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524,366 tools. Updated 2026-09-06 15:15

"Coding in Python and R" matching MCP tools:

  • Current chain-control requirements on California mountain highways. Data: Caltrans chain-control status for fixed checkpoints on mountain routes (I-80 Donner, US-50 Echo Summit, SR-88, SR-89, and others). Levels: R-1 = chains OR snow tires required; R-2 = chains required except 4WD/AWD with snow tires on all four; R-3 = chains on ALL vehicles (rare, usually precedes closure). Refresh: 5-minute cache. Filters: route (e.g. "80", "US-50", "SR-88"); center "lat,lon" with radius_km for all checkpoints around a place (e.g. around Truckee), whatever highway they are on. Off-season (roughly May-October) there are usually no controls anywhere; the response says so explicitly rather than returning an empty list. Chain requirements can change hour to hour in storms - tell the user the data_as_of time and to carry chains anyway when snow is possible.
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  • Lista serviços oferecidos pela ER+ ALÉM dos cursos regulares: 'demo' (gravação de demo profissional com Ruy, R$ 350), 'mentoria' (mentoria 1:1 com Ruy, R$ 250/h), 'b2b' (treinamentos corporativos pra empresas). Use quando aluno perguntar sobre demo, mentoria, treinamento empresarial. Pra cursos regulares, use list_courses.
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  • Produce a focused pull-request review checklist for a language or stack. FREE. Covers the things that actually break in production, with extra items per language. Typical input {"language": "python"} returns {"language": "python", "checklist": ["...", ...], "note": "..."}. Use before a review, to decide what to look for. Not for reviewing actual code - pass code to review_diff or security_deep_dive. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
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  • Simulate long-term compound interest growth for retirement portfolios, 401(k)s, Roth IRAs, UK ISAs, or European ETF savings plans (Sparplan) with recurring monthly deposits. Behavior: Deterministic, idempotent calculation with zero external side effects. Applies discrete compound interest formula with periodic annuity deposits: Future Value = P*(1 + r/n)^(n*t) + PMT*(((1 + r/n)^(n*t) - 1)/(r/n)). Returns final accumulated balance, total principal contributed, total compound interest earned, and annual wealth progression milestone table. Usage Guidelines: Use for multi-year personal wealth projection and retirement nest-egg simulations. Do not use for Indian mutual fund monthly SIPs with annual step-up; use sip_investment instead.
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  • Calculate reducing-balance monthly Equated Monthly Installment (EMI), total interest payable, and amortization schedule for home, auto, or personal loans. Behavior: Deterministic, idempotent calculation with zero external side effects. Computes standard monthly EMI formula: E = P * r * (1 + r)^n / ((1 + r)^n - 1), where r = annualRate / 12 / 100. Returns monthly EMI, total payment (principal + interest), total interest percentage, and first-year amortization breakdown. Usage Guidelines: Use for general global reducing-balance loans and consumer debt. Do not use for US residential mortgages requiring property tax, hazard insurance, and PMI escrow; use mortgage_piti instead.
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  • Validates a Python automation script that runs OUTSIDE the game, on three axes: Python syntax (using the real interpreter), Minecraft commands embedded in the script (against the official command index), and the shape of the /connect WebSocket message envelope. For behavior pack scripts use validate_script instead — Python does not run inside a pack. The embedded command check is the most valuable one: a command written from memory can look syntactically fine and still do nothing in the game. Only strings starting with / are treated as commands. If syntax could not be checked, syntaxChecked is false in the result; ok:true alone does not mean the syntax is valid.
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  • Authoritative ICD-10 → ICD-11 mapping using WHO transition tables (release 2025-01, bundled with the server). Returns the primary 1:1 ICD-11 category for the ICD-10 code plus any alternative ICD-11 candidates that WHO documents (some ICD-10 concepts split into multiple ICD-11 entities). For each mapping, includes the ICD-11 code, title, chapter, and the Foundation URI / Linearization URI for navigating to the full entity definition. Use this for clinical coding, billing migration, retrospective analysis, and any workflow that needs authoritative mapping rather than text-search candidates. Coverage: 11,243 ICD-10 categories (excludes chapters and blocks like "A00-A09" which aren't used in clinical coding). Provide a code like "E11" (Type 2 diabetes), "I21" (Acute MI), or "A07.8" (4 alternatives in WHO's table). Both dotted ("A07.8") and undotted ("A078") forms are accepted. Returns "no mapping" when the code isn't in the WHO category-level table — that's the honest answer rather than a fuzzy search fallback.
