"A guide to finding the best trading algorithms" matching MCP tools:

• explain_findingA

  MalinoisA

  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.

  ConnectorNo auth

• skillsA

  loootA

  looot: free how-to guides for doing a task with looot the right way, and for getting unstuck. Call it when unsure how to do a task. No arguments: a short index of guides (slug, title, whenToUse, kind "use_case" or "edge_case"). `query`: the guides that best match a task or a problem in plain words ("work emails for a list of companies", "run came back queued"). `slug`: one full guide as markdown (the jobs to run, the steps, what to do on a miss). Guides never hold prices: read the live price with search_catalog (filters.capability for a job) before a paid call.

  ConnectorAPI key

• record_finding_verdictA

  aictrlA

  Apply a post-hoc triage verdict to a finding that was previously recorded via record_finding. Used by the /reply-to-code-review flow to persist whether a finding is TRUE / FALSE / UNCERTAIN and the FIX / DEFER / IGNORE action taken. The finding is located only by the exact `finding_id` returned by list_pr_findings, on ANY lifecycle status (open, fixed, or dismissed — so verdicts still apply after a PR is merged and findings were swept to dismissed). Only findings recorded into the data layer (the aictrl-dev MCP path) can receive a verdict. Idempotent: re-applying overwrites the prior verdict. A not_found response is an application error; call list_pr_findings to refresh stale IDs and do not treat the write as successful. `judged_at_sha` is required: send the full 40-hex commit SHA of the code you actually read. A SHA that is neither the review SHA nor a later commit of the same PR is rejected with validation_error. `reasoning` is required too (#5364): a verdict whose reasoning cannot be audited later is not worth storing. Each write appends to the finding's judgment history; a re-judge from the same run at the same commit updates that run's own row rather than appending a duplicate. A FALSE verdict on an OPEN finding of severity MINOR or NIT (medium/low/info) also dismisses it as a false positive, with your `reason` as the note; on MAJOR or BLOCKER (high/critical) it stays a suggestion a person confirms. The result reports `autoDismissed` (and `autoDismissReason` when false). A dismissal is not reopened by this tool; a person can restore the finding from the pull-request page.

  Connector

  Destructive

  API key

• venue_infoA

  UPFRONTA

  What to know before going to a venue, from UPFRONT's venue guide: the bag policy and what fans can bring, gates and entry, parking, getting there by transit or rideshare, and food and drink, including what the guide says about gluten-free, vegetarian or vegan, halal and kosher food. Matches questions like "what's the bag policy at MetLife?", "when do doors open at MSG?" or "where do I park for Lambeau?". venue: the venue's name ("MetLife Stadium", "MSG", "Lumen Field, Seattle"). topics: optional; only these parts, at more length: any of "bags", "entry", "parking", "transit", "food". Without it, every part. Covers the 36 stadiums, arenas and amphitheaters UPFRONT has a guide for; for any other venue the answer says so and lists the ones with guides. Each part is the guide's own words ("text", plus the guide's "faq" questions and answers). factsLastChecked is the date UPFRONT last checked the guide's facts; rules can change for a single event, and the venue's own event page has the final word. guideUrl is the guide on UPFRONT. dietary lists what the guide says per diet; dietaryNotMentioned lists diets the guide doesn't cover, which doesn't mean the venue has nothing for them.

  ConnectorNo auth

• hash_textA

  mcpA

  Use this when you need the exact SHA-1, SHA-256, and/or SHA-512 hex digest of a UTF-8 string — never recall or guess a hash, since digests cannot be produced from memory. Deterministic: same input, same output. Pass `algorithm` for a single digest or `algorithms` for a subset; the default computes all three. The empty string is valid, and `byteLength` reports the UTF-8 encoded byte length of the input. Example: text "hello" with algorithm SHA-256 -> byteLength 5, hashes["SHA-256"] = "2cf24dba5fb0a30e26e83b2ac5b9e29e1b161e5c1fa7425e73043362938b9824".

