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675,782 tools. Updated 2026-10-19 08:48

"Discover" matching MCP tools:

  • Discover genre-aware new releases, strong public-archive matches, or popular OffStereo shows. Call exactly once per listener request: put every positive genre into the same genres array, use [] when none were requested, and avoid one call or card per genre. query carries the listener's full wording, exclusions, counts, and no-padding constraint. Results remain relevant rather than padding a requested genre or archive search with unrelated rows. Dated music-history requests use music_today and are not a discover mode. playableOnly limits results to music that plays in ChatGPT. allowBuild and allowSave preserve a read-only request. The result card already includes song playback; a separate one-song card is for an explicit request for a dedicated song card.
    ConnectorNo auth
  • Recommend WHERE the user should eat, drawn from what they have actually ordered through Layout. Use it for 'where should I eat', 'what coffee spots would I like', 'somewhere new for lunch', 'anywhere good near me' — any ask for a suggestion rather than a specific restaurant. Pass `geo` whenever you have the user's coordinates and `near` when they NAMED a place ('I'm in Roseville', 'what about downtown Oakland'); distance and open-now are computed from that, not from where they last ordered. Read-only: it never orders and never charges. EVERY SUGGESTION COMES WITH ITS EVIDENCE. `reason` is the conclusion Layout computed ('Because you order iced decaf lattes') and `becauseOf` is what it was computed FROM — the restaurants and items off their own order history. Cite it: 'based on your orders at Fourscore Coffee' is checkable, where 'you seem like a coffee person' is a guess, and the difference is the entire point of this tool. Relay `reason` as given. NEVER invent a reason, attribute a taste they have not shown, or describe a restaurant beyond the fields returned — you are not being asked what you know about their city, you are being asked what LAYOUT knows about them. AN EMPTY LIST IS AN ANSWER, NOT A FAILURE. `nothingBecause: 'no_orders'` means Layout has nothing to reason from — say so and offer to order something; do NOT fall back to restaurants you happen to know, which would present your own guess as their personalization. `nothingBecause: 'no_matches'` means their tastes matched places but the filters excluded them all — offer to widen it. HOURS ARE PART OF A RECOMMENDATION. Each place carries `openStatus`: 'open', 'closed' or 'unknown'. The list already leads with what is open, so suggest from the top and do not point somebody at a shut door. Say `closesAt` when you have it: 'open until 5' is actionable where 'open' is not. 'unknown' means Layout holds no hours for that place — say you do not know them, and never call it closed or open. Lead with ONE suggestion and offer the rest: a list is a search result, and they asked for a recommendation. WALKING DISTANCE IS A CONSTRAINT. When they want somewhere they can walk to, pass `walkable: true` and `query` with the kind of food they named: nothing further than a short walk is suggested, and if nothing they would like is that close, the result is a walkable search instead (`walkableSearch: true`, rows in `places`), which are not personal picks and must not be described as based on their orders.
    ConnectorOAuth
  • Discover AgentMarketplace's capabilities, tools, auth methods, and scopes. Call this first when connecting to AgentMarketplace to understand what's available and how to authenticate. No authentication required. Returns a catalog of available tools, resources, auth methods, and scopes.
    ConnectorNo auth
  • Find APIs on the Routavo network that can perform a capability. Returns each provider with its published price, measured latency, terms, and the exact argument schema for calling it, plus the rule Routavo uses to pick between them. Call this before call() when you do not already know a provider id.
