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762,023 tools. Updated 2026-11-10 02:28

"A search for the string pHqghUme" matching MCP tools:

  • 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.
    ConnectorNo auth
  • Search JobYap job postings by natural-language query. Matches job titles, falling back to significant keywords when the full phrase finds little. Returns result ids, titles and citable URLs for use with fetch. For structured filtering (location, company, remote, freshness) prefer search_jobs.
    ConnectorNo auth
  • Semantic search over guthmann.estate — market insights, reports, neighborhood portraits, listing exposés, project pages and the company's own pages. Hybrid retrieval (vector + keyword, no reranking); one result per page with title, description, image, best-matching snippet and score. Use it for questions that need prose (analysis, context, advice); use the data tools for exact numbers and `listings` for what is currently for sale — the search index follows the website with up to six hours of delay. Parameters: - q: natural-language query, in the language of the pages you want (min 2 characters) - locale: "de" | "en" — language of the indexed pages (default: en) - section: comma-separated filter — "listings" (exposés), "projects" (new-build projects), "market-intelligence" (insights, reports, portraits), "pages" (company, services, guides); omit for all - limit: 1-20 pages (default: 10) Key response fields: - url, title, description, image, section, language - snippet (best-matching text passage), score (0-1)
    ConnectorNo auth
  • Compatibility tool: OpenAI connectors require a tool with this exact name and one string argument. Searches conferences by free text — a city, a topic, a company or a conference name — and returns at most 10 results as id, title and url only. If you can pass separate arguments, use search_conferences instead: city, country, topic and dates, up to 100 rows, with the detail this one leaves out. Pass an id to `fetch`.
    ConnectorOAuth
  • Display up to ten selected podcasts as cards from earlier Listen Notes results. First use a search or lookup tool, then pass each returned id with that result's result_info.presentation_ref as result_ref. Copy this opaque, case-sensitive string exactly and reuse the identical value for all items from the same result. On an invalid-reference error, retry only the card call once with the exact original reference, without another search. Use only the requested, relevant items. No additional Podcast API request. If a reference is missing or expired, present the existing Listen Notes links instead; do not refetch solely to draw cards. Cards include available website, RSS, Apple Podcasts and email links.
    ConnectorOAuth
  • Use this when you need the exact SHA-1, SHA-256, and/or SHA-512 hex digest of a UTF-8 string — never recall or guess a hash, since digests cannot be produced from memory. Deterministic: same input, same output. Pass `algorithm` for a single digest or `algorithms` for a subset; the default computes all three. The empty string is valid, and `byteLength` reports the UTF-8 encoded byte length of the input. Example: text "hello" with algorithm SHA-256 -> byteLength 5, hashes["SHA-256"] = "2cf24dba5fb0a30e26e83b2ac5b9e29e1b161e5c1fa7425e73043362938b9824".
    ConnectorNo auth

Matching MCP Servers

  • A
    license
    Not graded
    quality
    C
    maintenance
    面向 Codex、WorkBuddy 等 AI 工具的知你AI助手合并版 Skills,涵盖当前会话分诊、客户查询与画像、历史会话检索、客户分群和 API Key 用量查询,并连接个微、企微、视频号、微信小程序、公众号、服务号、微信客服、微信小店、抖音号、小红书、微博、网站及H5客服等渠道。
    MIT No Attribution
  • A
    license
    Not graded
    quality
    A
    maintenance
    . A good description should be concise and describe what the server enables users to do, e.g. * Enables to interact with WordPress sites...' Then a huge block? Actually the user message includes the README content inside tags, then after the readme, there is a large block of text starting with '{
    7,061 npm
    MIT

Matching MCP Connectors

  • Search the TCLP knowledge graph using fusion search (semantic + BM25). Args: query: Free-text search query (max 1000 characters). node_type: Content scope — "tclp" (clauses, glossary terms, guides) or "all". Laws, regulations, standards and frameworks are not searchable here: use `find_legal_resources`. content_type: Return only one content type: "clause", "glossary_term" or "guide". Omit to search every type. limit: Maximum number of results to return (1–50). rerank: Whether to apply RRF reranking when combining graph and text results. include_full_text: Include each hit's full body text (Markdown). Off by default — bodies are large; request only when you need the content, and prefer a small `limit` when you do. Returns: JSON with "meta" (totals, timing) and "results" (ranked hits with title, url, content_type, scores, summary, optionally relationships_text, related and full_text). `summary` is short plain text: the clause summary, the first paragraph of a glossary definition, or a guide's excerpt. It is null when the item has none. `child_name` is a clause's child name (e.g. "Odhran's Clause"), null for other content and for a clause that has none; text search also matches it. Each hit's "references" lists the instruments it cites: pass a reference's `work_id` to `get_legal_resource` for details. A reference's `edge` (governs, references, describes) says how the content relates to the instrument; it is not a statement of the instrument's legal effect. An empty list means the hit cites no instruments. null with "lrsf" in meta.degraded means references could not be loaded: do not conclude that the hit cites no instruments.
