"Understanding the term 'flux' or its various applications" matching MCP tools:

• smithsonian_browse_categoryA

  smithsonian-mcp-serverA

  Browse Smithsonian objects within one exact category — a single museum (mode "museum"), culture, indexed date term (mode "period"), object type (mode "medium"), or subject term (mode "topic"). The value must be an exact indexed category term, not free text: resolve museum, culture, period, and topic vocabulary with smithsonian_list_terms first (object_type is not enumerable there — harvest it from smithsonian_search_objects results, and treat each casing as its own category, since a harvested object_type covers only the casing it was written in). Returns the category total count, a page of matching objects, and a museum breakdown of that page; page the full category with start and rows. For open-ended or topic discovery, start with smithsonian_search_objects instead.

  ConnectorNo auth

• create_applicationA

  FlowCastleA

  Create a new application (workspace) owned by the caller. Requires a personal API key (usr_...) — application-scoped keys cannot create applications. Seeds default flows unless skipDefaultFlows is true. Creates persistent state and is NOT idempotent: calling it twice creates two applications. Returns the new application id, which you then pass as applicationId to the other tools.

  ConnectorNo auth

• tag_rule_updateA

  Prowlo — Reddit & X for AI agentsA

  Update a TAGGING RULE (dashboard: 'Tagging rules') — not a Keyword Monitor entry (those are Watchers; see watcher_update). Rename its term (pass `keyword`), set what it refers to (pass `description`), and/or pause/resume it (pass `active`). Renaming keeps already-tagged records on the old tag; new matches use the new term. Changes take effect on the next scheduled processing cycle. Existing opportunity scores and matches are not retroactively updated. (requires a free Prowlo account — call it to get a signup link)

  ConnectorNo auth

• aiapplyd_review_applicationA

  AI ApplydA

  Act on the user's applications. decision "approve" submits each waiting application on the employer's hiring system under the user's name: it spends one of their applications per job and cannot be undone. "reject" skips it: nothing is sent and nothing is spent. "cancel" stops one that is still queued or preparing. "refine" rewrites its resume or cover letter from instructions (document_type and instructions; uses AI credits). "re_prepare" builds its documents again (optional steps). "set_stage" records how it is going (stage). Pass up to 25 application_ids from aiapplyd_get_applications. Only approve on the user's explicit go-ahead, such as a "yes" to a specific application. On a timeout or an error, call aiapplyd_get_applications before retrying; an approve that already went through is reported as already approved. Do not use it for matches with no application yet; use aiapplyd_apply or aiapplyd_triage_matches. Next: aiapplyd_get_applications to follow the submissions.

  Connector

  Destructive

  No auth

• get_termA

  ESG Hub MCP ServerA

  Look up one glossary term by record ID ('term:abc123'), permalink, or exact name and return its full definition and facets. Use it when the user asks 'what is <term>'; to find terms by topic, or across all content, use search_esg or search_content, and to survey the glossary use list_terms. Name matching is exact (case-insensitive) with no fuzzy or partial matching, and it returns a single term, never a list. The `definition` field is the authoritative text and `facets` carries the topic/content_type classification; an unknown identifier returns NOT_FOUND. Cached ~10 minutes; rate-limited per IP; retry on 5xx.

  ConnectorNo auth

• aggregate_recordsA

  Kepler CRMA

  Computes counts, sums, averages, minimums, or maximums over one record type, optionally grouped by a field or a date bucket, with the same filters as list_records. Use for "how many", "per stage", "average fee", "placements per month". Returns exact figures from the database, never estimates. Placement consultant attribution groups count each placement by its percentage share; fee metrics are net of credited rebates and money is returned per currency without conversion. For pipeline questions aggregate applications, not candidates.

