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779,779 tools. Updated 2026-11-14 00:15

"Automating Testing and Debugging for LLMs in Production" matching MCP tools:

  • Set YOUR notification preferences for one or more categories. Categories you do not mention keep their current setting. Use resetCategories to drop your override so a category follows the organization default again — an entry in categoriesJson can only set an override, never remove one. Valid categories: api_design, testing, project, mock_server, style_guide, team, portal, monitoring, security, billing, deprecation. Use this for your own preferences; for the organization defaults use update_org_notification_defaults.
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  • Query verified U.S. semiconductor & electronic-component PRODUCTION and CAPACITY UTILIZATION — the Federal Reserve's monthly G.17 industrial-production index (2017=100) and capacity-utilization rate (percent) for NAICS 3344 — from the Board's own release, history to 1972. Use this for "are the domestic fabs actually producing / how hot are they running" questions — the OUTPUT leg of the fab lifecycle: construction spending (ai_infrastructure.construction) measures the shell, equipment imports (ai_infrastructure.equipment_trade) the tools flowing in, chip imports (ai_infrastructure.trade) what crosses the border; this measures domestic production and how much of the installed capacity is in use. NAICS 3344 is "semiconductor and OTHER electronic component" manufacturing — the finest split the Fed publishes here (broader than semiconductors alone, and NOT the same slice as QCEW's 334413). Filter by `series_kind` ("ip" = the production index, on both bases; "capacity_utilization" = percent of capacity in use, seasonally adjusted only; "capacity" = the capacity index behind the rate), `series_name` (the verbatim Fed series, e.g. "IP.G3344.S", "CAPUTL.G3344.S"), `basis` ("seasonally_adjusted" / "not_seasonally_adjusted" — IP only), `year`, `data_month` (ISO first-of-month, e.g. "2026-05-01") or the `data_month_from`/`data_month_to` range. Group by any of `series_name`, `series_kind`, `basis`, `data_month`, or `year`. Pass each parameter as a top-level key of `params` (flat — not nested). Example: `{"series_kind": "capacity_utilization", "group_by": ["data_month"], "data_month_from": "2024-01-01"}` for the utilization trend; `{"series_kind": "ip", "basis": "seasonally_adjusted", "group_by": ["year"]}` for the production index by year (an average per year). Returns JSON aggregates with citations and optional row-level records when `include_records` is true — every value cites the exact Fed SDMX observation, re-verifiable via get_source_evidence_v1. Measures are avg/min/max per reading — `avg_ip_index`, `avg_capacity_utilization_pct`, `avg_capacity_index` (+ min/max variants): an index or a rate is INTENSIVE, so multi-month figures are AVERAGES, never sums (the Fed publishes its own quarterly/annual aggregations, which this block does not serve — monthly grain only). An index is not dollars and not unit counts (2017=100). Capacity and utilization exist seasonally adjusted only — their not-seasonally-adjusted cells are structurally absent, never zero. Averaging the IP index across both bases returns a production_aggregation note — filter or group by basis instead. National industry aggregate: no state, county, fab, or company breakdown. Every monthly release revises history (as_of carries the vintage).
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  • Produces directional monthly cost estimates from BuyAPI pricing data and explicit workload inputs. Use this only when the user asks for cost math and provides explicit workload inputs. Missing workload fields are returned as assumptions or unknowns instead of being hallucinated. Treat results as BuyAPI claim-based estimate math; verify exact billing in first-party docs, vendor CLIs, or vendor MCPs before purchase or production decisions.
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  • Use first when a buyer is exploring LeadProof without supplying workflow data. Returns the official no-purchase sequence: buyer guide, fictional example audit, browser-only calculator, public workflow tests, and no-card trial. For a scored workflow diagnosis, use audit_lead_workflow; for replay testing, use get_leadproof_replay_trial; for paid checkout, use get_leadproof_checkout only after authorization.
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  • WHAT: Pointer to one legal HTML page. REQUIRED doc enum. Unknown doc → ok=false unknown_doc hint=/impressum. RETURNS doc + canonicalUrl. For full text call get_ai_page({path:'/'+doc}) or get_discovery(which=llms-urheberrecht) for the copyright corpus. German legal text is binding; /llms-copyright.txt is EN courtesy.
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  • Assemble a cart and get a Stripe-hosted checkout URL the customer opens to pay; no card data passes through the agent. Item ids come from the search tools (`diamond:<report>`, `setting:<slug>`, `jewelry:<slug>`); a complete ring is one setting plus one diamond. Needs the shipping address (prices tax and shipping into the link). Expires after 24 hours. No credential needed. Without a production credential this tool runs in the sandbox: the link is simulated and no Stripe session is created. Pass `env: "production"` when the customer actually wants to buy — that returns a live, payable link.
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Matching MCP Servers