    ConnectorNo auth
  • Search the TCLP knowledge graph using fusion search (semantic + BM25). Args: query: Free-text search query (max 1000 characters). node_type: Content scope — "tclp" (clauses, glossary terms, guides) or "all". Laws, regulations, standards and frameworks are not searchable here: use `find_legal_resources`. content_type: Return only one content type: "clause", "glossary_term" or "guide". Omit to search every type. limit: Maximum number of results to return (1–50). rerank: Whether to apply RRF reranking when combining graph and text results. include_full_text: Include each hit's full body text (Markdown). Off by default — bodies are large; request only when you need the content, and prefer a small `limit` when you do. Returns: JSON with "meta" (totals, timing) and "results" (ranked hits with title, url, content_type, scores, summary, optionally relationships_text, related and full_text). `summary` is short plain text: the clause summary, the first paragraph of a glossary definition, or a guide's excerpt. It is null when the item has none. `child_name` is a clause's child name (e.g. "Odhran's Clause"), null for other content and for a clause that has none; text search also matches it. Each hit's "references" lists the instruments it cites: pass a reference's `work_id` to `get_legal_resource` for details. A reference's `edge` (governs, references, describes) says how the content relates to the instrument; it is not a statement of the instrument's legal effect. An empty list means the hit cites no instruments. null with "lrsf" in meta.degraded means references could not be loaded: do not conclude that the hit cites no instruments.
    ConnectorNo auth
  • Full-text search across all SEC EDGAR filings since 2001 for a keyword or phrase. Wraps EDGAR's own full-text search index, so it covers every filer and form type, not just a single company. Useful for finding who is disclosing a particular risk, technology, litigation, or event across the entire market. When to use: cross-company research ("who is disclosing AI-related risk factors"), finding filings that mention a specific term, litigation or regulatory tracking. When NOT to use: you already know the company (use edgar_filings_feed, which is company-scoped and cheaper), or you need results from before 2001 (EDGAR full-text search does not cover that far back). Args: - query (string, required): search text. Wrap an exact phrase in double quotes, e.g. "\"material weakness\"". - forms (string[], optional): restrict to form types, e.g. ["10-K"]. - dateFrom (string, optional): ISO start date (YYYY-MM-DD). - dateTo (string, optional): ISO end date (YYYY-MM-DD). - limit (integer, optional, default 10): maximum hits to return (1-50). Returns structuredContent: { "query": "material weakness", "totalMatches": 10000, "totalIsApproximate": true, "count": 2, "hits": [ { "id": "0001193125-26-123456:doc.htm", "entity": "Example Corp.", "form": "10-K", "filedAt": "2026-03-01", "cik": "0000320193" } ], "source": "https://www.sec.gov/edgar" } "totalMatches" is a lower bound and "totalIsApproximate" is true once EDGAR's own count exceeds its display cap (10,000) — narrow with forms/dateFrom/dateTo for a precise count.
