"Tools and strategies commonly used in coding" matching MCP tools:

• percentage_calcA

  calc.engineerA

  Calculate what percentage one number is of another. Given a value and a total, returns the percentage, decimal form, and simplified fraction. For example, 3 out of 4 yields 75%, 0.75, and '3/4'. Commonly used for test scores, survey results, financial ratios, completion rates, and unit conversions. Chain with percentage_increase to compare successive measurements or use with test_grade for academic scoring.

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• get_my_strategiesA

  Sentinel AlephA

  Lists the saved strategies on the API key's account, newest first, archived ones included (active false): id, mode, engines, minimum confidence, direction and symbols. Use it to pick the strategy_id that run_backtest, update_strategy and delete_strategy take; for live bot activity use get_my_bots. Archived strategies count toward limit, and there is no paging: a strategy beyond the newest limit is read by its id with get_strategy; an account without strategies gets an empty list. An empty symbols list means any pair, so run_backtest then needs symbol. Needs an API key (without one the call is refused with 401) and spends 1 read unit of the daily quota; read only.

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• flipr_opportunityA

  flipr-x402A

  Analyze current Flipr.bet opportunity before deciding to flip. Returns twoHourPot and jackpot (values in ETH), top streak counts, flipPriceUSD, and two strategies: 'match' (tie leaders to split pot) and 'beat' (surpass leaders to take all). Each strategy shows expected cost in ETH, number of flips needed, and ROI. ROI > 1.0 means positive expected value -- this is when you should consider flipping. Pots are in ETH; flip cost is paid in USDC via x402. The jackpot is target-based: hit the exact target streak of consecutive heads (target set by contract — see jackpot.targetStreak in this response) to win 80% of the jackpot pot. Funded by a portion of flip fees. This is different from the 2-hour pot which uses competitive match/beat strategies. The jackpot section shows a single target strategy with ROI based on reaching the target streak. Call this FIRST before using flipr_flip. FREE — rate-limited only. [pricing: {"cost":"0","currency":"FREE","type":"free","network":"eip155:8453"}]

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• get_integration_guideA

  TestMyVibesA

  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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• compare_backtestsA

  Backtest360A

  Run several strategies on the same data and compare side by side. One quota-counted call, but compute scales with the number of strategies. If the wall-clock compute budget is exceeded, the call fails with a tool error (504) instead of returning partial results — narrow the request (fewer strategies, shorter date range, coarser frequency) and retry. Args: data_source: Shared data source (same shape as run_backtest). strategies: List of {"label": str, "strategy": {...}, "execution": {...}?} entries. Labels need not be unique or id-safe — they are echoed back verbatim in the result. include_benchmark: Add a buy-and-hold benchmark to the comparison. response_detail: Shaping level applied to each strategy's result. trades_limit: Max trades per strategy when detail is 'full'. Returns: {"strategies": [{"label", "result"}, ...], "equity_curves": {...}, "alignment"?}, each result shaped at the requested detail. When a benchmark is included, non-benchmark entries also carry "relative" (beta, alpha, information ratio, etc.). A 400/422 rejection returns {"accepted": false, "error": ...}; capacity/timeout/permission failures raise a tool error.

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• arena_compare_strategiesA

  Backtesting ArenaA

  Which of these strategies performed best on the same data? Run 2–5 strategies against the SAME pair, interval and date range and return per-strategy metrics plus a comparison summary (best by CAGR, best by win-rate, worst by drawdown). Use this when the user asks which of several strategies fits a market — it holds the pair, interval and requested date range fixed, which a series of separate arena_run_backtest calls does not guarantee. What it does NOT equalize is the EVALUATION window: a strategy with a long warmup starts trading later, so compare actual_date_from across the runs and check result.benchmark before ranking by CAGR. For one strategy across many pairs use arena_run_universe_backtest instead. Caveat worth passing on: comparing N strategies and reporting the winner IS multiple testing — the winner’s edge is upward-biased. arena_get_robustness_field puts a counted N on that. Sequential, expect 10–50s. Per-day quota: Pro=20, Power=200. [API Pro tier]

