"A server with DEEP SEARCH functionality for flexible use" matching MCP tools:

• searchA

  UseMyContext.aiA

  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

• list_jurisdictionsA

  BizVerifyA

  Lists every registered jurisdiction with its code, active/inactive status, and supported capabilities — search, entity lookup, quick verification, and deep verification. Free and requires no authentication. Use it to confirm a state or country is supported and which verification tiers it offers before calling verify_business or search_entities.

  ConnectorNo auth

• check_connectionA

  FundingLandscapeA

  Verify MCP server connectivity. Returns success immediately with no database calls. Use this FIRST if experiencing tool errors - a successful response confirms the server is reachable. It does not confirm account, search, or paid-feature authentication, which can still return "Auth required" separately. Does not count toward your monthly searches.

  ConnectorNo auth

• x_searchA

  Veezee: LinkedIn people & company data for agentsA

  Search X by keywords. type picks the mode: recent (default) is the deep chronological sweep and keeps paginating as far as you follow the cursor; popular returns the highest-engagement tweets for the query; people finds accounts and returns a single page (no cursor). Advanced query operators pass through verbatim, e.g. "from:nasa", "min_faves:100", exact phrases in quotes -- there is no separate date parameter, so use since:/until: operators for time windows. Costs 6 credits per page; a cursor page is a NEW call priced the same way, so a deep sweep costs linearly in pages. Returns tweet summaries (text, author with follower count, views, likes, retweets, replies, created_at, url, id) with a cursor. Fetch one tweet's full detail with x_get_tweet and an account's timeline with x_get_tweets. For comment-level sentiment inside topic communities, reddit_search type=comments is usually the sharper instrument.

  ConnectorOAuth

• searchA

  AgileHeroA

  The product's global full-text search (OpenSearch): cards, epics, wiki pages and projects, matching titles, descriptions, comments, checklist items and attachment filenames, relevance-ranked with a recency boost. Use this to find anything by content ("the card where we discussed the migration"); use search_cards only for title-substring lookups inside one project. Each result carries a type, an action-ready uid (cards feed get_card/update_card, epics get_epic, wiki_pages show_wiki_page, projects the project_id parameters), a deep-link url, and <mark>-highlighted snippets showing why it matched. Optionally scope with project_id or assigned_to_me. Paginate with page/per_page; total_count is the full match count.

  ConnectorNo auth

• searchA

  SMI Aware AssistantA

  Open-ended discovery across SMI deep reports, research bundles, and exports when you do not already have a record id — finds candidates by subject name, url, or keyword and returns typed references to pass to fetch. If you already have a record id from the conversation rather than from a search result, call the specific tool instead: smi_get_deep_report or smi_get_export to read one record, smi_check_order_complete for order readiness, smi_list_deep_reports or smi_list_exports for filtered listings, smi_get_report_findings for findings within a report. Deep reports and research bundles are filtered server-side by subject first/last name, broadening to an unfiltered fetch ranked client-side (across id, name, url, summary) when the filtered fetch finds nothing; exports match on url.

  ConnectorOAuth

• fetchA

  Penfield MemoryA

  [ChatGPT Connector compat] Fetch memory by ID. Exists to satisfy ChatGPT Deep Research's required `search`/`fetch` tool contract. Native MCP clients should fetch via `recall` + memory_id, or use the API's GET /memories/{id} endpoint directly. Returns a single memory with citation support (id, title, url, text fields). Args: id: Memory UUID to fetch ctx: MCP context Returns: Dict with id, title, url, text, metadata fields

  ConnectorOAuth

• searchA

  Melvea Local Honey DiscoveryA

  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

• fetchA

  UseMyContext.aiA

  Fetch one document's full extracted text by id (a file id from search / search_files / list_files), in the deep-research result shape. ALIAS: this is the SAME read as get_file (same data, same permissions, same audit, same size guard - large files are truncated) - use it when your client requires the id/title/text/url fetch contract (ChatGPT deep research); otherwise prefer get_file, which also serves download links and inline images. Read-only; audited.