    ConnectorNo auth
  • Embed a text string into a 768-dim Gemini Flash vector. Use for HyDE-style retrieval: (1) write a hypothetical short paper that would perfectly answer the user's query, (2) embed it with task_type='RETRIEVAL_DOCUMENT' (default — matches the corpus embedding side), (3) pass the resulting embedding back through search-style tools to find real papers nearest to the hypothetical. task_type='RETRIEVAL_QUERY' matches the query side and is useful for direct user-query embedding without HyDE. Pro-only — requires an SF_API_KEY on a Pro account; anonymous and free callers get a 403 pro_required. Cost: ~$0.0001/call; rate-limited at 30/minute per API key.
    ConnectorNo auth
  • Start generating hero image variants for an idea's ad. Runs in the background. Args: - ideaId (string) - prompt (string, optional): defaults to the idea's saved image prompt Returns: { job: { id, status, prompt, variantCount, results }, note }. Poll idealaunch_get_image_job until status is 'succeeded', then choose one with idealaunch_apply_hero_image. Consumes one of the idea's AI generation turns. Costs no Ad Run credit.
    ConnectorOAuth
  • Full-text search inside JournalEntry compendium packs — page NAMES and page CONTENT. The tool for rules/lore text ("what does grappled say?" → query "grappled", pageTypes ["rule"]; class write-ups, spell lists): compendium-search sees only document names. Requires bridge module 8.11.0+. Each match carries the PAGE uuid — pass it to uuid-resolve for the full text. matchedIn tells what matched: name matches win (content not scanned, snippet null); content matches carry a ~200-char snippet. Query is a case-insensitive substring; packs are scanned in order until limit, results unsorted.
    ConnectorAPI key
  • Sign-in required: call connect(email) and connect_verify first (free, one email) unless this connection is already signed in. Search held regulation text. Returns pinpoints and excerpts, not summaries. Requires regulation id (e.g. eu-ai-act) and query string. limit, detail (compact|full) and max_chars bound the response. Then read_unit on the best pinpoints; verify_citation if checking someone else's cite.
    ConnectorNo auth
  • Search this Cubite site's courses by keyword and get each match's public page URL, for linking to or citing it. This is the search half of the search/fetch pair that ChatGPT connectors and deep research require. The whole query is matched as one case-insensitive phrase, so use one or two distinctive words. Courses match on name or description and are listed in name order; a course without a URL slug has no public page and is never returned, while courses hidden from the catalog are. Returns up to 10 results as {id, title, url}; pass a result's id to `fetch` for its citable text. It is not an inventory: to list, count or manage courses use course_list, which has no keyword filter but returns every course, with or without a slug, with its id, settings and enrollment count.
    ConnectorAPI key
  • List a company's bank statement transactions, newest first, paged, with totalCount. Each has acDocumentId, date, amount, currency, movement, bank account, title, description and status (documentRequired while it needs a document or coding). Pass acDocumentId as transactionId to get-transaction-conversation, add-transaction-comment or list-transaction-cashcoding-recommendations. It has no text search; dateFrom and dateTo are inclusive. For ledger entries in every account, use search-accounting-transactions.
    ConnectorOAuth
  • Turn a fuzzy or partial name into real, ranked candidate package names, using the registry's own live search index — not a guess at what the package is probably called. For npm this queries registry.npmjs.org's actual search API (the same one npmjs.com uses). For Cargo this queries crates.io's real search endpoint. For PyPI: there is currently no official PyPI search API (XML-RPC search was permanently disabled in 2022 and never replaced) — calling this with ecosystem 'pypi' returns an explicit message saying so rather than a fabricated or scraped result, along with a suggestion to use the exact package name with docs_get_package_info instead. Args: - ecosystem ('npm' | 'pypi' | 'cargo') - query (string): the name or description to resolve, e.g. "react" or "async http client" - max_results (number, 1-10, default 5) Returns JSON with: candidates (array of {name, version, description, score, url}), source_url, fetched_at. Error Handling: - ecosystem 'pypi' always returns an explanatory message, not an error and not fabricated results - Returns "Error: ..." only for actual npm/crates.io request failures
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  • List workflows for the user's current team. Supports optional status filter and substring search. Input roles: - status: "active" | "inactive" | "archived". Omit to return all. - search: substring to match against workflow name. - page / per_page: pagination. Default page=1, per_page=20, max per_page=100. Usage patterns: - Before create_workflow: call list_workflows with `search:` to check for duplicate-name workflows. - When the user asks "what workflows do I have": call with no filters. - When the user asks "what's my automation doing?": filter by status="active" — but Active only means a workflow is allowed to run. Whether it runs on its own depends on its schedule (On or Paused), which the list does not show; call get_workflow and follow its `run_state` before saying any workflow is running. A workflow is Active/Inactive, a schedule is On/Paused — never mix the two. - Each item's `id` is a UUID string. Use it as `workflow_id` in get_workflow / update_workflow / run_workflow / get_workflow_runs. **Links:** present `link_url` to the user exactly as returned — copy it character for character. Never retype, shorten, or rebuild a link or the IDs inside it.