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• adidas_product_review_topicsA

  Crawlora MCPC

  Adidas review topics for one product model: the topics its customer reviews can be filtered by, commonly satisfaction, comfort, color, purchase, fit, appearance, quality and style. Feed a topics[].topic value back to adidas_product_reviews as its topic argument to read only the reviews about that aspect. The vocabulary is per model rather than a fixed list, so read it per model instead of hard-coding it. model_number is the Adidas model number (e.g. SAMBAU2312) from an adidas_search result's products[].model_number field -- NOT the SKU in products[].id. A model with no reviews, including an unrecognized model_number, returns an empty list rather than an error. The label field is a display form of topic, not translated text: Adidas returns the same English values for every locale here.

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• adidas_product_review_topicsA

  Crawlora MCPB

  Adidas review topics for one product model: the topics its customer reviews can be filtered by, commonly satisfaction, comfort, color, purchase, fit, appearance, quality and style. Feed a topics[].topic value back to adidas_product_reviews as its topic argument to read only the reviews about that aspect. The vocabulary is per model rather than a fixed list, so read it per model instead of hard-coding it. model_number is the Adidas model number (e.g. SAMBAU2312) from an adidas_search result's products[].model_number field -- NOT the SKU in products[].id. A model with no reviews, including an unrecognized model_number, returns an empty list rather than an error. The label field is a display form of topic, not translated text: Adidas returns the same English values for every locale here.

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• axiorank_list_agentsA

  AxioRank: Zero-Trust for AI AgentsA

  List the active agents in your AxioRank workspace (id, name, labels, quarantine + last-used status). Use this to find an agent's id before calling agent-specific tools. Requires the `agents:read` scope.

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• list_payment_methodsA

  agentcardA

  List the saved payment methods (used only to pay for flight bookings, not for cards or adding funds). Returns each method with its id, brand, last 4 digits, and expiry, and marks the default one. Use setup_payment_method to add a new one. The gated tools set_default_payment_method and remove_payment_method also exist; call them by name even though they aren't in the tools list.

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• tld_lookupA

  Agent BitsA

  Identify what a DNS top-level domain such as com, io, or ai is classified as and commonly used for when classifying domains or answering TLD questions. Use when: - What kind of TLD is .io? - Is .ai a country-code or generic top-level domain? - Get curated metadata for DNS TLD com Do not use when: - Check whether a full domain name is registered or available - Resolve DNS records or WHOIS ownership - Look up MIME types for file extensions (use mime_lookup)

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• tld_lookupA

  Agent BitsA

  Identify what a DNS top-level domain such as com, io, or ai is classified as and commonly used for when classifying domains or answering TLD questions. Use when: - What kind of TLD is .io? - Is .ai a country-code or generic top-level domain? - Get curated metadata for DNS TLD com Do not use when: - Check whether a full domain name is registered or available - Resolve DNS records or WHOIS ownership - Look up MIME types for file extensions (use mime_lookup)

  ConnectorNo auth

• listBookingsA

  MAQAMI TravelB

  Find a customer's hotel bookings by the email address and last name used to book. Both must match the booking holder; nothing is returned otherwise. Returns each booking with its `bookingId`, status, hotel, dates, guests, price and cancellation policy. To look up, change or cancel one booking, use its `bookingId` with the same `email` in the booking tools.

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• set_strategy_publicationA

  LightbringerA

  Publishes a strategy or returns it to draft on explicit user request. Published strategies become organisation-wide context for members and Lightbringer agents, including existing competitor monitoring. Publication does not schedule or start monitoring. Multiple strategies may be published simultaneously. Requires strategy management rights.

  Connector

  Destructive

  OAuth

• listBookingsA

  MAQAMI TravelB

  Find a customer's hotel bookings by the email address and last name used to book. Both must match the booking holder; nothing is returned otherwise. Returns each booking with its `bookingId`, status, hotel, dates, guests, price and cancellation policy. To look up, change or cancel one booking, use its `bookingId` with the same `email` in the booking tools.

