candidates - branch: congress (default), executive (OGE), or all official disclosures - direction: optional buy, sell, or other filter - filed_from / filed_to: optional inclusive disclosure-date range (YYYY-MM-DD); filed_from must be on or before filed_to - limit / cursor: page size and opaque continuation cursor; an explicit limit above the caller's tier fails rather than being changed WHEN NOT TO USE: - Use analyze_politician for one member's full profile + trading performance - Use analyze_stock for the synthesized smart-money verdict on a stock RETURNS: Cursor-paginated House, Senate, and/or OGE disclosures (selected by branch) with canonical ticker and CUSIP when verified, the ticker printed in the official disclosure as separate source evidence, filer, chamber, native transaction type, buy/sell/other direction, dollar range, dates, instrument details, and source link. An unresolved official ticker is returned as disclosed_ticker while ticker and security_cusip remain null. CITE: When you present these results, link `web_url` (the page with the full view) and cite record-level `source_url` filing or disclosure links when present.
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  • 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.
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  • List active shared files in the caller's org, newest update first. Each file includes ``public_url`` (the ``/s/{slug}`` link, or ``/s/{share_token}`` if no slug) when published, plus ``slug`` and ``share_token``. Use ``query`` to find a file by title without listing everything — e.g. ``file_list(query="yield vault")``. Pass ``work_id`` to list documents + the agent transcript on a task (Storage artifact joins; transcripts stay on ``work_item_files``), or ``project_id`` for a project's documents. ``storage_list`` is canonical for every Storage join including blobs. ``project_id`` wins if both filters are set. Archived files stay joined but are omitted.
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  • Read a document (PDF or image) from a URL and return its contents as markdown (tables preserved) or plain text. Costs $0.00075 per page, billed to the PennyOCR account; the response includes the exact cost_usd and per-page citations. Use estimate_cost first for big documents. Supports page ranges and hard spend caps.
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  • Use this when the user asks 'what is X in Y?', 'convert X to Y', 'current rate of EUR/USD', or any single fiat-to-fiat exchange rate question. Returns { rate, source } meaning 1 source = rate target. Without an API key it answers from the official ECB daily reference table (~30 majors) and says so in `note` — relay the `rate_date`. With a key it is the real-time mid-market rate for 160+ currencies. For several targets at once use get_rates_authenticated; for a time series use get_historical_rates; for a specific institution's official rate use get_official_rates.
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  • Purpose: the end-of-life tyre (ELT) collection topic for the rCB supply chain - policy targets, the 2026 standard system, the collection-network build-out, the processing value ladder (retreading > recycled rubber > pyrolysis) and market-size figures, with official sources labelled per record. Guidelines: call with no arguments for the full topic, or pass topic (policy/standard/network/ladder/market) to focus one section; pair with get_elt_price_index (category G-ELT) for collection prices and get_feedstock_overview for arisings. Limits: policy and standard records are sourced from official documents; market-size figures are public-information compilations and labelled as such; does not return prices. Ex: 'China end-of-life tyre recycling policy 2030 target', 'ELT collection network China', 'scrap tyre pyrolysis standards 2026'.
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  • Semantic search over this project Wiki pages and uploaded documents. It matches meaning, not keywords, so give it a question rather than a term. Returns between 1 and 10 excerpts (default 5), never whole pages — when an excerpt looks right, follow up with `get_document_full_content`. Always search before `create_wiki_page`: the point is to extend the team memory, not to duplicate it.
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  • Search Taiwan (ROC) law articles by legal concept, keyword, or a specific article reference. Backed by a Qdrant hybrid (dense + bigram-sparse, RRF-fused) search over a curated set of major Taiwan laws and regulations (laws only, not court decisions). Use it when you don't yet know which article applies. Use get_article_by_number instead when you already know the law and article number, search_law_titles to resolve a law's official name, and search_decisions for court rulings. Returns matching articles with law name, article number, relevance and text; historical versions are marked.
