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

• map_icd10_to_icd11

  Medical Terminologies MCP

  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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• assets.list

  AI Design Blueprint

  Public — list downloadable doctrine and agent asset artifacts (skill packs, rule packs, MCP setup snippets) the user can drop into their AI coding tool to import the Blueprint as native skill/rule files. Returns a list of assets with name, format (one of: zip / md / markdown / mdc / json / toml / text — the full vocabulary), pack_version, download_url, and platform target (Claude Code, Cursor, Codex, Gemini, Qwen). The response also carries `count` (length of `assets`) for symmetry with principles.list / clusters.list / guides.list. WHEN TO CALL: the user asks how to bring the Blueprint into their coding agent, or wants to install it as a local skill/rule file. WHEN NOT TO CALL: for the live MCP tools themselves — those are already available through this server. For doctrine content, prefer principles.list/get and guides.list/get. BEHAVIOR: read-only, idempotent, no auth required. Asset artefacts are regenerated on every deploy from the canonical doctrine.

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• percentage_calc

  calc.engineer

  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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• d365fo_set_connection

  ALM X++ MCP Server

  Securely register the D365 F&O connection (URL + Entra app-registration credentials) for the CURRENT session. The client secret is encrypted in memory (AES-256-GCM), never written to disk and never echoed back. Once set, all odata_* and dmf_* tools use it automatically until it expires or you call d365fo_clear_connection. Use this instead of resending the secret on every call. In a locked server deployment (D365FO_LOCK_SERVER_CONFIG=true) this tool is disabled and the server's own environment credentials are used instead.

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• load_backtesting_workflow

  Shibui Finance

  Backtesting and simulation guardrails: survivorship, drawdown, Sharpe, day-of-week. REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL when the user asks to backtest, simulate, validate a strategy, test "what happens after X", compare forward returns, measure win rates or hit rates, compute Sharpe, drawdown, profit factor, rotation strategies, basket returns, or any hypothetical return over past data. Contains hard rules for survivorship bias, outlier handling, sampling design, day-of-week filters, and risk-adjusted metrics (Sharpe, Sortino, drawdown). Can be combined with other workflow tools.

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• flipr_opportunity

  flipr-x402

  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_strategy

  Heista

  Read a creative strategy in full by its powersource_id. Returns the same brand-merged bundle shape as get_powersource(data) — buyer profile, 12 behavioral tensions, angles, narrative direction, tone of voice, selling points, CTAs, proof, brand story, homepage data, offering — projected through the public PowerSource API serializer. Use this when you already have a powersource_id (from list_strategies) and want the full strategy payload in one call, without the job_id round-trip that get_powersource needs. Archived strategies are excluded by default (parity with list_strategies). Pass include_archived=true to read archived strategies. Read-only, free, account-scoped.

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• get_integration_guide

  TestMyVibes

  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_backtests

  Backtest360

  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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• get_briefed

  VARRD — Statistically Validated Trading Edges + AI Research Engine

  Get a personalized market news briefing based on your validated edge library. Profiles your strategies, searches today's news for the instruments and setups you actually trade, and writes a concise digest connecting each headline to your specific book. Each news item includes a ↳ line tying it to your actual positions and edges (e.g. 'your ES momentum setups', 'your GC mean-reversion edge'). Requires at least 5 strong edges in your library. Costs credits.

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• read_strategy_list

  Arcadia Finance

  Get Arcadia LP strategies. Use featured_only=true for curated top strategies (recommended first call). Returns a paginated list with 7d avg APY for each strategy's default range. Increase limit or use offset for pagination. All APY values are decimal fractions (1.0 = 100%, 0.05 = 5%). For full detail on a specific strategy (APY per range width), use read_strategy_info.

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• merge_json

  IA-QA — 130+ QA & Dev Tools for AI Agents

  Deep merge two JSON objects. Supports three array strategies: replace (default), concat, or unique (dedup concat). Nested objects are recursively merged — override takes precedence for primitives.

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• assets.list

  AI Design Blueprint Doctrine

  Public — list downloadable doctrine and agent asset artifacts (skill packs, rule packs, MCP setup snippets) the user can drop into their AI coding tool to import the Blueprint as native skill/rule files. Returns a list of assets with name, format (one of: zip / md / markdown / mdc / json / toml / text — the full vocabulary), pack_version, download_url, and platform target (Claude Code, Cursor, Codex, Gemini, Qwen). The response also carries `count` (length of `assets`) for symmetry with principles.list / clusters.list / guides.list. WHEN TO CALL: the user asks how to bring the Blueprint into their coding agent, or wants to install it as a local skill/rule file. WHEN NOT TO CALL: for the live MCP tools themselves — those are already available through this server. For doctrine content, prefer principles.list/get and guides.list/get. BEHAVIOR: read-only, idempotent, no auth required. Asset artefacts are regenerated on every deploy from the canonical doctrine.

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• axiorank_list_agents

  AxioRank: Zero-Trust for AI Agents

  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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• arena_compare_strategies

  Backtesting Arena

  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 every variable but the strategy fixed, which a series of separate arena_run_backtest calls does not guarantee. 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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• list_payment_methods

  agentcard

  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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• nihr_get_award

  Nihr

  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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• best_use

  Real Estate Analyzer

  Screen ONE property across every strategy the provided inputs qualify for and rank them by deal score — answers "what is the best use of this property?". Provide a superset of inputs (price, marketRent, adr, occupancy, rehabBudget, arv, units, …); strategies missing inputs are skipped with reasons. All rates/percents are FRACTIONS (0.0675 = 6.75%). Omitted operating inputs are filled with documented defaults and listed in assumptions.estimated_fields. Free, no key.

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• run_batch_backtests

  Helvetic Research

  Run several previously created portfolio strategies in one call and get all backtest_ids back together. Use when comparing allocation variants (e.g. 60/40 vs 70/30 vs 50/50): create each with create_strategy, then run them here instead of calling run_backtest repeatedly. Follow up with compare_backtests to rank them. strategy_ids: comma-separated strategy_ids from create_strategy

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• research_strategy_schema

  Helvetic Research

  Return the full JSON contract for run_quant_research strategies - every supported field, operator, and option for signal, futures/commodity, and synthetic-options strategies. Call this only when you need details beyond the worked example in run_quant_research (e.g. options legs, stop-loss/take-profit, VIX-aware filters).

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