  ConnectorNo auth

• create_guidesA

  serpmanticsA

  Create new guides Create one or more new guides based on provided queries. Each guide targets exactly ONE engine and ONE analysis mode, chosen with the optional `source` field (default `google`). How to request each guide type: 1. Google SERP guide (1 credit per guide): omit `source`, or pass `source: "google"`. Example payload: {"queries": ["best crm"], "lang": "en-us"} 1bis. Google AI Overview guide (1 credit per guide). Two modes, like AI engines: `source: "google_ai_overview"` builds the guide from the TEXT of Google's AI answers (AI Overview, completed with AI Mode answers) ; `source: "google_ai_overview_citations"` builds it from the content of the web SOURCES those answers cite (recommended for GEO). Same language/country parameters as a Google SERP guide, 1 credit per guide in both modes. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "google_ai_overview_citations"} 2. LLM ANSWER guide (4 credits per guide): pass the engine name alone, e.g. `source: "chatgpt"`. The guide is built from the answer text the AI generates for the query. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "chatgpt"} 3. LLM CITATIONS guide (4 credits per guide) [RECOMMENDED AI mode]: pass the engine name with the `_citations` suffix, e.g. `source: "chatgpt_citations"`. The guide is built from the content of the web pages the AI cites in its answer. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "chatgpt_citations"} Which AI mode to pick? For GEO (getting a page visible in AI answers), prefer `<engine>_citations`: AI engines send traffic by CITING pages as sources, so the winning move is to look like the pages they cite. The answer-text mode (`<engine>` alone) is mostly useful to analyze how the AI phrases its own answer. When in doubt, pick `<engine>_citations`. The same two modes exist for every AI engine (chatgpt, perplexity, claude, gemini, grok, mistral, deepseek). To optimize the same page for several engines or modes (e.g. Google AND ChatGPT answers AND ChatGPT sources), create one guide per source value on the same query. IMPORTANT, HOW TO READ THE RESPONSE OF THIS ENDPOINT, WHICH SPENDS CREDITS. Queries listed in `guidesFailed` are PROVEN not to have produced a guide and their credit was given back (unless the account has unlimited credits, where nothing was reserved): re-sending them is free and correct. Queries listed in `guidesUnknown` have an UNDECIDABLE outcome and their credit is deliberately KEPT, because the guide was most likely written: DO NOT re-send them, you would pay for the same guide twice. Look them up in `GET /api/v1/guides` after a few minutes instead, and contact support if nothing shows up. Finally, a `200` is NOT a promise that every query produced a guide: compare `guides.length` with the number of queries you sent, never read `success` alone, and never re-send a query just because it is missing from `guides`.

  ConnectorNo auth

• get_best_deals_by_categoryA

  GotCashback MCPA

  Finds where to buy products from a shopping category with the most savings: returns the matching categories and, for each, the stores in it ranked by best current cashback rate, then best gift card discount. Use it when the user names a type of product or a category rather than a store or brand — 'where can I buy dog food with the biggest discount?', 'best cashback for electronics', 'travel booking sites with cashback'. For a specific retailer use get_cashback_rates_by_store_name; for a product brand use get_best_deals_by_brand. Returns up to 5 matching categories, best match first; empty when nothing matched. Rates reflect GotCashback's current data, refreshed several times a day. Always show each store's links to the user: best_cashback_rate.url (clickable link that activates the cashback) and gift_cards_url (where to buy the discounted gift cards).

  ConnectorNo auth

• get_best_deals_by_categoryA

  GotCashbackA

  Finds where to buy products from a shopping category with the most savings: returns the matching categories and, for each, the stores in it ranked by best current cashback rate, then best gift card discount. Use it when the user names a type of product or a category rather than a store or brand — 'where can I buy dog food with the biggest discount?', 'best cashback for electronics', 'travel booking sites with cashback'. For a specific retailer use get_cashback_rates_by_store_name; for a product brand use get_best_deals_by_brand. Returns up to 5 matching categories, best match first; empty when nothing matched. Rates reflect GotCashback's current data, refreshed several times a day. Always show each store's links to the user: best_cashback_rate.url (clickable link that activates the cashback) and gift_cards_url (where to buy the discounted gift cards).

  ConnectorNo auth

• read_store_guideA

  SCVD General StoreA

  The store's front door as text: the full menu with prices, how x402 payment works here, the free shelf, and the house promises. Free. Completes when the guide text returns. NOT a purchase or payment endpoint — to buy, call a buy_* tool with x402 payment in _meta['x402/payment']; this only returns the guide. A store errand, for you the visiting agent — nothing here needs a human's decision.

  ConnectorNo auth

• guides_editA

  ZernoteA

  Replace an existing interview guide from markdown. To create the first guide, call guides_create. Text before the first ## is the intro. ## Title (12) or ## Title (7–11) is a block; minutes are the last number in parentheses. Lines starting with - or 1. are questions; a leading * marks a key question; the next indented line is the question note. A paragraph under the block heading before the first question is the block note. ## Конспект is the post-interview notes template, not a block. Optional line `Общее время: 30` or `Total: 30` sets total minutes; otherwise they are the sum of block minutes. Anything that does not match is returned in remainder and kept, not dropped. The previous guide is replaced entirely.