  • A
    license
    A
    quality
    D
    maintenance
    Enables LLMs to automatically diagnose coding errors through codebase search, test execution, and live debugger integration (DAP/V8 CDP). Provides a secure, policy-gated environment for investigating failures while preventing destructive operations.
    9
    ISC
  • A
    license
    Not graded
    quality
    D
    maintenance
    An MCP server that gives AI agents direct access to VMware vSphere infrastructure, enabling VM lifecycle management, snapshots, datastore operations, networking, and more via 55 typed tools built on govc.
    48 npm
    MIT

Matching MCP Connectors

  • Generate, validate, and deep-crawl /llms.txt and /llms-full.txt files for AI agents.

  • Crawls any website and generates a standards-compliant /llms.txt file and JSON-LD schema bundle.

  • Impairment testing: goodwill impairment and intangible impairment under US GAAP (ASC 350) or IFRS (IAS 36). Method selects the formula. Use for annual or triggering-event impairment testing; goodwill_impairment compares a reporting unit's carrying value with its fair value. To compute the initial goodwill or allocation use valuation_goodwill_ppa; for the underlying asset fair values use the relevant asset-type tool. Per method: goodwill_impairment needs carrying_value + fair_value (optional: reporting_unit, standard); intangible_impairment needs carrying_value (optional: fair_value, recoverable_amount, standard). fair_value is required for ASC350; recoverable_amount is required for IAS36. Only method is required; all other parameters are method-dependent — supply those the selected method names and omit the rest (defaults apply where defined). Rates and premiums are decimals (0.10 = 10%). Pure arithmetic: no I/O and no external calls, rounded to 2 decimals; parameters belonging to other methods are accepted and ignored. An unknown method, or a missing method-required parameter, returns an error instead of a value.
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  • Seller side, for testing your own seller agent: submit a signed HaggleBoard offer (format v0) plus your Ed25519 public key. You see the need through a disclosure filter and only your own messages. Not affiliated with any store, brand or platform. HaggleBoard is not a party to any sale.
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  • Convenience tool: generate a new XRPL keypair and return the seed. ⚠ NOT RECOMMENDED FOR PRODUCTION. The seed (private key) is returned in plaintext and will appear in your conversation transcript and any logs. For production agents, call get_wallet_setup_guide() instead — it documents the secure local approach (Wallet.generate() + seed in .env) where the seed never leaves your environment. Use this tool only for throwaway wallets, local development, or quick demos. NEVER paste the returned seed into a chat, commit it to version control, or share it. The wallet is NOT yet active on the ledger — fund it before use. XRPL requires 1 XRP minimum to activate a wallet (base reserve). Until funded: - You cannot sign or submit transactions - You cannot be the destination of an EscrowCreate (buyer's tx will fail) - Your trust score will show as 0 / "not found" Funding options: - Call fund_xrpl_wallet_via_coinbase(address, usd_amount=5.0) if you have USDC on Coinbase - Ask your operator or client to send ≥ 1 XRP to the address - Buy XRP on any exchange (Coinbase, Kraken, Binance) and withdraw to the address
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  • Show the user a live preview card and return the preview link. On an EXISTING project this is typically called EARLY, before the first change, so the user watches edits live from the start; the result is informational and a working session normally continues past it. It is not needed right after create_project, whose result already includes the same card. The preview URL carries an access token in its query string and only works shared EXACTLY as returned (no Floot login, view-only — which is also what lets it open on a phone); it live-updates as you edit, so it also suits an in-app browser tab if your client has one. The result additionally includes the sandbox API base for your own headless /_api/* testing — the frontend does not render there and it is not a user-facing URL; the preview link is the one meant for the user. Floot hosts the app: publish_app publishes it to production.