    ConnectorNo auth
  • Find what official data is available about a topic. Use this to explore what datasets exist. It returns catalogue metadata, never observations — and neither do ``ask`` and ``build_url``, which prepare an exact source request that still has to be downloaded and queried (``fetch`` / ``stage_url`` when the client cannot do that itself). **Two response shapes**, and ``shape`` says which one arrived. - ``ranked`` — ``results`` lists matching datasets, best first, each with its dimensions, coverage, and the ``matches`` that justify it. - ``anchored`` — ``topic`` named one concrete code (a place, a country, an indicator) and nothing forced the ranked path. The answer is then ``anchor`` (the code chosen, and what else the topic could have meant), ``facets`` (what varies across the datasets publishing it) and ``anchored_datasets`` (those datasets, paged by ``page.next_offset``). ``results`` is ``[]`` on this shape by construction — that is not "nothing found". If the chosen code is wrong, re-query with one of ``anchor.alternatives[].name``. The two shapes never both appear. Anything that scopes the search is served by the ranked path: ``agencies``, ``region``, ``user_country``, ``keywords``, a non-English ``language``, or an ``offset`` past the anchored page. A code also stays ranked when fewer than max(15, ``limit``) datasets publish it (it or a code beneath it), and when resolving it or counting its datasets fails or does not finish in time — that last case, and only it, carries a ``retrieval_degraded`` warning with level ``anchor_unavailable``; a retry may then anchor. Anchored rows are datasets that publish the code or one beneath it — never ones merely permitted to carry it, never ones carrying only its parent. Two keys explain the rest of the response: ``_k`` expands the abbreviated row keys, and ``_notes`` explains whatever this particular response happens to contain, keyed by field or ``field=value``. Common workflow: discover -> inspect -> ask
    ConnectorOAuth
  • looot: free search of the data API catalog for up to 5 eligible endpoints by task, capability, category, provider, endpoint, input-schema, output-schema, schema, or hybrid mode (auto infers one). Each result has bounded relevance/evidence/availability/price/freshness components and its category; unknown evidence stays distinct from zero. minimumScore is applied before resultLimit. Identity modes never substitute another endpoint or provider. Never returns a mock endpoint. `detail` changes only how much of each candidate comes back, never ranking or matching: "full" (default) is the whole candidate; "title" returns rank, endpointId, provider, name, capability, category, estimatedPrice, priceBasis, costPerSuccessUsd, async, works {rate, runs, p50Ms, thin} and sourceCapability, enough to pick one to inspect. `capability` is the job id; `sourceCapability` the raw registered slug. Full candidates carry `credential` ("platform_own_key_optional": the platform key runs it, your own key is optional). No endpoint for the named job: candidates is empty and meta.warnings has "no_supply_for_job: <jobId>: ...". maxPrice removed every match: meta.warnings has "price_above_max: <jobId>: ..." naming the cheapest. `jobInputs` are the inputs for the `job:<id>` run; a pinned tool id takes that tool's own field names, so inspect it first. For more than 5 results or a whole category, use `search` (limit up to 200, category/provider/capability/price filters). This search is lexical: when the job is easier to describe in a sentence and nothing here is a confident match, discover_smart judges a shortlist with one small paid AI call (see its description for the cost). `prefer` (balanced default, cheapest, reliable, fastest; `ranking` is an alias) orders providers inside a job; each full candidate's `facts` says why. Field details: https://api.looot.ai/llms-full.txt.
    ConnectorAPI key

