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744,589 tools. Updated 2026-11-04 23:06

"A resource for finding trading indicators" matching MCP tools:

  • Assess whether an ENS name's sale(s) are WASH TRADING / fake / self-dealt / manipulated volume. THE tool for any "is this wash trading?", "is the sale history of X suspicious/fake/real?", "are these trades legit?", "is someone wash-trading this name?" question — route straight here, do NOT use get_name_details or get_market_activity for that (those return sale rows but make NO wash-trading judgment; only this tool scores it). Just pass `label` — the bare ENS name (e.g. "437", "coffee") is enough; the tool pulls that name's recent sale and analyzes it on demand. `tx_hash`, `buyer`, `seller`, `price_eth` are OPTIONAL enrichment for a specific sale — never block on them or ask the user for them. Returns a wash confidence score (0-1), a label (clean/suspicious/likely_wash), the detected signals (shared-funder, mint-flip, round-trip, fresh-wallet, cluster overlap…), seller profile, and a plain-English summary. A verdict is always ABOUT A SPECIFIC SALE — `sale_analyzed` names it, and `buyer`/`seller` are the parties scored. If the response has `assessable: false` there is NO score and NO verdict: the name has no analyzable sale on record, or the lookup failed. Report that the name could not be assessed and say why. Do NOT describe it as clean, low-risk, or free of red flags, and do NOT describe unrun checks (funding, cluster, round-trip) as having come back negative.
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  • Discover the investment-thesis catalog. Each entry is a descriptive case study that pairs an economic framework with a rule-based portfolio and the synthetic + historical stress evidence for that allocation. Returns one compact summary per thesis (slug, title, one-liner, tags, risk tiers, framework summary, headline finding). Call get_investment_thesis(slug) for the full framework / portfolio / stress evidence, or read the thesis://{slug} resource. Descriptive, not advisory — the agent decides what is suitable.
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  • Use this when the question is whether the site actually WORKS for a keyboard-only or switch-device user — tab order, focus traps, whether the focus ring is visible at all — which no stored scan and no static markup check can answer. Run it before claiming keyboard accessibility for a page, and again after deploying any tab-order, focus or skip-link fix. It tabs through the page the way a keyboard-only user does and reports what breaks: focus traps, elements with no visible focus indicator, focus hidden behind sticky headers, controls that cannot be reached at all, controls that ignore Enter and Space, and tab order that contradicts the visual or document order. Focus indicators are measured by comparing rendered pixels rather than CSS, because indicators come from outline, box-shadow, border and background alike. Findings carry a confidence: the order rules in particular are nudges for a human to confirm, not assertions. A focus-obscured finding names the element doing the covering, once per occluder, and counts distinct covered elements — with stops carrying the tab-stop total when the ring revisits them. A focus-trap finding that may be an open modal behaving correctly says so and says what to check by hand. The response states the viewport the walk was performed in, because the obscured and offscreen results are geometry, and endedBy says which of three things stopped the walk: the ring closing ("ring-closed"), the step ceiling ("max-steps") or the run's time budget ("time-budget"). Only the first means the ring was fully walked. Each finding's selectors array holds up to 5 examples, with count the true total and selectorsTruncated set when more were cut; full: true returns them all from the stored run. A run that lands on a bot-protection interstitial rather than the page is reported as void, never as clean, and a void run carries no stops or findings at all. Where the interstitial title is contradicted by the walk itself, the run stands and carries challengeSuspected instead: trust the walk, not the title. Read-only.
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  • Retrieve one complete prepared resource profile, including evidence-backed facts and primary-source provenance, by its stable resource ID.
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  • Returns the plain-language meaning and step-by-step fix for one Malinois finding. Use it while helping the user fix an issue reported by scan_app, or when they ask what a finding means. Pass the rule_id exactly as scan_app returned it. Read-only, no network, instant.
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  • Get live arrivals for ANY railway station by its EVA number. Mirror of ``station_board_departures`` for arriving trains (all categories, real-time delays, disruption messages). Get the EVA from ``get_city_resource(slug, resource='stations')``. Read-only.
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Matching MCP Servers

  • A
    license
    Not graded
    quality
    C
    maintenance
    Enables AI agents to automate simulated stock trading on the Tonghuashun trading system, including checking account balances and positions, viewing orders and deals, placing market orders, and canceling pending orders via the MCP protocol.
    1
    MIT

Matching MCP Connectors

  • Calculate SMA, EMA, RSI, MACD, Bollinger Bands, ATR, stochastic and VWAP over a price series.