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  • [JOURNAL] Amend an OPEN journal trade by trade_id: move your stop or target, fix size_usd / leverage / thesis. A stop MOVE changes only the current stop (what the watchdog and close-time touch scan use); realized R stays measured against your INITIAL stop, so trailing to breakeven can't inflate R. To fix a genuine fat-finger in the original entry or stop, also pass correct_entry=true — that resets the R basis (disclosed in the response). asset/side can't be amended — void and re-log for that. Pro.
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  • Returns the canonical guide for using TMV from a coding-agent context. Covers the fix-test-retest loop, how to write a good test prompt, how to read the actionTrail / consoleErrors / failedRequests outputs, and common gotchas. Call this first if you're a new agent on a project — it'll save you a debug session. The same content is served at https://testmyvibes.com/docs/coding-agents.
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  • Get a multi-year capital allocation breakdown for a US public company. Shows how management deploys cash across all six categories — capex, R&D, M&A, dividends, buybacks, and debt — plus pre-computed deployment ratios (% of operating cash flow) and over-distribution flags. Use this tool when the user asks: how does a company allocate capital, what's the buyback-vs-dividend mix, is the company over-distributing, is growth funded by R&D or M&A, what's the cash-return-ratio trend, or any 'where does the money go' question — including owner-earnings (Buffett-style) and reinvestment-rate (Damodaran-style) analysis. Data sourced from annual 10-K filings; PIT-safe via as_of_date. R&D is included as a deployment category (the primary growth-reinvestment vehicle for knowledge-economy firms), but since it's already deducted before operating cash flow, `rd_pct_ocf` is INFORMATIONAL and `total_deployment_pct_ocf` EXCLUDES R&D to preserve the cash-flow identity (OCF = capex + M&A + dividends + buybacks + debt repayment + Δcash). The `flags` object carries pre-computed booleans: `buybacks_exceed_fcf`, `total_returns_exceed_fcf` (buybacks + dividends > FCF), and `debt_funded_distribution` (over-distribution funded by leverage vs cash). Available on all plans.
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  • Calculates LoRa packet time-on-air using the Semtech AN1200.13 formula. Computes symbol duration, preamble time, payload symbol count, effective data rate, and the minimum transmission interval for 1% duty cycle compliance. Essential for capacity planning in LoRaWAN and Meshtastic mesh networks. Accepts spreading factor (SF7-SF12), bandwidth (125/250/500 kHz), coding rate (4/5-4/8), payload size, header mode, CRC, and optional low data rate optimization. Feeds airtime_ms to channel_utilization for mesh load analysis.
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  • Get the realised track record: win-rate + R-multiple distribution. Aggregates actual closed outcomes (tp_hit, trail_stop_hit, stop_hit, position_closed) into an honest scorecard — win_rate, wins/losses, and the realised-R distribution (mean/median/min/max/total). Pass a ticker for its per-ticker record; omit it (or pass "") for the portfolio-wide record. HONESTY: small samples are flagged `illustrative: true` with an explanatory `note`, and `win_rate` is null when no closed P&L exists. Never present an illustrative record as a reliable hit-rate. Every number is grounded in stored outcome events — none are fabricated. This is the ground-truth check on signal quality: a high stated R:R only holds if the realised-R mean is positive and the stop-hit rate is low. Args: ticker: Stock ticker (e.g. "AAPL"), or "" for portfolio-wide. Returns a dict with scope, sample_size, win_rate, realised_r, and note.
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  • Liefert in 'focus' alle Angaben zu einem ICD-10-GM-Kode: Kodier-Kennzeichen, Inklusiva/Exklusiva und Kodierhinweise, Einträge des Alphabetischen Verzeichnisses, zugeordnete ATC-Wirkstoffe, Morbi-RSA-Gruppen sowie DKR- und SEG-4-Verweise. Dazu in 'parents' die übergeordneten Kodes und in 'items' die direkt untergeordneten. Ohne Kode aufgerufen liefert die Funktion die oberste Ebene, sodass sich der Katalog Ebene für Ebene durchlaufen lässt. [EN] Everything about one ICD-10-GM code: coding flags, inclusions, exclusions, coding notes, alphabetical index entries, cross-references, parent and child codes. Call it after a search to inspect a hit; call it without a code to browse the catalog from the top.
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  • [JOURNAL] Read your private trade journal. status=open|closed|void|all (default all shows open+closed; void is hidden unless asked), limit for history (default 20). Open trades include live unrealized PnL/R and a warning if your stop level has traded since entry. Closed trades include resolved outcomes (ret %, R, MAE/MFE). stats block = personal calibration: win rate and realized R per n0brains entry grade — where your entries were actually good. Pro.