Matching MCP Servers

  • A
    license
    Not graded
    quality
    C
    maintenance
    Enables coding agents to run disciplined hunts over public data, enforcing evidence ledgers, calibration controls, novelty checks against catalogues and literature, and fresh-eyes review before any claim is trusted. Human-only decisions such as waivers and expert attestations stay out of reach of the agent.
    MIT
  • A
    license
    Not graded
    quality
    A
    maintenance
    MCP server registry and marketplace that enables dynamic discovery, installation, and activation of tools at runtime, allowing AI agents to use new tools without restarting.
    913 npm
    7
    MIT

Matching MCP Connectors

  • Search, inspect and invoke every public tool on Invokera through one MCP connection.

  • Read-only city guides and public itineraries for family and group trips.

  • Browse voices with sorting and filters. Unlike focus (which curates by depth — load-bearing, fresh, aging), discover gives direct control: sort by weave count to find the most carried-forward thoughts, by warmth to find voices in the most attended-to currents, or by age for the newest arrivals. Filter by current, language, or room.
    ConnectorNo auth
  • Find the right ToolRouter tool for your task. Describe what you need in plain language. Examples: "analyze a website", "research competitors", "find prospect companies", "check DNS records". Exact tool name (e.g. "seo") returns full schemas and examples. Flow: prefer route({ intent }) to pick and run a tool. Use discover when you need schemas or a listing, then call use_tool(tool, skill, input). Every discover response also includes a top-level `connectors` array listing SaaS accounts the user has already connected (LinkedIn, Google, Notion, etc.). Use that to pick the right tool and account without asking — e.g. if `connectors` shows LinkedIn, the linkedin-post tool is ready to use. Categories: data, media, search, marketing, development, communication, analytics, productivity, ai, finance, security, infrastructure
    ConnectorNo auth
  • START HERE. One call that returns the public lobby, every public room, the agents you can talk to (real first, demo personas labeled isDemo=true), and concrete next steps. Works with or without an API key.
    ConnectorNo auth
  • START HERE. One call that returns the public lobby, every public room, the agents you can talk to (real first, demo personas labeled isDemo=true), and concrete next steps. Works with or without an API key.
    ConnectorNo auth
  • Find a paid endpoint. Free: searching the catalog costs nothing. Keyword search is the fastest path from a task to an endpoint: pass `query`. No results is a real answer: nothing offers that term. Pass `domain` to list one service's endpoints, `url` + `method` together for one endpoint's full docs (parameters, request-body schema), or no arguments at all for the allowed service domains.
    ConnectorOAuth
  • Discover all available PulseNetwork verticals. Returns a categorized list of all 76 intelligence APIs (971 endpoints) with descriptions, coverage, pricing, and available actions. Use this to find the right vertical for a task.
    ConnectorNo auth
  • One project chosen at random from the archive. Editorial serendipity: the way a reader opens a magazine to an unplanned spread.
    ConnectorNo auth
  • Discovery: finds the true requirements of the person's job before any model is chosen. Start with purpose: the reply carries the discovery instructions and the evidence catalogue. YOU ask the person the questions (one thing each, plain words, offering the returned choices); then call again with the sealed session, their answers and your structured updates. Each reply gives progress, rejected updates with reasons, next targets, answer choices from live data and a shortlist. At most 5 rounds. Ends with a confirmation view; call with confirm=true once the person agrees. The person can stop any time (end_now=true). Nothing about the person is stored by XFMS.
    ConnectorNo auth
  • Discovery: finds the true requirements of the person's job before any model is chosen. Start with purpose: the reply carries the discovery instructions and the evidence catalogue. YOU ask the person the questions (one thing each, plain words, offering the returned choices); then call again with the sealed session, their answers and your structured updates. Each reply gives progress, rejected updates with reasons, next targets, answer choices from live data and a shortlist. At most 5 rounds. Ends with a confirmation view; call with confirm=true once the person agrees. The person can stop any time (end_now=true). Nothing about the person is stored by XFMS.
    ConnectorNo auth
  • Browse recent discoveries and investigations. Continue a page only with its returned cursor. Set mode to seeking for objects tagged need-help: answer a question, offer an experiment, or explore an adjacent problem. With group_by=work, seeking omits resolved/completed/closed tags and non-live claims. Read current replies and contribute the next useful piece. Pass view=summary for items without bodies.
    ConnectorNo auth
  • Search for hotels, restaurants, attractions, or activities to recommend to the traveler, returned as rich visual cards (image, rating, price level, link). Use this when the user wants suggestions or things to do/eat/stay near a place.
    ConnectorNo auth
  • Find agents and MCP servers for a natural-language task. Filter by resource type, protocol, callability, health availability, authentication, capability evidence, skill, source, and freshness; paginate with page and limit. Returns ranked candidates with match reasons. Location, language, pricing, and side-effect metadata are not indexed yet and are reported in meta.unsupportedFilters. Unknown states never satisfy known-state filters.
    ConnectorNo auth
  • Search sealed handoffs. Default sort is savings. Demos hidden unless include=demo.
    ConnectorNo auth
  • Search sealed handoffs. Default sort is savings. Demos hidden unless include=demo.
    ConnectorNo auth