  ConnectorOAuth

• get_national_fha_statsA

  FinanceRateCalc HMDA statisticsA

  ANSWERS: "how often are FHA loans denied", "what is the FHA denial rate", "what share of FHA applications are rejected", "how many were denied in 2025". Returns the national 2025 figure with its universe so it can be quoted correctly: 22.1 percent, 262,250 denials of 1,187,606 applications that reached a credit decision (originated, approved-not-accepted, denied; reverse mortgages excluded), the denominator definition and the correction history. Most published FHA denial rates are 2023 purchase-only figures near 13.6 percent, a different universe, so state the universe when quoting. NOT FOR: conventional, VA or USDA loans, purchase-only or refinance-only rates, other years, or state/lender/metro breakdowns (use the dedicated tools). Historical observation computed from the public CFPB HMDA 2025 record (actions 1,2,3; loan_type 2). Not a prediction about any individual application. Attribution: FinanceRateCalc, CC BY 4.0.

  ConnectorNo auth

• calculate_refi_breakevenA

  Senaro Personal FinanceA

  Calculation, not advice. Verify with a professional before acting. Deterministic mortgage refinance break-even analysis. Given your current loan (balance, rate, remaining term) and a refinance offer (new rate, new term, closing costs, optional points), computes: - monthly P&I savings; - the cash-flow break-even month (Senaro's formula: total refinance cost divided by monthly savings, rounded up to a whole month, built on the payback test the CFPB toolkit describes); - the interest delta over your remaining-term horizon, and each loan's interest over its whole schedule (the current loan's remaining term, the new loan's full term); - a term-matched scenario that isolates the rate cut from a term reset; - a term-reset-trap flag (a longer term and a lower payment, but more interest over the new loan's full term than over the current loan's remaining term); and - the economic break-even (net-worth crossover) month under an equal-outflow model: both sides spend the same each month; the side that keeps the current loan starts with the upfront refinance cost invested at month 0 (nothing when costs are rolled in); money not spent on a payment is invested at investment_return_pct. The search runs to the end of the longer loan term, and stops earlier where a loan's term ends with money still owed. Rate-and-term refis only (cash-out and tax effects are out of scope). Pick this when refinancing your existing mortgage into a new rate and term is the question; pick `compare_mortgage_terms` when comparing two mortgage structures on a purchase you have not yet taken out. All defaults cite primary sources (LodeStar/ALTA closing-cost data, the CFPB toolkit's payback test). Scalar output, no chart series. payoff_months and payoff_month_shift use {status, value, explanation}; the two break-evens use {code, month, explanation}.

  ConnectorNo auth

• aiapplyd_get_applicationsA

  AI ApplydA

  List the user's applications and where each one stands, or read one by application_id to see what will be or was sent: the tailored resume, the cover letter, the screening answers, why it stopped, and its place in the queue, plus the employer's confirmation page as an image when that page is the proof. Use this to check progress, to find applications waiting for the user's approval (status "waiting_for_review"), or to see whether an employer confirmed a submission. An application is reported as employer-confirmed only when the employer sent a receipt or showed its confirmation page. Other status filters: queued_to_apply, submitted, verified, not_landed, taken_down. Returns 20 per page. Read-only: it spends no credits. Do not use it to act on an application; use aiapplyd_review_application. Next: aiapplyd_review_application to approve, reject or change what is waiting.