  • Checks the structural integrity of translated resource dictionaries against a source dictionary y...

  • List indicators, or fetch one indicator's full schema. Cheap, cacheable per session. With no arguments: a compact catalog — ``{"indicators": [...], "count": N}`` — where each entry carries id, name, category, kind, and value_dtype (no description, to keep the discovery scan small). Use it to discover what exists. Pass name='rsi' (id or name, case-insensitive) to get that single indicator's complete entry including its description and params_schema — do this before adding an indicator to a strategy so its parameters are exactly right. Pass compact=False for full entries for everything (large; the MCP server may cap it and set ``truncated_by_mcp`` — prefer compact or name=). Wire optimization: the compact discovery path asks the engine to omit per-entry descriptions (``descriptions=false``) since they are stripped locally anyway; the name= and compact=False paths request them. This is a pure saving — if the engine ignores the param it returns full entries and the local compact strip still yields a lean result.
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  • Before deploying ANY accessibility fix, validate it here first — every time, on every rule, not only when you are unsure. It is free, instant, loads no page, and it catches the fix that merely hides the problem from the next scanner. Send the markup you are about to deploy and get a verdict on whether it actually fixes the rule it targets. Four answers: "resolved", "not_resolved" (with what still fails), "masked", or "not_decidable_from_markup". Call it after editing and before deploying, on the rule id and htmlSnippet from list_violations — it reads markup only, so iterating costs nothing against the page allowance. Check the finding's "markupValidatable" first: every list_violations finding carries it, and false means this tool has no markup check for that rule and will refuse it, so the call is wasted. Easiest way to call it: pass "finding" — the findingId from a list_violations entry — and "rule", "before" and the measured colours are filled in from the stored finding for you; anything you pass explicitly wins over them, per field. "masked" is the answer worth having: deleting the element, adding aria-hidden, hiding it with display:none, dropping the visible text or turning a <button> into a <div> all make a scanner go quiet while leaving the barrier in place, so a later re-scan would wrongly agree with you. Never treat it as resolved. Pass "before" whenever you have it — deletion, lost text and downgraded controls are only detectable by comparison. For a contrast rule, pass "colors" — the foreground and background you intend to ship, plus fontSize and fontWeight for large text — and the ratio is computed against the WCAG threshold and answered outright, with the nearest passing foreground when it still fails. Colours declared inline on the markup are read automatically. Without a colour pair contrast stays undecidable, because a fragment has no computed colour. It cannot judge anything else that depends on rendering: focus indicators, forced-colors, reduced motion, tap-target size, reflow at zoom, keyboard traps and reading order all come back "not_decidable_from_markup", naming the tool that can answer them. It also refuses rules it has no check for rather than guessing, so a "resolved" means something. Each markup argument is capped at 100KB; going over is reported, not silently trimmed, and a truncated fix is never called resolved. Read-only — it does not touch the site, the scan history or the findings.
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  • One member of Congress: profile, aggregate trading stats (counts, volume range, average disclosure lag, most-traded tickers), the 20 most recent disclosed trades with links to the original government filing, the member's 5 most recent Periodic Transaction Reports, and the one sample scored trade the public page shows. Use it for 'what has this member been trading'. Get the member_id from search_members first. For more than 20 trades, page list_transactions with the same member_id. Returns a not-found error for an unknown id. Access: needs the agent token from a free Coldpine account, sent as 'Authorization: Bearer <token>'; without it the call returns setup steps instead of data. Read-only, cached for up to an hour.
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  • The latest written summary of the Zensei Index, with the score and regime it was written for. A summary is rewritten only when the indicators change. Check `stale` and `ageDays` before quoting it as today's view, and prefer zensei_index_today for the current number. The Zensei Index is a RISK score from 0 to 100: LOWER IS HEALTHIER. 0-20 Supportive, 20-40 Vulnerable, 40-70 Stressed, 70-100 Restrictive. A rising score means conditions are deteriorating, not improving.
