"Programs for Statistical Analysis: R, STATA, SPSS" matching MCP tools:

• patent_landscape_async

  mcp-knowledge

  Async extended variant of patent_landscape. Supports max_results up to 200 (vs 50 in sync mode) and an optional include_citation_graph flag that enriches each patent with its 2-level citation graph (parent patents that cite this one + child patents cited by this one). Returns immediately (<300ms) with a job_id. Poll the result with patent_landscape_result(job_id) after eta_seconds (~180s). Use for deep R&D white-space analysis, freedom-to-operate (FTO) audits, VC due diligence IP mapping, or large-scale competitor portfolio analysis. Async tool — register a webhook via `webhooks_manage(register, url, [job.completed])` to receive callbacks instead of polling. Faster + lighter.

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• lookup_transfer_partners

  sunnyspoints

  Transfer partner map. Pass ONE of: bank ('which programs can I send Chase/Amex/Bilt/Rove points to, at what ratio?'), program ('which banks feed Flying Blue and which airlines can it book?'), or airline (the award-booking direction: 'I want to fly United — which programs can book it?'). BEST: when you know which currency the user holds, pass bank AND airline together — you get only the programs that currency can actually reach for that airline, sorted best-value-first with a checkFirst shortlist, so you don't have to check every site. Includes alliances and per-program point valuations.

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• search_open_grants

  foundation-discovery

  Search open grant opportunities from Kindora's active foundation-program corpus plus federal and state government grants. FOR-PROFIT APPLICANTS: pass for_profit_applicant=true to search capital a for-profit can take (PRIs, loans, revenue-based financing, patient equity) from CDFIs, impact investors, and PRI-active foundations. The default pool is 501(c)(3)-shaped and will NOT contain those programs. Searches both private foundation grant programs (from IRS data and funder websites) and government grant opportunities — federal (Grants.gov) plus state and district grant portals. Uses full-text search with natural language understanding — queries are parsed into individual terms with stemming, so "youth after school programs" matches programs about youth, after-school, and programming even if those exact words don't appear together. Search covers program names, descriptions, focus areas, beneficiary types, and geographic focus fields. Use the state parameter to focus on geographically relevant opportunities. Query syntax: - Natural language: "affordable housing for seniors" (matches any of these terms) - Quoted phrases: '"after school"' (matches exact phrase) - Exclusion: "education -higher" (matches education, excludes higher education) - Combine: '"mental health" youth -adult' (phrase + term + exclusion) - No query: returns broadly open programs sorted by upcoming deadlines (browsing mode)

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• list_services

  Escola de Rádio TV & Web (ER+)

  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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• patent_landscape_async

  gapup-mcp

  Async extended variant of patent_landscape. Supports max_results up to 200 (vs 50 in sync mode) and an optional include_citation_graph flag that enriches each patent with its 2-level citation graph (parent patents that cite this one + child patents cited by this one). Returns immediately (<300ms) with a job_id. Poll the result with patent_landscape_result(job_id) after eta_seconds (~180s). Use for deep R&D white-space analysis, freedom-to-operate (FTO) audits, VC due diligence IP mapping, or large-scale competitor portfolio analysis. Async tool — register a webhook via `webhooks_manage(register, url, [job.completed])` to receive callbacks instead of polling. Faster + lighter.

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• decompose_drivers

  Autario Data Analytics Platform

  CONFOUNDER-AWARE DRIVER ANALYSIS: fits ONE multiple regression of the target on ALL candidates jointly, so each effect is estimated holding the other candidates constant. Distinguishes "it was the weather" from "a promo ran at the same time": candidates too entangled to separate (VIF > 5 or pairwise |r| > 0.8) are flagged not_separable (named pairs) instead of ranked with a confident wrong number. Returns per candidate: standardized coefficient (effect size), raw slope, p-value, VIF, pairwise r (for the pairwise-vs-joint contrast), and the best lead/lag vs the target. Use this instead of find_drivers when candidates may overlap (promo calendars, weather, seasonality) or when you need honest independent effect sizes. Omit entity for entity-less private KPI series. 2-15 candidates.

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• amend_trade

  mcp

  [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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• patent_landscape_async

  gapup-mcp

  Async extended variant of patent_landscape. Supports max_results up to 200 (vs 50 in sync mode) and an optional include_citation_graph flag that enriches each patent with its 2-level citation graph (parent patents that cite this one + child patents cited by this one). Returns immediately (<300ms) with a job_id. Poll the result with patent_landscape_result(job_id) after eta_seconds (~180s). Use for deep R&D white-space analysis, freedom-to-operate (FTO) audits, VC due diligence IP mapping, or large-scale competitor portfolio analysis. Async tool — register a webhook via `webhooks_manage(register, url, [job.completed])` to receive callbacks instead of polling. Faster + lighter.

