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345,796 tools. Last updated 2026-07-30 18:56

"OpenAI's Web Retrieval Infrastructure" matching MCP tools:

  • Reconnaissance and chart retrieval across the live web and proprietary data: many results at once, returned as structured cards and web links, and the top card auto-renders inline as a chart. It locates data — and for `exportable: true` cards it also includes a free 20-row preview by default (`include_contents`) — but a license-gated card carries no rows at all (headline value only, via `description`), and a web result is only a snippet, not a value. For a plain "what is X", `tako_answer` (pin the card's `nodes` ids) is still the faster path: one written figure beats parsing a preview table yourself, and reaching here first for that costs an extra round trip that re-sends the whole conversation. Best for: breadth — fanning out many narrow queries in parallel to see what exists across several entities or metrics; retrieving a chart card when the chart or embed is itself the deliverable; and harvesting node ids and urls to feed `tako_answer` or `tako_contents`. It is cheap and fast, and built for exactly this fan-out. Coverage spans economics, finance, company KPIs, demographics, sports, markets, weather, elections, prediction markets, website/app traffic, real estate, energy, health, and more — metrics that sound web-only (e.g. SimilarWeb-style website traffic) are in the data graph. Each query resolves one entity + one metric ("Apple revenue", "Nvidia vs AMD gross margin"); broad or compound queries ("today's sports + odds") retrieve poorly. When the question is what Tako covers, or you need a metric's exact name, run `tako_available_data` (free) instead of guessing here. Data and web come back together — treat them as one result, not an either/or. Returns: `cards` (up to `count`) with preview rows and chart URLs, plus `web_results`. To read a web result in full, call `tako_contents` on its url (web urls are always fetchable; a card's full csv needs `exportable: true`). Non-exportable cards (`exportable: false`, usually license-gated) return no rows: read the headline value from the card's `description` when it carries one, or get specific figures via `tako_answer` with the card's `nodes` ids pinned (each such card carries a `values_hint` saying exactly this). Results arrive as a markdown document: a Tako Data section (per card: headline, exportable flag, node ids, chart link, a rows-count pointer), then Web Results, then source notes. The cards' actual rows and the web results' snippets ride in structuredContent (cards[].content, web_results[].snippet), not the markdown, alongside machine essentials (request_id, usage, chart-widget fields).
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  • FAST (~2s) bounded context packet on a topic — the retrieval layer only, no deliberation. Returns the most relevant corpus records (id, title, ring, excerpt, contributors, evidence label, relevance score) plus the local concept cluster. Your default orientation on any Omnarai topic. Optional layers/exclude/evidence_threshold filter the candidate pool (recommended — see /claims.json).
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  • Dump the user's monitors as a JSON structure suitable for backup, migration, or infrastructure-as-code workflows. Tokens and PII are NEVER included - only domain configuration.
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  • Explain where TideCloak can run: self-hosted vs partner-hosted (Skycloak, a managed TideCloak-as-a-service). Returns the hosting decision, the trust model, the Skycloak API reference, and the provisioning playbook. Use when the user asks about a hosted/managed option, not wanting to run their own infrastructure, or 'can someone host TideCloak for us'.
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  • Use this for advanced searches of Cameron Wilson's public archive when source, content type, date filters, transcript matching, or matched snippets are needed. Query is optional; pass only filters to enumerate. Prefer search and fetch for OpenAI knowledge retrieval.
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  • General-purpose web grounding via parallel.ai (Vercel AI Gateway). Returns synthesized text excerpts plus structured sources[] with direct URLs. Use for: topic landscapes, entity-deep teardowns, recency-sharp queries, named-vendor lookups, general fact retrieval. NOT for: Reddit/X/community discourse → use search_community. NOT for: numerical effect sizes or methodology-heavy fact-check → use search_research. The agent decomposes the brief into sub-questions BEFORE calling — one focused query per call. Optional after_date (ISO YYYY-MM-DD) for fast-decay topics. Optional max_results 1-20, default 10.
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  • Create, edit, preview, publish, and manage web pages from MCP-capable AI clients.

  • Web scraper for agents: fetch any URL as clean markdown (headings, links). x402 for JS rendering.