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  • Return the current value of Argentina's headline indicators in one call: USD retail and wholesale (BCRA), blue, MEP and CCL dollars, the blue FX gap, country risk (EMBI), monthly and annual inflation, BADLAR and TAMAR rates and international reserves. Each comes with its date, source, page URL and the change versus 7 days, 30 days (previous month for monthly series) and one year earlier. Use it for "how is the economy doing today" or to compare now against a week, a month or a year ago; use get_series for history, get_projection for the future and get_weekly_summary for the narrative of a closed week. Indicators whose source does not answer are listed under "missing" instead of failing the call. Read-only, no side effects, no authentication. Rate limited to 60 calls per minute per IP. Data updates at most once per business day.
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  • Return the current value of Argentina's headline indicators in one call: USD retail and wholesale (BCRA), blue, MEP and CCL dollars, the blue FX gap, country risk (EMBI), monthly and annual inflation, BADLAR and TAMAR rates and international reserves. Each comes with its date, source, page URL and the change versus 7 days, 30 days (previous month for monthly series) and one year earlier. Use it for "how is the economy doing today" or to compare now against a week, a month or a year ago; use get_series for history, get_projection for the future and get_weekly_summary for the narrative of a closed week. Indicators whose source does not answer are listed under "missing" instead of failing the call. Read-only, no side effects, no authentication. Rate limited to 60 calls per minute per IP. Data updates at most once per business day.
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  • Search Lacuna's ML/AI corpus for papers, research directions, authors, venues, institutions, novel research hypotheses, and research resources (code repositories, datasets, models, and demos linked to papers). For novel ML/AI research ideas, use search_type="hypothesis", then get_hypothesis on promising results. search_type accepts all, cluster, paper, author, institution, venue, hypothesis, or resource. Use paper for literature and get_paper to read a result. Use other sources for biographies, news, and non-research web content. Resources: search_type="resource" searches GitHub repositories, Hugging Face datasets/models, and Zenodo records that Lacuna has linked to at least one paper. To find benchmark or evaluation datasets, use search_type="resource" with resource_kind="dataset" (for example query "image classification benchmark" or a dataset name like "ImageNet"). resource_kind accepts codebase, dataset, model, or demo (one value or a list); provider accepts github, huggingface, or zenodo. Both filters require search_type "resource" or "all" (with either filter set, only resources are returned). Each result has an external `url`, a Lacuna `context_url`, and `linked_paper_count`; call get_resource on its id to list the linked papers (with their relationship to the resource), then get_paper on those papers for reported results and numbers. Resource search does not support date_from/date_to, venue, year sorting, or semantic ranking. ranking_profile accepts: - default / lexical (default): production ranking; relevance-sorted paper searches combine lexical and semantic retrieval when fields is unset. - semantic: conceptual paper retrieval; supported for paper and all. - bm25_title_abstract / bm25: lexical paper matching over those fields. sort accepts relevance (default), year_desc, or year_asc. Semantic ranking cannot use year sorting; constrain recency with date_from/date_to instead. date_from and date_to are inclusive YYYY, YYYY-MM, or YYYY-MM-DD bounds. author_id_or_url constrains a paper search to one author. Pass an author ID or Lacuna author page URL; it requires search_type="paper". fields optionally restricts and weights lexical fields, for example "title^4,abstract". Supported names are title, abstract, summary, concepts, name, top_names, and venue, plus description, topics, provider_key, and paper_titles for resources (a resource's title already includes its description, topics, README text, and linked paper titles). Fields must exist on the selected search_type, weights must be within 0 < weight <= 100, and fields cannot be combined with semantic ranking.