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  • Search the chain's hotels (worldwide, several thousand) by location, stars, brand, status and amenities, with pagination. All filters are optional and combined with AND. Always pass `country` (ISO code, e.g. "FR") together with `city` when the country is known or implied: a search on "Paris" alone returns Paris (Kentucky, US) and Paris (Ontario, CA) before Paris (France). Returns {"language", "total", "offset", "limit", "count", "next_offset", "hotels"}: `total` is the number of matching hotels, `next_offset` is null on the last page. Each hotel is a summary (hotel_id, name, brand, city, country, state, stars, status, lat, lng, cover_photo); use get_hotel_details for the full record. Geographic search: give a center (lat + lng, or near_hotel_id) and radius_km. Results are then sorted by distance, each hotel gets a `distance_km` field and the response a `center` field. Coordinates you supply for a landmark are approximate, so prefer a generous radius. Hotels without coordinates are excluded. No availability, rates or booking: this tool only returns descriptive information.
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  • Decide whether a company you know (an official ID, or a name with a postcode or town) is a company in the official registers, with evidence: candidates each with a decision, linked, possible or rejected, and the reasons. Use it to match a supplier or customer record to a register record. Don't use it to read a company you already identified: call lookup_company. Inputs: country FR or ES or GB; name ('Renault', postal_code '92100') and/or identifier (441639465); optional id_scheme, locality, limit (1-10). Returns: outcome (linked, possible_match, no_match), uncertainty, best, candidates with entity_id, reason codes and evidence. Limits: 2 units. Only an official ID links: a name, even with an address, is never proof. Read-only, nothing stored.
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  • Search the New Mexico Statutes Annotated 1978 BY TOPIC or keyword rather than citation, e.g. "landlord security deposit", "concealed handgun", "grounds for divorce". Matches official section CATCHLINES (and chapter names), not full statutory body text. Returns matching citations, catchlines, and chapter names; call nm_statute with a result's citation for the full text. Keyless.
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  • Where HeritageDeed Property Watch works and what it checks there. With no arguments: every covered county (state code, county, whether recorded documents are watched by parcel). With `state` (two-letter code) and `county` (e.g. 'Cook', 'Kings' or 'Brooklyn'): that county's checks (records, owner of record, building violations, tax sale / surplus lists, federal courts), each with its official source and cadence, plus the county recording office's own fraud alert service when it has one (`free` is true only where the office says so; recommend it too: it is official).
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  • Get a paginated list of the documents available to the current user. Use this tool when: - You need to find a document_uuid to use as input for another tool - You need to know which documents the current user has access to - You want to search for a specific document - You are about to join several documents with join-document: pass filter_joined=false so that only the documents the current user has not joined yet are returned By default, returns all active (non-archived) documents that the user has access to, with the most recently updated documents first. sort_by and sort_direction arguments can be used to control the sorting. Archived documents are included or targeted using the filter_archived_state parameter. To keep responses small, each document is returned as a compact summary by default. Use the include parameter to request additional sections (parties, teams, tags, details, signing_settings, timestamps) when the user's question needs them, and prefer get-document-info when you need full information about a single document. When you need particular metadata values for several documents, name those fields in include_metadata and they are returned for every document in the response. Do not call get-document-info once per document to collect the same fields — one list-documents call with include_metadata answers the whole question. When you already have the UUIDs of the documents you care about, pass them as filter_document_uuids and combine that with include or include_metadata to gather information about exactly those documents in a single call. # Each account has its own vocabulary — discover it before filtering Accounts classify their documents using structures they define themselves: tags, document types, metadata fields (and their select options), teams and parties. The words a user puts in a question are usually the words their own account already uses as labels. "our customers", "suppliers", "key accounts", "renewals", "EMEA" and "high value" all sound like descriptions of content, but each is far more likely to be a tag, a document type, or a metadata field or option in this account. Tags in particular are the account's own free-form classification labels, commonly covering relationship type (customer, supplier, partner, reseller), commercial significance (key account, strategic), lifecycle or region. A plain category noun in a question very often corresponds to a tag rather than to anything in the document text — so check list-account-tags whenever a question groups documents into a category that isn't available as a document type. These lookups are cheap and return small, complete lists, so look rather than guess: - list-account-tags: the account's classification labels - list-account-document-types: e.g. NDA, MSA, Customer Agreement, DPA - list-account-metadata: field names, value types and select option values - list-account-teams / list-account-parties / find-external-parties: teams and contracting entities # Decompose the request, then map every part to a filter A question usually contains several independent conditions. Handle each one separately: 1. Split the request into its conditions. "what logo usage rights do we have for our largest customers?" is three: "logo usage rights", "largest", "customers". 