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741,183 tools. Updated 2026-11-04 01:59

"Uptime Kuma" matching MCP tools:

  • Get one monitor with its recent checks. The include flags pull in what the monitor detail page shows next to it: uptime and latency percentiles over 24h to 90d, the alert policy that applies (inherited or its own), its maintenance windows, and the fire/resolve history of its alerts. Use this when you already have the monitor id; to browse a project's monitors use list_monitors. Requires project context.
    ConnectorAPI key
  • Read a report across screens for a time window. When to use: - Uptime and outage causes, what actually played, or who changed what. When NOT to use: - One screen's detail: use get_screen_status. What is wrong now: use list_items kind alerts. What to know: - Reads stored history only; only screens this connection can see count. Needs screen.view (uptime), playback-log.view (proof_of_play) or audit-log.view (audit_log). Parameters: - report: uptime (online % per screen, outages with causes, worst first, one-line insights), proof_of_play (plays, watch time, skips and failures per content, and where) or audit_log (who changed what, newest first, by name). - from and to: uptime and proof_of_play only; ISO 8601; default the whole stored window (30 days for uptime) up to now; a non-ISO value is refused. screenId: uptime and proof_of_play only, one screen. - since, limit (default 50) and cursor (nextCursor of the previous page): audit_log only. - Parameters for another report are ignored. Example: {report:"uptime", from:"2026-10-13T00:00:00Z"}.
    ConnectorOAuth
  • Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FEES: every opportunities[] row and partition_check.arbitrage carry edge_pp_gross (== gap_pp / overround_pp), fees_pp, edge_pp_net, net_positive, plus polymarket_fee_pp, fee_basis and fee_categories[]. BOTH cost components are modeled: Polymarket's own per-category TAKER FEE (fee = shares × rate × p × (1-p), rates crypto 0.07 / sports-economics-culture-weather-other 0.05 / finance-politics-mentions-tech 0.04, geopolitics and world events fee-free; verified against Polymarket's own docs as of 2026-09-13) and Polygon gas (~$0.02/leg). The taker fee dominates: ~$1.75 per 100 shares on a crypto market at 50c versus $0.02 of gas, so rows that looked profitable before fleet #1927 may now show net_positive:false — that is the correction, not a regression. Each leg is priced at ITS OWN market's rate and price (the fee curve peaks at 50c and falls toward both extremes). fee_basis says where the rate came from: 'payload' (read off the market, the normal case), 'category' (mapped from its fee category), 'fee_free', or 'fallback' (rate unknown — charged at the modal 0.05 rather than assumed free, so an unreadable market is never reported as costless). Where fill_check reprices against live depth, this does NOT double-count that spread cost. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.
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  • Checks x402 protocol conformance for a target service URL: a live 402 probe (well-formed challenge, non-empty accepts, atomic-unit amounts) plus price coherence against the target's own well-known. PAID ($0.10 USDC via x402). This MCP server holds no wallet, so calling this tool returns the upstream payment requirements rather than a result — pay them with your own x402 client, or call the endpoint directly. A signed, permanently published attestation of the same check is available at /midas-ops/attest ($0.50). Does NOT measure output quality, uptime history, or on-chain transaction volume — see the returned scope_note.
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  • Get the public dashboard summary The free marketing-dashboard rollup: the network-wide host rollup (fleet count + mean uptime/latency), the hourly fleet-average p50 latency trend over the last 24h, and the top-10 providers by market share (0..1 fraction). No host list, full registry or arbitrary per-host uptime is exposed.
    ConnectorNo auth
  • List the monitors on the account, newest first, 30 per page. Each entry carries the id needed by every other tool, plus name, url, type, current status, check frequency and the uptime percentage over the last 24 hours. Start here when the request names a monitor by name rather than by id, and when asked what is broken - filtering by status "down" answers that in one call. Returns an empty list rather than an error when nothing matches.
    ConnectorNo auth

Matching MCP Servers

  • A
    license
    A
    quality
    A
    maintenance
    MCP server for Uptime Kuma that enables monitoring and management of uptime monitors, heartbeats, notifications, tags, and maintenance windows via natural language.
    35
    590 npm
    62
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables LLM clients to manage Uptime Kuma HTTP(S) monitors, groups, tags, and notifications, and to retrieve heartbeats, stats, and incident history through MCP tools.