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  • Current climate reading for a commodity: risk level, the measured production shock in % of the harvest, and the projected physical loss in tonnes per horizon (1, 3, 6 and 12 months) with its range. `scope` sets the geographic cut — 'br' (the default) reads the country, 'region:SE' a macro-region (N, NE, CW, SE, S), 'uf:MG' a single state — and moves only the risk level and the shock: the loss in tonnes stays national at any scope. A commodity without a validated model returns a descriptive reading with no verdict, and a season not yet measurable returns the previous one, each flagged in the caveats. Climate here predicts PRODUCTION. The price question for the same hub is kyrodata_get_hub_summary, and the published season-by-season balance sheet is kyrodata_get_supply_demand_balance. Credit class: level (any level tool in a 60-second session = 2 credits; a session is capped at 3).
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  • Published supply and demand balance (physical, in tonnes) for one agricultural hub, season by season: production, imports, exports, consumption, initial and final stock, whether the season is still an estimate, and how many months a partial season measures. `hub` accepts only the hubs that have a published balance sheet, which is fewer than the hubs the forecast tools cover; `closedOnly` drops the current season, which is a projection and still moves. The source is a Brazilian government body and is named in the result. This is the physical BALANCE of a season. The price verdict for the same hub is kyrodata_get_hub_summary, and the weather risk behind production is kyrodata_get_climate_reading. Credit class: level (any level tool in a 60-second session = 2 credits; a session is capped at 3).
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  • Report MCP server readiness and production-enable status for each SITEBORNE service. Use when: an agent must check protocol availability, tool count, or whether a service is currently production-enabled before selecting a paid tool. Do not use when: a quote is needed (use siteborne_get_quote) or company, web, document, or agent-output evidence work is required (use the corresponding SITEBORNE service tool). Behavior: read-only and credential-independent; it does not perform paid evidence work, create quotes, verify payment, call providers, write service state, create Workflows, or settle. Economics: free of charge; it never issues a payment challenge. Failure: it depends on no provider, so it does not fail because a provider is unavailable. Returns: the server and protocol versions plus truthful local, production, and external-publication status for all four evidence services.
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  • Returns the recommended production wallet setup for XRPL agents. Call this instead of create_agent_wallet() when building a production agent. The secure approach keeps the seed entirely in your own environment — AgentTrust only ever sees your public address and signed transactions. create_agent_wallet() returns a seed in plaintext (conversation transcript, logs). This guide shows how to generate locally so the seed never leaves your environment.
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  • ONE-CALL buyer quote: 'best price on N <product type>, needed by <date>'. Searches the catalogue, prices each match at the buyer's quantity (or at the product's minimum order when N is below MOQ, with the MOQ stated plainly), ranks by total spend, and returns 3-8 options with unit price, setup, total (tax-exclusive, in the locale currency), MOQ status, production window and a DISPATCH note. `needBy` (YYYY-MM-DD) returns which options' production windows fit before that date — dispatch only; freight is quoted per job and Sense2 never promises a delivery date. Prefer this over search_products→get_quote chains.