  ConnectorNo auth

• wordpress_termsA

  Opus Growth, Ad Platforms MCP ConnectorA

  Manage the CATEGORIES and TAGS of a connected WordPress site: list them, create one, rename it, change its slug, set its DESCRIPTION, move it under a parent, or delete it. action: 'list' (default) | 'create' | 'update' | 'delete'. The description is the only body text a category archive has. Without it the archive is a bare list of post titles, which is why category pages usually rank for nothing even when the posts under them do — so a new category is worth two sentences here. For the archive's SEO title, meta description, focus keyword or noindex use wordpress_set_seo with term_id. On a MULTILINGUAL site every language has its OWN term — the Turkish "Apostil ve Tasdik" and its English counterpart are two different terms with two different ids — so each row carries a `language` field and all languages are listed together; pass lang to narrow to one. list also reports each term's post count, its live archive URL and its current SEO fields, so you can see in one call which categories are empty or unoptimised. On create and update lang does more than filter: it SETS the term's language, which is what puts an English category on the /en/ archive base instead of the site's default language. Setting the language needs Opus Growth Connector 0.7.9 on the site; on an older one the call is REFUSED before anything is written, because there lang is silently ignored and the term lands in the site's default language with the wrong archive URL. Creating a term that already exists returns the existing one instead of failing. Changing a slug CHANGES the archive URL and the reply says so explicitly, because the old address then returns 404 and needs a redirect. Deleting a term never deletes posts — it only removes the link, and the reply tells you how many posts were affected. delete needs confirm=true.

  Connector

  Destructive

  OAuth

• propose_termA

  ESG Hub MCP ServerA

  Submit a new glossary term for human review. Nothing is published immediately: the call creates a pending proposal and returns a `proposal_id`; a reviewer decides whether it goes live, and only an approved term later appears in get_term. Use it only when the user explicitly wants to contribute a term; to look one up use get_term. `name` is the display name and `definition` must be at least 10 characters; `facets` is optional and its values should come from get_esg_metadata / list_industries vocabularies. Requires a write token in ESG_HUB_WRITE_TOKEN — a missing or invalid token returns 401 — and calls are rate-limited.

  ConnectorNo auth

• list_discovered_appsA

  FallaxA

  The SaaS applications the customer's own Google or Microsoft tenant says its people actually use, with how many distinct users were seen and whether Fallax ships a lure that impersonates that app. The single best predictor of whether a simulation is plausible, and the right input when suggesting what to simulate next. Returns nothing unless the workspace turned app discovery on.

  ConnectorOAuth

• calculate_current_ratioA

  liquidity-leverageA

  Calculate the current ratio, a liquidity measure of whether a company can cover its short-term obligations (due within a year) with its short-term assets. Formula: Current Ratio = Current Assets / Current Liabilities. WHEN TO USE: Use to assess short-term solvency, compare liquidity across peers of different sizes, or screen for distress risk. WHEN NOT TO USE: Do NOT use as the sole liquidity measure — it ignores asset quality and timing of cash flows (use calculate_quick_ratio or calculate_cash_ratio for stricter views). BEHAVIOUR: pure deterministic calculation — no side effects, no network or storage access; idempotent and non-destructive; identical inputs always produce identical outputs. Division by zero or non-finite inputs returns an explicit error instead of a number. RETURNS: JSON object { current_ratio: number (e.g. 1.8 = 1.8x), inputs }. PARAMETERS: current_assets (required): Total current assets, e.g. 500000. Must be >= 0. current_liabilities (required): Total current liabilities, e.g. 280000. Must be > 0.

  ConnectorNo auth

• get_tutorial_by_titleA

  Glushkov Modelling MCPA

  Read-only. Finds one educational tutorial by its human-readable title and returns its content and metadata. Use this tool when the user knows an article title but does not know its slug. Use get_tutorials to browse or filter tutorials, or to retrieve one tutorial when its slug is known. Use search_tutorial_content when the user knows only a term, technique, material, tool, or instruction that may occur inside a tutorial. The tool prefers an exact case-insensitive title match and otherwise uses a case-insensitive partial title match. Returns a not-found result if no tutorial matches the provided title.

  ConnectorOAuth

• add_termsA

  HebrewCore by baba HebrewA

  Add protected terms to the account, or update existing ones (matched by exact term text). Every later protected translation on the account (translate, translate_batch and the clinical tools) keeps these terms exactly as written, or uses `translations.he` / `.en` / `.ru` for that target language when set. Sending a term that already exists replaces its translations and note. Up to 2,000 terms per account, each up to 200 characters. Changes apply to new requests within 30 seconds. Free.