    MIT

Matching MCP Connectors

  • Prices Kalshi daily high-temperature markets against the NWS forecast for the market's OWN settlement station, and measures whether that forecast actually beats the market. Two modes. LIVE (default): returns the full strike ladder for one city and settlement date with market_prob (mid), forecast_prob, and edge_pp per strike, plus the settlement clause verbatim. BACKTEST (`backtest_days: N`): scores an archived gridded forecast against the market on settled days and returns brier_market vs brier_forecast with a plain-English `verdict`, so the edge is MEASURED rather than asserted. READ THE WARNINGS — they are not boilerplate. (1) These markets DO NOT settle on the NWS. They settle on The Weather Company (weather.com) at a Kalshi station code such as CLINYC, which the response quotes verbatim; so part of every edge_pp is NWS-vs-Weather-Company disagreement about the same day at the same station, which is not mispricing and not tradeable. `settlement_vs_forecast_basis_f` from backtest mode is that part as a number. (2) The station is DERIVED from the settlement clause, never from the city name: Chicago settles at MIDWAY and New York at CENTRAL PARK, so a city-centre forecast would misprice a whole ladder. A station that cannot be resolved yields rows with no forecast and a reason, never a guessed coordinate. (3) forecast_prob assumes a normal distribution around the NWS high whose width is ASSUMED, not fitted (stated in `distribution_assumption`) — run backtest mode to see whether it is calibrated. (4) edge_pp is gross: no Kalshi fees, no bid-ask. MEASURED RESULT, AND IT IS NOT THE FLATTERING ONE: on the first backtest (KXHIGHNY, 13 settled days to 2026-09-11, 58 market observations) the MARKET beat the forecast — Brier 0.1008 for the market against 0.1594 for the archived gridded forecast, lower being better. So on that sample there is NO forecast edge to sell, and a large edge_pp is more likely to be the model disagreeing with a better-informed market than an opportunity. The measured settlement-vs-forecast basis was 1.7F mean absolute over 8 pinnable days, slightly warm-biased, which is a big share of a typical edge_pp on a 2-degree bracket. Re-run backtest_days before believing any edge; if a later sample reverses this, the numbers say so. NWS is US-only, so the ~30 international Kalshi weather series (London, Paris, Tokyo) return market prices with forecast_unavailable rather than a forecast. Precipitation series are listed but not yet priced. Cities: nyc, chicago, los angeles, miami, austin, houston, denver, philadelphia — or pass `series_ticker` for any other (e.g. "KXHIGHTBOS").
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  • Claygent-style per-row research: answer ONE question about ONE company and return a JSON object matching your output_schema, with every field wrapped in its own evidence — {value, evidence_url, quote, status}. status is NEVER self-reported by the model: "found" means this code independently verified the model's quote is a VERBATIM substring of text actually fetched; "inferred" means a value was given but the quote could not be verified; "not_established" means no source answered the field, and its value is always null — never guessed, never a blended score. Sources: "web" fetches the company's own site (entity.domain required — homepage, /about, /leadership) via fetch_url; "catalog" checks entity_profile (SEC EDGAR; resolved:false for a private company is expected, not a failure); "both" (default) tries both. max_cost (USD, default 0.02, max 0.50) scales how many pages are fetched and refuses up front if it is too small to pay for even one extraction call (floor $0.002) — never silently overspends. A row where every source comes back empty costs nothing: every field is mechanically not_established with NO model call made. For a boolean/derived field (e.g. "does this company sell to healthcare"), the quote only has to SUPPORT the value — a descriptive sentence about customers/products counts, the source need not state the answer verbatim. leadership_page_status ("fetched"|"not_found"|"not_attempted", plus leadership_note) says plainly whether a leadership/team page was actually read, so a named-person field (head_of_sales) coming back not_established is distinguishable from "this company just doesn't publish one" vs. "we never checked". model_output_empty:true means the model returned nothing usable (a transport/budget problem) — every field is not_established for THAT reason, never read as 20 individual "no" judgments. Use with a fixed question + schema across many rows for "Claygent over N companies with a hard cost cap" (composes with batch callers). For picking from a fixed label list instead of extracting open fields, use classify_row (cheaper, one model call).