    ConnectorOAuth
  • Display up to ten selected episodes as cards from earlier Listen Notes results. First use a search or lookup tool, then pass each returned id with that result's result_info.presentation_ref as result_ref. Copy this opaque, case-sensitive string exactly and reuse the identical value for all items from the same result. On an invalid-reference error, retry only the card call once with the exact original reference, without another search. Use only the requested, relevant items. No additional Podcast API request. If a reference is missing or expired, present the existing Listen Notes links instead; do not refetch solely to draw cards. Cards include Listen Notes listening links and manual audio download links when available. Cards do not play audio inline or download media for the user.
    ConnectorOAuth
  • This is Anysearch's domain discovery tool. IMPORTANT: Step 1 of vertical search. REQUIRED before any search that uses a domain. Returns valid sub_domains and sub_domain_params for the specified domain(s). Call this when the query targets a specialized vertical or needs structured parameters: stock prices, financial data, academic papers, legal cases, medical/drug info, flight status, weather, exchange rates, geographic POIs, code repositories, or any domain where a structured identifier (ticker, DOI, CVE, IATA, coordinates) is involved. ## When to call — pick the domain(s) that match what the user is asking about: academic agriculture business code energy environment film finance gaming health ip legal resource security social_media travel ## Input — choose from the list above and pass via the domain or domains parameter: - domain: single domain string (use only when 100% certain the query is single-domain) - domains: batch query for up to 5 domains in one call (takes priority over domain) 🏆 ALWAYS prefer the `domains` (plural, array) parameter. Pass ALL potentially relevant domains at once — even for seemingly single-domain queries, consider related domains: - Query about "cryptocurrency regulations" → domains=["finance", "legal", "security"] - Query about "best gaming laptops" → domains=["gaming", "tech", "ecommerce"] - Query about "climate change impact on agriculture" → domains=["environment", "energy", "academic"] ## Returns Markdown table filtered to the specified domains: sub_domain | description | params ## CRITICAL: How to use results - sub_domain is the PRIMARY routing key — always pass it to search - params column shows available structured parameters — pass them via sub_domain_params in search, NEVER embed in query - If multiple sub_domains returned (especially from multiple domains), use batch_search — one query per sub_domain — instead of multiple sequential search calls - Params marked (required) in the output MUST be passed when using that sub_domain in search. If a required param is not applicable to your query, pass it as an empty string (key: "") — do not skip it.
    Connector
    Destructive
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  • Validates a French SIRET (Système d'Identification du Répertoire des Établissements) number using the official Luhn algorithm. SIRET is a 14-digit number — the first 9 digits are the SIREN (company identifier) and the last 5 digits identify the specific establishment. Returns { valid: boolean, siren: string, establishment: string, siret: string }. Use when processing French invoices (factures), validating supplier registrations, or any B2B transaction requiring a verified French business establishment identifier. Handles the La Poste special case automatically.
    ConnectorNo auth
  • Search the Melvea local honey directory by free-text query and return matching producers as a list of results (id, title, url). Designed for ChatGPT Deep Research and Company Knowledge. Use for any local-honey discovery query that names or implies a place; the tool parses place and varietal from the query. Returns an honest empty list when nothing matches — never fabricate. Pair with fetch to retrieve full producer detail.
    ConnectorNo auth