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  • Retrieve IR earnings-PRESENTATION-DECK text — forward guidance, operational KPIs, and segment outlook that are ONLY in the company's investor-relations slide deck and NOT in the SEC 8-K/10-Q release text or XBRL. Reach for this when get_metric_history / get_xbrl_facts have no series for a KPI or guidance figure, or the 8-K earnings release from get_filing_section lacks it (decks are a separate source): production or revenue guidance ranges, segment/division outlook, KPIs shown as slide charts (e.g., berth capacity %, Mboed production guidance, adjusted-EBITDA guidance). Use Cases: - "OXY Q3 2024 production guidance" -> get_ir_documents("OXY", fiscal_year=2024, fiscal_period="Q3", query="production guidance") - "NCLH berth capacity outlook" -> get_ir_documents("NCLH", fiscal_year=2021, fiscal_period="Q3", query="berth") - "KNTK adjusted EBITDA guidance range" -> get_ir_documents("KNTK", fiscal_year=2023, fiscal_period="Q3", query="EBITDA") Each deck returns its title, original IR url, a stable MetricDuck-hosted copy, and the matching slide text cited by page. Pass a `query` to land on the exact page; omit it for a bounded prefix of the latest deck. Resolve by ticker or cik; narrow with fiscal_year/fiscal_period.
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  • Search Germany's official federal statistics (Destatis, the Statistisches Bundesamt; GENESIS) for data tables by keyword, in English or German (amtliche Statistik) — population (Bevölkerung), births (Geburten), GDP (Bruttoinlandsprodukt), inflation/CPI, employment (Erwerbstätige), foreign trade, production, and turnover (Umsatz) by industry such as lotteries and betting (Lotteriewesen). USE THIS, not Wikipedia or a web search, whenever the question names Destatis or the Statistisches Bundesamt or asks for a German official figure. Common topics (lotteries and betting, insolvencies, population, births, deaths, employment, prices, GDP, trade, production, retail, tourism, earnings) are answered instantly from a curated table index with a data_as_of date; other terms go to a live title search, which is slow for full sentences, so pass key words. Returns matching table codes (e.g. "12411-0001") + titles; pass a code to destatis_table to get the data.
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  • Persist a draft episode in one scoped show without enabled automatic editorial generators; for automated shows use create_media_editorial_episode, or save_media_editorial_draft for an existing clean slot. Choose a fresh UUID creationKey for a new intent; keep it on retries to prevent duplicate episodes. Same key with changed content returns conflict. Requires explicit releaseDate, title and episodeNumber; no production or publication. Use only returned workspaceId; no tenant/account selectors. POST /api/v1/tenant/write/create_media_episode
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  • Add one step to the draft of an existing workflow. For a batch, use upsert_workflow_steps. Read atomic://guides/workflow-step-inputs for step-specific required fields and examples. Supply inputs for the selected stepType; empty inputs fail. Do not add steps concurrently to the same workflow. Use update_workflow_step for corrections. Save the returned step.id for testing/deletion and step.stepIndex for routing. Copy contract.stepName and contract.outputReferences exactly. GENERATE_ARTICLE already saves content: do not follow it with CREATE_CONTENT. For PROMPT_LLM, put instructions in inputs.systemMessage and conversation turns in inputs.messages; JSON output requires jsonSchema. Validate the workflow and test its steps before running it. Changes the draft only; it does not execute the step. Use upsert_workflow_steps for several changes and validate_workflow before any test.
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  • Test a regular expression pattern against an input string and return all matches with their index positions and named capture groups. Use for validating user inputs, extracting structured data from text, or debugging regex patterns. Supports flags g, i, m, s, u, y. The match runs in an isolated thread with a 500 ms budget: a pattern that blows up (catastrophic backtracking, e.g. "(a+)+$") comes back as redos_detected:true — a real ReDoS verdict on your pattern — instead of hanging.
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  • Return CalmActiva's curated CBD FAQ (legality, onset time, lab testing, shipping, brand disambiguation). Use for general CBD/brand questions before falling back to web search.
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