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  • Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server in your client (another vendor's Gmail, Splunk, Slack, etc. connector), we cannot fix it and reporting it here only delays you; file it with that server instead. Not sure? Pipeworx tool names are the ones this connection lists. Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. Filing without an account returns a `claim_token`; pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed and what changed. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.
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  • For one model, list the monitored relays that sell it, one row per relay using its highest-uptime group: input/output/cache price per 1M tokens in the relay's own currency (CNY or USD), 24h uptime and latency. Sorted by uptime, then price. Paged with limit and offset: total, returned, hasMore and nextOffset say whether the page is complete, and coversAllRelays is true only when it holds the whole board. This is not a price ranking and includes USD-priced relays and promotional groups; for the lowest price under an uptime condition use find_cheapest_relay.
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  • Use this when a signed-in operator asks what changed on a monitored domain, whether its website went down, or what the monitoring has flagged. Read the monitoring alert log for the domains the caller's account monitors, newest first, including website uptime incidents (site_down, site_partial, site_recovered, and site_blocked when the site's protection refuses our checks). Requires an API token. Each row carries id, domain, type, check, summary, a deterministic detail map, created_at, email_sent_at, acknowledged_at and delivery_class — a 'dashboard_only' row was deliberately kept out of the digest mail, so an agent watching only the inbox would never see it; this log is the complete picture. PAGE DOWN BEFORE ADVANCING `since`: next_before is non-null exactly when older rows remain, and a caller that ignores it, takes a full page and moves its watermark to the newest row it saw drops every row it did not receive. `since` is an INCLUSIVE floor, so rows repeat rather than go missing — de-duplicate on id. READ-ONLY by decision: there is no ack and no delete here, because acknowledging an alert is the human's own triage on their dashboard and an agent that acks on their behalf silences a row they have never seen. Report what the log says and let them clear it.
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  • Find templates in the Control Plane Template Catalog: databases, caches, queues, search, storage, gateways, AI, analytics, auth, security, automation, observability, developer tools, and self-hosted products. Pass `query` naming the capability or product needed ("vector database for RAG", "uptime monitoring with status page", "self-hosted Google Analytics"); when the user describes a goal or problem instead, decide the capability it needs and search for that. Results are ranked, each with a confidence, what must exist before install, and the template to pick instead for other needs. Omit `query` to list the catalog or one `category`. An app the user asks you to build, such as a blog, wiki, or shop, is built (plan_app) unless they name a template. Then pass the pick as `name` for its prerequisites, README notes, and the EXAMPLE values.yaml to copy for install_template. Postgres, MySQL, MariaDB, MongoDB, and Redis install with `add_database` unless they need a setting it does not take, such as backups.
    ConnectorOAuth
  • List the monitors of a project with their current status. Set grouped to see them as an environment → spec tree the way the sidebar shows them (paging does not apply then). Set includeStats to add 24h uptime, p95 latency and the response-time sparkline per monitor. Use this to browse monitors or find a monitor id; for one monitor with its checks use get_monitor. Requires project context.
    ConnectorAPI key
  • Check MentionForge Worker liveness and whether paid research can settle. Omit include_backends or set it true to keep source_backends; set false to drop that object while status and payments_ready still return; extra keys are rejected; {} is valid. Use this free pulse when you only need uptime; for list price or trial terms use get_pricing instead; for a sample payload use get_example instead; for cited mentions use research_mentions. Never charges, never runs research, needs no X-Wallet, Idempotency-Key, or PAYMENT-SIGNATURE, and does not consume the shared 10-call trial or paid rate limits.
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  • Uptime of every monitor of the project over a period, worst first, in one call: per monitor uptime_pct, downtime (seconds + text), outage count, longest outage and MTTR (mean time to resolve, resolved outages only), plus project totals (average uptime, total downtime and outages, MTTR, monitors currently down). Period from/to: default the last 30 days, at most 366. Filter by name, protocol or group. Active monitors only unless include_paused. Use it for "which monitors had the worst uptime" or an SLA overview; get_monitor_uptime gives a per-day/week series, list_outages the outages themselves. Healthchecks and servers are not included.