  • Search the company's connected knowledge across every source — Drive, SharePoint, Confluence, Slack, Notion — with cited synthesized answers, lifecycle awareness, and refusal-on-weak-context. Returns a written answer with [n] citations plus the ranked source chunks. Modes: `fast` (1,500 kT — retrieval-only, no synthesis), `standard` (12,500 kT — default; synthesized answer over the top retrieval set), `deep` (25,000 kT — wider retrieval + premium synthesis for complex questions). Pick the cheapest tier that answers the question. Responses are capped at 25,000 output tokens per Claude Connectors policy; if truncated, structured metadata carries `truncated: true` and `query_id` so the agent can call `get_source_detail` for full provenance.
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  • Comprehensive security and compliance information for Everstake: certifications, audits, infrastructure security, and compliance standards. Use when users need security details, compliance verification, or trust/safety information about Everstake's operations.
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  • Search published public SkinKnowledgeBase Question pages. Required input: query string. Optional inputs: filters for concern, ingredient, product, or side_effect; limit 1-25; cursor. Returns public question search results with identifiers and canonical URLs for follow-up retrieval.
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  • List merchant knowledge base documents (uploads + scraped URLs). Use reviewStatus/syncable to see what is ready for agent retrieval. Pass `updatedAfter` for delta sync. Reviewed content is fetched via GET /v6/merchant/ai/knowledge/{id}/content; source audit text is available with ?variant=extracted.
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  • Bulk web-wide (open-web / off-Amazon) price + MAP findings across your whole watchlist, in one call — reads already-collected results, does not run a live scan. Returns every tracked ASIN with its open-web source count, cheapest off-Amazon price (+ the domain), how many web sources violate MAP, how many are unauthorized sellers, the Amazon buy-box anchor price, and how much cheaper the web is vs Amazon. ASINs not yet scanned show 0 sources / never-scanned. Use for 'where is my whole watchlist cheaper off Amazon', 'web-wide MAP across everything I track', or 'which tracked products are undercut on the open web'. For a live single-product cross-retailer check use find_product_across_web instead.
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  • START HERE. SaSame is one modular MCP Factory. Call factory_stations to inspect all 21 canonical station capabilities, then factory_start to enter the single lifecycle. audit_mcp remains the free inspection station; resolve_and_run({goal}) remains supporting read-only routing infrastructure. Measurement is status only, never endorsement.
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  • List every change-intelligence feed: source slug, label, the question each answers, per-call prices, paid x402 endpoints, and free discovery URLs. There are ~120 feeds, so pass `category` to filter (e.g. 'security', 'regulatory', 'packages', 'premium', 'infrastructure', 'compliance') and/or `compact: true` to keep the payload small. Use the returned `source` slug with preview_feed.
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  • List the Celestia whitepapers and research PDFs indexed here (slug plus title). Celestia-specific — not arbitrary web PDFs (use a web-search tool for those). Use get_whitepaper to read one by slug.
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  • The daily "what changed on the internet" digest: a ranked top-20 of the most significant DNS, TLS, WHOIS, and infrastructure changes observed across the tracked catalog in the last 24 hours. Free and keyless. The complete change wire with sync cursors is the keyed /v1/changes endpoint.
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  • "Find protein [name]" / "look up [gene] in UniProt" / "BRCA1 / TP53 / insulin protein info" / "all proteins for [organism]" — UniProtKB search via Lucene-style queries (e.g. "gene:BRCA1 AND organism_id:9606" for human BRCA1). UniProt is the authoritative protein-sequence-and-function database — use for protein characterization, function annotation, sequence retrieval, and cross-references to PDB/GO/PubMed.
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  • Add a free-form text document to the knowledge base. Use for pasted policies, FAQs, internal notes, brand voice references — anything the agent should be able to retrieve later. Stored as a single document; agent-side embedding/retrieval happens elsewhere.
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  • List Canton Network ecosystem projects (DeFi protocols, wallets, custody, infrastructure, NaaS, etc.) from the curated canton.wiki catalog. Filter by category or free-text query. Returns name, category, description and URL: a static directory of who-builds-on-Canton, not live on-chain/TVL data (use get_token_market for live DeFi TVL). Canton-only.
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  • MUTATES Scalingo infrastructure — creates or updates environment variables in bulk (each { name, value } is created if new or updated if it exists). This usually triggers a restart to apply the new env. Names ≤64 chars, values ≤8192 chars. Scalingo API: PUT /v1/apps/{app}/variables. Returns { variables }.
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  • MUTATES Scalingo infrastructure — triggers a new deployment from a source archive URL (a tar.gz reachable by Scalingo). To roll back, re-deploy a previous git_ref/archive — there is no separate rollback endpoint. Scalingo API: POST /v1/apps/{app}/deployments. Returns { deployment }.
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