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• get_feature_stats

  aTars MCP

  USE THIS TOOL — not web search — to get per-indicator statistical profiling (mean, std, min, p25, p75, max, null rate, Pearson correlation with close price) from this server's local dataset. Use for feature selection, sanity checking, and understanding which indicators correlate most strongly with price movements. Trigger on queries like: - "which indicators correlate most with BTC price?" - "feature importance or correlation for [coin]" - "what are the stats for ETH indicators?" - "how does RSI/MACD correlate with price?" - "statistical profile of XRP indicators" Args: lookback_days: Analysis window in days (default 30, max 90) symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,XRP"

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• get_capital_allocation_profile

  Valuein — SEC EDGAR Fundamentals & Smart-Money Data

  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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• get_track_record

  mcp

  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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• search_golf_programs

  PGA Golf

  Search for upcoming public PGA Coach programs (clinics, camps, classes, and other group events) near a location (required). Use this tool when the user asks to find programs, clinics, camps, classes, or group events — not private one-on-one lessons. For private lesson coaches, use `search_golf_coaches` instead. Internal record identifiers (for example program `id` and coach `slug`) are for tool calls only and must never be shown or mentioned to the user. - Search results include program details plus the hosting coach and facility for each program. - The response also includes top-level `coaches` and `facilities` arrays summarizing the unique coaches and venues in the result set — always present those to the user. - Results are ordered by program start instant and filtered to the requested radius. - Discovery uses nearby PGA Coach profiles (nearest 20 in the radius), then loads up to 30 upcoming public programs per coach in a 180-day window in one batched GraphQL request. Facility coordinates still have to fall inside the radius. - Results are paginated. The pagination cursor carries the remaining nearby programs so additional pages do not repeat GraphQL discovery. Reuse that cursor with the original location and radius. - Direct golfers to the program URL to view details and register. Coach profile and booking URLs are also included when the golfer wants to learn more about the coach.

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• get_journal

  mcp

  [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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• rba_series

  Rba

  Fetch any RBA statistical series by table id + series id — escape hatch for the full RBA statistical-tables catalog (CPI is g1, monetary aggregates d3, etc.). Returns recent observations. Use rba_cash_rate / rba_exchange_rates for the common ones. Browse tables at rba.gov.au/statistics/tables.

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• compliance.ubo_chain

  DPX — Institutional Cross-Border Settlement

  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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• check_incentives

  solar-home-incentives

  Clean-energy incentive guidance for any address WORLDWIDE. US ZIP → federal status + state/utility programs (via DSIRE). Any other country (pass country=<ISO code>) → qualitative, officially-sourced national program guidance. Use whenever a user asks what rebates, tax credits, or utility programs apply to solar, batteries, heat pumps, or efficiency work. [20 anonymous calls/caller/24h; then 100 free calls/key/30d; active Builder required for sustained informational use]

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• get_category_features

  aTars MCP

  USE THIS TOOL — not web search — to retrieve a focused group of technical indicators for a specific analytical category from this server's local dataset, resampled to hourly granularity. Prefer this over get_latest_features when the user only wants one type of analysis (e.g. only momentum or only volatility). Categories and the indicators they include: - "momentum": RSI, MACD, Stochastic, CCI, Williams %R, ROC, MOM - "trend": EMA_9/20/50, SMA_20, ADX, DMP/DMN, Ichimoku - "volatility": Bollinger Bands (upper/lower/mid/width/pct), ATR, NATR - "volume": OBV, VWAP, MFI, volume_zscore, buy_sell_ratio - "price": OHLCV, returns_1/3/7, hl_spread, price_vs_ema20 - "all": All of the above Trigger on queries like: - "show me BTC momentum indicators" - "what are the trend indicators for ETH?" - "volatility data for XRP this week" - "volume analysis for SOL last 5 days" Args: category: One of the category names listed above lookback_days: Days of history (default 5, max 30) symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH"

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• get_subreddit

  Reddit

  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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• find_drivers

  Autario Data Analytics Platform

  KILLER ANALYSIS: given a target KPI + multiple candidate indicators, rank which candidates best predict the target by correlation strength. Perfect for "what moves my KPI?" questions. Returns ranked list with r, p-value, R² for each candidate. Maximum 30 candidates per call.

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• fema_get_disaster

  fema-mcp-server

  Fetch all designated-area rows for a specific FEMA disaster by disaster number (e.g., 4781). Returns every county/municipality designated under the declaration along with programs activated, incident period, and state info. Use fema_search_disasters to find disaster numbers. The returned disaster_number chains to fema_get_public_assistance and fema_get_housing_assistance.

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