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  • PERMANENTLY decommission (delete) an infrastructure server from the Cycle hub. This is IRREVERSIBLE through this tool — the server is removed from the cluster and, for provider-managed servers, typically destroyed at the provider. Cycle refuses to decommission a server that still has running instances, and this tool never forces past that: the environments or containers using the server must be deleted (or their instances stopped/migrated) first. This tool is two-step by design and NOTHING is decommissioned on the first call: 1. Call without confirm. The server is resolved and the response describes it — hostname, nickname (if set), ID, cluster, provider/model/location, when it was created, its current uptime, and every instance still placed on it with its state and owning environment. Present ALL of those details to the user verbatim. 2. Only after the user explicitly approves decommissioning that specific server, call again with confirm:true and server set to the exact 24-char hex ID from step 1 (hostnames are not accepted with confirm — the ID binds the action to what the user approved). Never set confirm:true unless the user has just approved this exact decommission; a general instruction like "scale down the cluster" is not sufficient.
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    Destructive
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  • Check whether one SaaS or cloud vendor (e.g. Stripe) is down right now: current status, confidence, active incidents, 30-day uptime and how fresh the data is, read live from PulseWatch. Use it for one vendor; use multi_vendor_status for up to 25 vendors at a flat price. Call list_vendors (free) first if you are not sure the vendor is tracked: unknown vendors return an error and are not charged. Read-only. Costs $0.01 USDC per call via x402 (payment goes in _meta["x402/payment"]); invalid input or an upstream failure is not charged.
    ConnectorNo auth
  • Score one planned payment and return approve, ask_human, or block before any tool sends money. Use before a crypto transfer, gift card, subscription, or paid API call. Do not use it for uptime (check_mcp_server_health, check_api_status), to judge whether a host or wallet is trusted (check_merchant), or to read remaining free scores (get_quota). Does not transfer funds. Returns score 0-100, verdict (approve means pay, ask_human means stop and ask a person, block means do not pay), reasons, and recommended_action. Scoring is deterministic, so rewording purpose will not change the verdict. amount is USD, not token units. api_key, when set, is a SpendGate sg_live_ key, not a Toolweather tw_ key from get_api_key. Uses SpendGate's quota (100/day anonymous, 1,000/day with an sg_live_ key), then $0.001 via x402, not the Toolweather check quota.
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  • Record the latest value of a Lock Screen Widget metric, identified by its key. Use it whenever the tracked number or text changes, such as new revenue, signups, or uptime. The value replaces the previous one. Widgets on the user's Lock Screen pick it up on their next refresh, about every 15 minutes, so it is not instant; for an immediate alert, use send_push_notification. If no metric uses the key yet, this creates one with a label made from the key, in number format for numeric values and string format for text; call create_widget_metric first for a currency, percent, or unit format or a custom label. Keys of deleted metrics are not recreated. Each successful call counts as a billable metric update and returns a billing error when the account's trial or plan does not allow more. Returns the metric with its new latest value and created: true when this call created it.
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  • Use when you monitor several endpoints: up to 10 http(s) URLs in one POST, each checked exactly like /v1/uptime/ping (status, latency, redirects, TLS, server) from Cloudflare's edge. Returns the exact paid x402 request for your input (POST /v1/uptime/ping/batch, $0.10 per call), with the response schema and an example; POST that JSON body to the URL with an x402 or MPP client to get the data. Bad input is refused before any charge. For one URL use url_uptime_ping. With a P0 access key (header Authorization: Bearer p0k_…, buy one at https://x402-bazaar-rank.x402-bazaar-rank-worker.workers.dev/keys/buy?usd=5) this tool makes the paid call itself and returns the data, deducting the listed price.
    ConnectorNo auth
  • Use when you monitor several endpoints: up to 10 http(s) URLs in one POST, each checked exactly like /v1/uptime/ping (status, latency, redirects, TLS, server) from Cloudflare's edge. Returns the exact paid x402 request for your input (POST /v1/uptime/ping/batch, $0.10 per call), with the response schema and an example; POST that JSON body to the URL with an x402 or MPP client to get the data. Bad input is refused before any charge. For one URL use url_uptime_ping. With a P0 access key (header Authorization: Bearer p0k_…, buy one at https://x402-bazaar-rank.x402-bazaar-rank-worker.workers.dev/keys/buy?usd=5) this tool makes the paid call itself and returns the data, deducting the listed price.
    ConnectorNo auth