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  • Trace the beneficial ownership chain for any legal entity up to 3 levels deep using GLEIF relationship records, then screen every node in the chain against the OpenSanctions consolidated sanctions list (OFAC SDN, EU, UN, UK OFSI). Returns chain structure (SUBJECT → DIRECT_PARENT → ULTIMATE_PARENT), per-node sanctions status, LEI lapse flags, overall CLEAR / REVIEW_REQUIRED / BLOCKED verdict, and FATF R.16 beneficial ownership compliance attestation. Required for correspondent banking due diligence, FATF R.12/13 UBO identification, and MiCA Article 72 counterparty risk management.
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  • Find which documentation SETS exist whose NAME matches a substring (e.g. "python" → Python 3.x, "react" → React). Returns doc SETS, NOT their content — this does NOT look up a function/method/API name. To search inside a doc for an entry like "Array.map" or "fetch", use search_index (slug + query).
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  • Get posts from a REDDIT subreddit — r/LocalLLaMA, r/python, r/news. PREFER for "what are people posting in r/<sub>", "whats new on r/<sub> today", "top posts on Reddit this week". Sorted hot (default), new, top, rising, or controversial. For "top"/"controversial" pass a time window (day/week/month/year/all) — e.g. "top posts in r/programming this week". Returns post id, title, author, permalink, date, and a body snippet. (Vote score and comment count are not available via Reddit RSS.)
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  • [JOURNAL] Read your private trade journal. status=open|closed|void|all (default all shows open+closed; void is hidden unless asked), limit for history (default 20). Open trades include live unrealized PnL/R and a warning if your stop level has traded since entry. Closed trades include resolved outcomes (ret %, R, MAE/MFE). stats block = personal calibration: win rate and realized R per n0brains entry grade — where your entries were actually good. Pro.
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  • Retrieve one UK NIHR award in full by its project id (either the modern form NIHR208893 or the older slash form 002/0028). Returns the plain-English abstract and the scientific abstract, award value in GBP, programme, funding stream and status, start and end dates, the contracted organisation with postcode and latitude/longitude, HRCS and UKCRC health-category coding, the fundingawards.nihr.ac.uk record link, and every named award holder with their ORCID and role. Use when an agent has an NIHR project reference and needs the detail behind it.
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  • Raio-X cadastral 360º de uma PESSOA (por CPF) OU EMPRESA (por CNPJ) — consolidado num relatório por seção. PF: identidade, contato/localização, dinheiro a receber (Valores a Receber do BC, IRPF, benefícios), crédito, antecedentes/sanções, societário, veículos e processos. PJ: cadastro/Simples, regularidade fiscal (CND Federal, CNDT, FGTS), dinheiro a receber, crédito PJ, SINTEGRA/TCU, QSA/societário, idoneidade (CEIS/CNEP/CEPIM/leniência) e processos. Informe `cpf` (pessoa) OU `cnpj` (empresa). Escolha o `nivel`: **basico** (R$39: identidade + dinheiro a receber), **medio** (R$149: + crédito + antecedentes + veículos), **avancado** (R$249: + societário + sanções internacionais + processos). Preço FIXO por consulta (pré-pago). TEMPO: basico ~15s, medio ~30-60s, avancado consulta muitas fontes e é o mais demorado (pode chegar perto do limite de tempo do cliente MCP; avise o usuário que a consulta pode demorar ~1 minuto). SCR e relatórios de crédito positivo (dados sob sigilo/autorização) só entram se `autorizacao_titular_scr=true` e são cobrados À PARTE, por cima do nível (SCR +R$39, relatório positivo PF +R$140, limite PJ +R$210, risco PJ +R$140). Confirme ANTES com o usuário que ele tem autorização declarada do titular; sem isso, esses itens são pulados. RESPOSTA: por padrão devolve um RESUMO (status de cada fonte + destaques) mais um arquivo .md com o dossiê completo, que você abre por seção com `arquivo_ler`. O dossiê inteiro passa de 100 mil tokens, por isso não volta na resposta. Use `formato="completo"` só pra consumo programático. Os dados podem estar incompletos/desatualizados e não substituem a consulta oficial (LGPD).
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  • Compute Ordinary Least Squares (OLS) bivariate linear regression best-fit trend line (y = m*x + c), Pearson correlation coefficient (r), and coefficient of determination (R^2). Behavior: Deterministic, idempotent calculation with zero external side effects. Evaluates sample means, covariance, and variances to solve slope m = Cov(X,Y) / Var(X) and intercept c = mean(Y) - m*mean(X). Computes Pearson r, R^2, standard error of estimate, and generates predicted y-values for each input x. Usage Guidelines: Use for trend forecasting, scientific scatter data fitting, and correlation analysis. Do not use for solving analytical quadratic or linear systems; use casio_991_solve instead.
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