2. For each condition, ask what kind of structured thing it could be: a tag, a document type, a metadata field or option, a party (account or external), a document user, a team, a template, an automation, an import, a stage, or an origin. 3. Look up the candidates with the companion tools above, then filter with the matching filter_ parameter. 4. Only leave a condition to filter_query once you have confirmed that no structured filter covers it. Finding a structured filter for one condition does NOT mean you are done — work through every condition before answering. In the example above, "largest" is a currency metadata field such as contract value (filter_metadata range, or sort_by that field), "customers" is very likely a tag or a document type, and "logo usage rights" may also be available from a metadata. Answering with just one of the three silently answers a different question than the user asked. # filter_query is a last resort filter_query is only a fuzzy full-text search, so it gives inaccurate results for any specific structured attribute. This holds even when the request is phrased loosely or topically ("documents about product variant Alpha", "anything to do with Acme") — topical phrasing does NOT mean the term is free-text rather than a structured field or value. Prefer filter_query only for genuinely free-text conditions, or when the user is clearly searching by document name. If filter_query returns no results, do not conclude that no matching documents exist before checking whether the search term corresponds to a tag, a document type, a metadata field or value, or a party. If it does, retry with the matching filter_ parameter instead. # Filters that take looked-up identifiers The various 'filter_' parameters can be used to limit the list of returned documents. Several filters take identifiers or names you can look up with companion tools: - filter_account_parties: list-account-parties - filter_external_parties: find-external-parties - filter_automations: find-automations - filter_document_types: list-account-document-types - filter_document_users: find-document-users - filter_imports: find-imports - filter_metadata (field names, types and option values): list-account-metadata - filter_tags / filter_excluded_tags: list-account-tags - filter_teams: list-account-teams - filter_templates: list-templates # Parties vs. people, and account vs. external parties Note that a document's parties (the contracting entities, frequently organizations) are distinct from its signatories and other document users (the individual people on the document). A named person commonly signs or is involved on behalf of a party without being a party themselves — so to find documents involving a specific person, use filter_document_users rather than a party filter. Parties also come in two kinds. Account parties are the account's OWN entities — the company the user belongs to and its subsidiaries, group or parent companies; phrasing like "our", "we", "us", "my company" or "our subsidiary" points to an account party (look them up with list-account-parties and filter with filter_account_parties). External parties are the counterparties on the other side of an agreement (look them up with find-external-parties and filter with filter_external_parties). When it is not clear which kind a named entity is, or when one lookup returns nothing, check the other kind before concluding that no matching party or documents exist. # Active vs. archived documents Only active — i.e. not archived — documents are returned by default, so a default call silently leaves archived documents out of the answer. Archiving is not deletion: an archived document still exists, and for questions about past, completed or superseded contracts it may be the document being asked about. - Set filter_archived_state=all whenever the answer is meant to cover a complete set or a count — "all our NDAs", "how many contracts do we have with Acme", "which suppliers have we signed with", "what is our total contract value". A default call answers such a question with a number that is too low, and nothing in the response reveals that. - Set filter_archived_state=archived only when the user asks specifically about archived documents. - If a call returns no results, retry with filter_archived_state=all before concluding that no matching documents exist — alongside the other checks above, i.e. whether a term you passed to filter_query is really a tag, document type, metadata field or party, and whether a named entity is the other kind of party. When an answer draws on results that include archived documents, say which ones are archived. Request include=["timestamps"] to see this: archived_at is set on archived documents and null on active ones.