  ConnectorNo auth

• create_google_sitelink_extensionA

  Metadata MCP ConnectorA

  Add an extra clickable shortcut (sitelink) that appears beneath a Google Ads ad — helpful deep-links like "See Pricing", "Book a Demo", or "Contact Sales" with two short description lines. Sitelinks lift click-through rate by giving searchers alternate landing paths to the same advertiser. ALSO KNOWN AS: sitelink, site link, extra link, ad link, secondary link, deep link, additional link, jump link KEYWORDS: sitelink, site link, link, deep link, shortcut, google ads, extension, pricing link, demo link, contact link, landing page, CTR, click through WHEN TO USE: - "Add a sitelink to our Google Ads library" - "Create a 'See Pricing' / 'Book a Demo' / 'Contact Sales' link extension" - "Register a new sitelink for the homepage redesign" - "I need a shortcut under our search ads that points to the new pricing page" WHEN NOT TO USE: - Want a non-clickable selling-point snippet ("Free Shipping", "24/7 Support") → use create_google_callout_extension - Want a labeled list of offerings (e.g. "Brands: Nest, Nexus") → use create_google_structured_snippet_extension - Same sitelink for Microsoft Ads / Bing → use create_microsoft_sitelink_extension (library entries are per-channel) - Anything for Facebook / LinkedIn / Reddit — ad extensions are a search-channel-only concept INPUTS (all required): - url: destination the sitelink opens. - link_text: visible link text (1-25 chars). - description1: first description line under the link (1-35 chars). - description2: second description line (1-35 chars). EXAMPLE: create_google_sitelink_extension( url="https://example.com/pricing", link_text="See Pricing", description1="Plans for every team size", description2="Start free, upgrade anytime", ) Returns the persisted extension (id, externalId, type=SITELINK, channel=GOOGLE_ADS). A 400 usually means a character-limit was exceeded.

  ConnectorAPI key

• google_flights_round_tripA

  SearchapiA

  Search round-trip Google Flights with airline, time, price, and booking details. Required on every call, including token follow-ups: departure_id, arrival_id, outbound_date, return_date. Preserve all original search options, including travel_class, passenger counts, currency, and filters. **Workflow:** 1. Search for outbound flights. 2. Repeat the arguments with the chosen outbound flight's departure_token to retrieve return options. 3. Repeat the arguments, replacing departure_token with the chosen return flight's booking_token to retrieve booking details. One-way: google_flights_one_way. Flexible dates: google_flights_calendar_round_trip.

  ConnectorOAuth

• searchA

  SocialGPTA

  Search across your own connected-account content and return the best matches. Each result has an `id` (pass it to `fetch` for the full item), a `title`, a `url`, and a `text` snippet. This is the deep-research "search" entrypoint the ChatGPT/Claude connectors call by convention; for semantic search over analyzed videos specifically use `search_videos`. Returns {"results": [...]}; when you have no connected accounts it returns reason="no_connected_accounts" plus a connect_url instead of results.

  ConnectorOAuth

• getPaperDetailsA

  qubitsok — Quantum Computing Jobs, Papers & ResearchersA

  Get full details for a specific quantum computing paper by its arXiv ID (e.g., "2401.12345"). Use after searchPapers or getLatestPapers when the user wants to dive deep into a specific paper. Returns: complete abstract, all authors, publication date, AI-generated tags with reasons, hook (one-line summary), methodology, gist, and key findings. Requires a valid paper_id from search results. Returns error if not found.

  ConnectorNo auth

• search_mcp_registryA

  fresh-feeds — trending/new/changed MCP servers + x402 change-data APIA

  Search the continuously-maintained MCP server registry (deduped, quality-scored, refreshed every 30 min) by name/title/description. Free; returns up to 25 matching servers with score, status, remotes and packages. For the FULL corpus (~1500 servers) use get_mcp_registry_snapshot (paid, x402).