  Connector

  Destructive

  No auth

• get_filingA

  StockPortfolio.proA

  Read one SEC filing — its metadata plus short excerpts of its text. Identify it by accession number (preferred, as returned by search_filings), or by ticker with an optional filing type, which defaults to the company’s latest 10-K. Request a named section such as "Risk Factors", "MD&A" or "Legal Proceedings", or search the filing for a term. Returns excerpts with their section and the filing URL, not the whole document. Use get_company_fundamentals for reported numbers.

  ConnectorNo auth

• enrich_providerA

  apis-ioB

  One call, pick your field groups — resolves a slug OR any identifier and returns exactly the groups you ask for, instead of chaining get_provider + get_provider_rating + get_provider_artifacts + get_provider_onboarding. Groups: profile, onboarding, artifacts, rating, insights. Understanding plan — the base groups moved with the rest of the discovery layer on 2026-08-31. Priced B2 (cross-catalog synthesis) — $0.05 per call under pay-as-you-go; included in Understanding and Influence. See apis://prices.

  ConnectorNo auth

• resource_dataA

  Data Gov InA

  Fetch records from any India Open Government Data (data.gov.in) resource by its resourceId. Supports pagination, per-field filtering, field projection, and sorting. The resourceId is the UUID shown on a dataset's page on data.gov.in (and in its API URL, e.g. api.data.gov.in/resource/<resourceId>). Example resourceId 9ef84268-d588-465a-a308-a864a43d0070 is "Current Daily Price of Various Commodities from Various Markets (Mandi)" with fields like state, district, market, commodity, variety, grade, arrival_date, min_price, max_price, modal_price. Use resource_meta first if you do not know a resource's field ids.

  ConnectorNo auth

• list_keywordsA

  ExtensionDashA

  Every search term tracked for one extension, one row per term per store. status is "pending" until a fetch has landed since the term was tracked, and "scanned" once one has. A "scanned" row with a null position means we searched depth_scanned results and this extension was not among them — that is a real observation, not missing data. A "pending" row can still carry a position. Removing a keyword stops the tracking but keeps the history, so a term tracked before and added again arrives with its previous result already in place; captured_on says how old that is. Poll until the status reads "scanned" to know the number answers the current tracking. locale is the store language the term was searched in. The same term ranks differently under hl=de than under hl=en, so two rows sharing a term and a store are two different results. locales lists every store language this extension tracks, with a keyword count each — start there to work a language at a time. It always reports every language, including when the locale argument narrows the rows to one. search_volume is Google Ads' average monthly searches for the term, worldwide, in the row's store language. It is web search demand, not searches inside the store, and is the same for both stores. null means not fetched yet, Google has no data, or the term can't be looked up (symbols such as + or %, over 80 characters or 10 words, or a store language without a Google Ads mapping); search_volume_fetched_at says which. Needs an ExtensionDash account. Without one, find_listing and get_store_listing still read any extension's current store page; sign up at https://extensiondash.com/signup and reconnect using the URL on your /profile page for anything else.

  ConnectorNo auth

• get_methodologyA

  Warmth Engine ObservatoryA

  Look up the WEO methodology definition for any platform-specific term, field, or concept (e.g. "CC-V", "T2", "PAA", "ENT-1", "PIET"). Returns the term's definition, its section anchor, a deep link to that section of the published methodology, and the methodology version. Use to resolve any vocabulary the other tools return. Pass `term`; matching is exact-first, then substring, and an unknown term returns a sample of available terms.

  ConnectorNo auth

• list_termsA

  Arco LexiconA

  Returns all published Arco Lexicon terms grouped by pillar, each with its slug and canonical short definition. Accepts an optional pillar filter. Use this tool first when you do not know which term to look up — it gives you the full vocabulary to orient from. Use lookup_term once you have identified the term you need.

  ConnectorNo auth