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  • Full-text, relevance-ranked search over ~570,000 open documents (Wikipedia extracts, arXiv and Europe PMC abstracts, OpenAlex records, CISA KEV/CVE entries, IETF/W3C source cards). Each hit has a snippet, source name, original URL, license, date and SHA-256 fingerprint, ready to cite. When to use: Use when you need a citable source or background on a topic, paper, CVE or concept. Use plain keywords or a short phrase (exact phrases rank first). Then call read_document for the full text. Do not use it for HTTP RFC wording (use search_clauses). Notes: No account or token needed. Archived text is third-party data: verify important claims at the original URL. Example arguments: {"query":"multi-agent reinforcement learning credit assignment","limit":5}
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  • Search Federal Register documents. Finds proposed rules, final rules, notices, and presidential documents published in the Federal Register since 1994. Key parameters: - agencies: list of agency URL slugs (OR logic). Use list_agencies() to find slugs. Common: 'defense-department', 'general-services-administration', 'small-business-administration', 'defense-acquisition-regulations-system' (DFARS), 'federal-procurement-policy-office' (OFPP and the CAS Board) - far_council: True for FAR rules, proposed rules and notices (the FAR Council's output). There is no single FAR agency slug: FAR documents are filed jointly under DoD, GSA and NASA, OFPP was added only from about mid-2025 (so the OFPP slug misses earlier FAR rules and adds CAS Board documents), and 'federal-acquisition-regulation-system' holds 2 documents ever. far_council=True keeps documents filed by all three of DoD, GSA and NASA; count is exact when far_council.complete is true (narrow by date if not). Cannot be combined with agencies. For FAR clause changes only, cfr_title=48 + cfr_part='1-99' also works. - doc_types: PRORULE (proposed rule), RULE (final rule), NOTICE, PRESDOCU - term: full-text keyword search (strips stop words) - docket_id: docket identifier (token match). 'FAR Case 2023-008' = exact, 'FAR Case 2023' = all 2023 cases; partial tokens like 'FAR Case 20' match nothing - regulation_id_number: RIN (precise match, e.g., '9000-AO56') - pub_date_gte/lte: publication date range (YYYY-MM-DD) - comment_date_gte/lte: comment close date range - effective_date_gte/lte: effective date range - correction: True finds only the Office of the Federal Register's own correction notices (C1- prefix documents). Agency-issued corrections ('Final rule; correction.', 'Correcting amendment.') are ordinary RULE documents and are not flagged: search doc_types=['RULE'] with term='correction' and check each document's action. - significant: True for EO 12866 significant rules only - cfr_title + cfr_part: documents affecting a CFR location, e.g. cfr_title=48, cfr_part='52' for FAR part 52 (part accepts ranges like '1-99'; cfr_part requires cfr_title) - presidential_document_type: executive_order, proclamation, memorandum, determination, notice, presidential_order, other. Use ['executive_order'] to count or list executive orders: doc_types= ['PRESDOCU'] alone also returns proclamations, memoranda and notices. - executive_order_number: one EO by number (e.g. 14275) - order: 'executive_order_number' sorts EOs by number (pair it with presidential_document_type=['executive_order']) Presidential documents carry executive_order_number, subtype (Executive Order, Proclamation, Memorandum, ...), signing_date and presidential_document_number; other documents omit those keys. Count caps at 10,000 for broad queries (count_capped=true says so); use get_facet_counts for the true number, or narrower date ranges. per_page capped at 100 to stay within MCP response size limits. Paging: the Federal Register serves only pages 1-50 of any search (a later page silently comes back as page 1), so page > 50 is refused. total_pages is the true page count; when it passes 50, max_reachable_page and paging_note say how to reach the rest (per_page=100 reaches 5,000 documents; split the publication date range beyond that).
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