  ConnectorNo auth

• get_multi_night_ratesA

  Gondola Award Travel SearchA

  Get cached, partial rate observations for a hotel over a flexible date range. Use this for seasonality shape and to shortlist candidate check-in dates (e.g. "any week in May"), never to prove a missing date is unavailable. `nights` is the exact stay length and `end_date` is the latest checkout, not the latest check-in. Coverage is especially sparse far in the future. Confirm every selected exact stay with get_hotel_rates before stating availability or a bookable price.

  ConnectorOAuth

• search_transcriptionA

  PodLearnA

  Keyword search WITHIN a single episode's transcript. Returns matching chunks with surrounding context. Use instead of get_transcription when the user asked about a specific topic — server does this faster + cheaper on context.

  ConnectorNo auth

• smi_get_deep_reportA

  SMI Aware AssistantA

  Fetches a single SMI deep report by id. Research Bundles are deep-report products, so use this tool for a Research Bundle id too rather than constructing a research_bundle: reference for the generic fetch tool. Accepts product-prefixed ids: RB-11751 (Research Bundle) and DR-11751 (Deep Report) both resolve here.

  ConnectorOAuth

• modem_docsA

  ModemA

  Search or read Modem's public docs to answer how Modem works: setup, integrations, this MCP server and its scopes, the API, and automations. Not for your organization's data; use `search_modem` for that. Send a `query` to search, or a `page` path from a search result (such as `api/modem-mcp-server`) to read the whole page. Send exactly one. Read-only, spends no agent credits.

  ConnectorOAuth

• createDeepResearchA

  Parallel Task MCPA

  Creates a Deep Research task for comprehensive, single-topic research with citations. USE THIS for analyst-grade reports, NOT for batch data enrichment. Use Parallel Search MCP for quick lookups. After calling, share the URL with the user and STOP. Do not poll or check results unless otherwise instructed. Multi-turn research: The response includes an interaction_id. To ask follow-up questions that build on prior research, pass that interaction_id as previous_interaction_id in a new call. The follow-up run inherits accumulated context, so queries like "How does this compare to X?" work without restating the original topic. Note: the first run must be completed before the follow-up can use its context.

  ConnectorOAuth

• conversations_searchA

  Perspective AIA

  Semantic search over conversation transcripts for a perspective. Returns a synthesized answer with source references. Use for qualitative / thematic questions: - Themes, sentiment, pain points, motivations - "What do people say about X?" - Broad sweeps where exact phrase match is not required Prefer conversations_data_analysis for counts/distributions. Prefer conversations_explorer for exact phrases, deep multi-transcript reads, or pattern comparisons (async job — poll with perspective_await_job). Prefer perspective_get_conversation when you already know the conversation id. Behavior: - Read-only. - Open-world: queries an external managed semantic search index built from the perspective's transcripts. - Errors when the perspective is missing/inaccessible. Returns result_kind "unavailable" when the search index is not ready.

  ConnectorOAuth

• fetchA

  OneQAZ Trading IntelligenceA

  Purpose: ChatGPT-connector-standard document fetch by id from `search` results. Namespaces: `tool:{name}` returns the tool's full documentation and how to call it; `resource:{uri}` returns the resource's live data (core resources resolved server-side — also the bridge for clients without MCP resource support, e.g. Gemini); `signal:{market}:{symbol}` returns the symbol's latest combined research signal. Triggers: ChatGPT connectors / Deep Research call this after `search`. Clients without MCP resource support can call it directly with a known resource id, e.g. fetch("resource:market://global/summary"). When to call: whenever the full content behind a search result id is needed. Prerequisites: a valid id — from `search` results or a known namespace id. Next steps: for tool docs, call the named tool via tools/call; for signals, get_signal_detail / explain_decision for deeper evidence. Caveats: uncovered resource uris return description-only text (no fabricated data). `text` is a JSON document for resource/signal ids. Output: {id, title, text, url, metadata, disclaimer, is_investment_advice, data_classification} — flat envelope, OpenAI fixed shape.

  ConnectorNo auth