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• polish_and_proveA

  StandoutA

  THE PRIMARY STANDOUT WORKFLOW. Use this when a user wants an AI-built website made client-ready without choosing individual design tools. First call: pass url (best), source, or business. Standout captures the baseline, scores the real phone and desktop render, chooses a coherent direction, and returns the exact implementation contract for the coding agent. The agent MUST apply the fixes in the repository. Final call: pass the original url/source plus after_url/after_source. Standout compares both versions and produces a client-safe before-and-after report and share link. Do not stop after returning advice; the completed outcome is fix, rerender, prove.

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• GetAverageTrueRangeA

  EquiblesA

  Average True Range (ATR) for a stock. Wilder's volatility measure built from the True Range (max of high-low, |high-prev_close|, |low-prev_close|) and smoothed recursively. Higher ATR means wider daily moves; commonly used for position sizing and stop placement. ATR is denominated in the stock's price units (USD). The smoothing is warmed up on price history fetched before startDate, so values do not depend on the requested range's left edge.

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• get_top_trading_strategiesA

  Helium MCP Server - News, Markets & AIA

  Get the top-ranked short volatility and long volatility option trading strategies. Returns two ranked lists — short_volatility (sell premium / theta strategies) and long_volatility (buy premium / gamma strategies) — each containing up to `limit` tickers. Each entry has the same fields as get_ticker: - ticker, name, latest_price, page_url - bullish_case, bearish_case, potential_outcomes, takeaway, analysis_date (AI-generated, when available) - price_forecast_days, price_forecast_percent, price_forecast_lower/upper_bound_percent (when available) - iv_rank_percentile (0-100, IV rank over past year, when available) - short_vol_call, short_vol_put: best short volatility option packs (when available) - long_vol_call, long_vol_put: best long volatility option packs (when available) Sort options: - "helium_rank" (default): Helium AI edge score — best overall expected value - "odds_of_profit": Highest probability of profit - "historical_performance": Best annualized historical P&L across backtested trades - "reward_to_risk": Best reward-to-risk ratio - "smallest_max_loss": Strategies with the smallest maximum possible loss Args: sort: Ranking method (default "helium_rank"). One of: 'helium_rank', 'odds_of_profit', 'historical_performance', 'reward_to_risk', 'smallest_max_loss'. limit: Number of results per strategy type (1-20, default 5).

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• export_backtestA

  Backtest360A

  Export a multi-strategy comparison as an Excel workbook. Quota-counted; needs a key whose plan includes full-metrics export (a 403 means the configured key's plan does not — do not retry). Returns the workbook base64-encoded — decode and write it to a ``.xlsx`` file. Args: data_source: Shared data source (same shape as run_backtest). strategies: Same shape as compare_backtests' ``strategies``. include_benchmark: Add a buy-and-hold benchmark to the export. Returns: {"filename", "content_type", "size_bytes", "content_base64"}. A 400/422 rejection returns {"accepted": false, "error": ...}; capacity/timeout/permission failures raise a tool error. If the encoded workbook would exceed the output size limit, raises a tool error — narrow the request (shorter date range, fewer strategies, coarser frequency) and retry.

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• list_recovery_strategiesA

  Wellness ProjectA

  List the user's recovery and mindfulness strategies. Use when the user asks about their recovery practices, mindfulness routines, or you need strategy IDs before logging a session. INFER — do not ask: - filter: default to 'active'; use 'all' for history; use 'historical' for ended strategies only. Returns each strategy's id, name, category, schedule, start_date, and end_date.

  ConnectorOAuth

• dreamagent_list_superpowersA

  DreamAgent CloudA

  List DreamAgent Superpowers — the account's ready-made AI tools (song/video/image generation, voiceover, lip sync, voice clone, transcription, media processing, PDF tools) with their enabled state and beta pricing. Read-only; no credits consumed. Use when the user asks what AI tools/superpowers are available, whether a specific tool is enabled, or what they can add to a project. Tools shown as enabled can be used from ANY of the user's projects through dreamagent_chat (just ask in the message).

  ConnectorNo auth