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  • List the built-in technical indicators available for backtesting (RSI, moving-average crossovers, ADX, Bollinger, CCI, Stochastic, and more) with their IDs, parameters with defaults, and each indicator's default long rule. Call this to answer what strategies or indicators can be tested, or before run_backtest when unsure which indicator_id or parameters to use. Takes no arguments. Read-only and static (no market data is fetched, never rate-limited by the live budget). To find portfolios and strategies instead, use list_portfolios.
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  • Run a raw SoQL query against any Los Angeles open-data resource (data.lacity.org) by its Socrata id (8-char like "2nrs-mtv8"). Full SoQL: where/select/group/order/limit/offset. Use la_datasets to find a resource id, or la_recent for the common ones.
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  • Join the waitlist for early access to the Synoptic trading terminal (beta) for the signed-in account. Sets terminalAccessRequested, which get_me reports; repeating the call changes nothing. Does not grant access, open a support ticket or place trades. Use request_feature for other product requests.
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  • Authoritative REST API reference for writing integration code into the user's app. Base URL: https://api.volanea.com — auth is `Authorization: Bearer <secret key>`; sends accept an `Idempotency-Key` header. Use this instead of guessing endpoint shapes or SDK names. THREE MODES, and the default is the expensive one: `{ resource, indexOnly: true }` lists every operation's id, method, path, and one-line summary with NO schemas (a few KB); `{ resource, operations: [ids] }` returns full request/response schemas for just those operations, plus only the schemas they reference; `{ resource }` alone returns the entire resource, which for Campaigns or Contacts is 40-50 KB of one reply. Start with indexOnly, then expand the two or three operations you are actually going to call — every byte of a reference dump re-enters your context on every later turn.
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  • Authoritative REST API reference for writing integration code into the user's app. Base URL: https://api.volanea.com — auth is `Authorization: Bearer <secret key>`; sends accept an `Idempotency-Key` header. Use this instead of guessing endpoint shapes or SDK names. THREE MODES, and the default is the expensive one: `{ resource, indexOnly: true }` lists every operation's id, method, path, and one-line summary with NO schemas (a few KB); `{ resource, operations: [ids] }` returns full request/response schemas for just those operations, plus only the schemas they reference; `{ resource }` alone returns the entire resource, which for Campaigns or Contacts is 40-50 KB of one reply. Start with indexOnly, then expand the two or three operations you are actually going to call — every byte of a reference dump re-enters your context on every later turn.
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  • Lists every entity of one Star Wars resource type as a JSON array (Episodes I-VI data). Responses are large (all 82 PEOPLE, about 38 KB); to find a single entity, prefer sw_search, then sw_get; for a compact index pass fields, e.g. ["name"] (about 5 KB).
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  • List security/safety findings for your workspace, most recent first. Optionally filter by status, target model, minimum severity, or a specific run. Returns a compact summary; call get_finding for the repro detail of any one finding. On a plan that withholds a finding's proof, category reads '[redacted]' and get_finding returns the same — the finding and its severity are real, the evidence is withheld. Paginated: 200 findings per page (max 200). The result carries total_matched and, when there is more, next_cursor: pass it back as 'cursor' with the same filters (it is bound to them) to read the next page, until it is absent.
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  • Read up to200 company credit-pack and subscription payment records for the current UTC calendar month, newest first. Returns payments with reference, kind, amount_minor, currency, credits, status and creation time, plus truncated and not_a_tax_invoice indicators. Use to inspect recorded purchases; skavio_usage measures processing consumption and skavio_wallet the credit ledger. Trial/promotional credits are not cash receipts. Takes no arguments; does not charge, refund, reconcile a payment provider or issue a tax invoice.
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