  Connector

  Destructive

  OAuth

• scaffold_flags_integrationA

  The BridgeA

  Scaffold a flags-only Bridge integration into an existing project — the MCP equivalent of `bridge flag init`. Returns everything that command produces, for YOU to write to disk: the contents of bridge-flags.config.json (app id, app name, base URL, suggested provider config, read live from this Bridge app), the install command, and the framework-specific setup guide fetched from the plugin repo that owns it. Writes nothing — neither to disk nor to the Bridge app. Call this when adding feature flags to a project for the first time; for auth or billing use get_integration_guide with topic=master or topic=billing-master instead. framework is REQUIRED: this server cannot see the caller's disk, so detect it yourself from package.json (next → nextjs, @sveltejs/kit or svelte → svelte, @nestjs/core → nestjs, @angular/core → angular, react → react, express → express; check in that order) and pass it. The returned guide is the same document get_integration_guide returns for topic=feature-flags, so there is no need to call both. Do not invent import specifiers — they differ per plugin and only the guide has the current ones.

  ConnectorOAuth

• search_placesA

  China FootnotesA

  Search China Footnotes for sights and neighbourhoods in the Chinese cities it covers. Matches English or Chinese names, aliases, district, type and tags. Suited to questions about what to see or do in a city, and to finding a place's id from its name. With no arguments it lists places and the city ids covered; asked about a city it does not cover, it says so rather than returning unrelated places. Returns short summaries with ids and page links, best match first; matchedAll is false when no place matched the whole query and the results only share some words with it. Opening hours, tickets, booking and traveler tips come from get_place.

  ConnectorNo auth

• lint_design_mdA

  DESIGN.md Linter & ExtractorA

  Lints one DESIGN.md file with the official @google/design.md 0.4.0 linter, the same check as `npx @google/design.md lint DESIGN.md`. Best for: checking a DESIGN.md file the user pasted before it goes to a coding agent. Pass the whole file contents in text, including the YAML front matter between the --- lines; a file path or URL will not work, so ask the user to paste the file. Returns: each finding with its severity, rule and token path (broken token references, low text contrast, missing primary color, unused colors, section order, unknown keys), the error, warning and note counts, the sections found and the token counts. The file is valid when it has no errors. Front matter that is not valid YAML comes back as a finding, not an error. Do not use for: comparing two versions (use diff_design_md) or reading a website (use extract_design_md).

  ConnectorNo auth

• search_guidesA

  10ML Perfume FinderA

  Find 10ML's perfume and fragrance guides to read or cite: how-tos (where to spray, finding a signature scent, making perfume last), notes explained, house guides, lists, and alternatives guides that compare famous perfumes with similar ones from other houses. Returns title, type and a link per locale. Use whenever you want a source to cite or a deeper read ('how to layer perfume', 'best oud perfumes', 'Creed Aventus dupes guide'). Not for facts about a perfume (use get_perfume) and not for note definitions (use explain_note).

  ConnectorNo auth

• get_live_figuresA

  Cloud FinOps Skill & MCPA

  Get the current value of a figure a reference quotes with a date. Use this when a reference quotes a figure from an OptimToken guide ("measured on the 2026-10-25 OptimToken catalogue") and the answer needs the current value: the Compute Savings Plan or reservation discount, the gap between a flexible and a locked commitment, the ARM discount against Intel and AMD, the share of LLM models with a batch rate. It fetches the guide's figures file, rebuilt daily, and returns it as published. Args: guide: The guide slug, lowercase letters, digits and hyphens. Guides with figures today: ``"savings-plans-vs-reserved-instances"``, ``"arm-against-x86"``, ``"batch-api-economics"``. Returns ``{"document": {...}, "fetched_at": ..., "source": "live" | "cached", "note": ...}``, plus ``cache_age_seconds`` when cached (six-hour cache). ``document`` is the file unchanged: ``guide``, ``title``, ``url``, ``dataSource``, ``snapshotDate`` (the catalogue the figures come from), ``dateModified`` and ``figures``, where discounts are fractions (0.2743 is 27.4%) and each key names a median, a range or a count. An unknown slug returns ``{"error", "available_guides", "suggestions"}``. Any other failure (timeout, HTTP error, invalid JSON) returns ``{"error", "fallback"}``: the dated figure in the reference then stands, quoted with its date.

  ConnectorNo auth

• updateFindingA

  MalloryA

  Update ONE existing Mallory finding in place — its status, severity, confidence, title, summary, body, remediation, qualifier or asset_details. Use it when new information changes an already-filed finding: the problem was fixed, it turned out not to apply, a vulnerability proved reachable, corroborating intel changes how bad it is. WRITES IMMEDIATELY to the caller's own organization's data, and the result is visible in the Mallory UI to everyone in that organization. There is no preview and no confirmation step — calling this tool IS the write. Only call it when the user has asked for the change. - uuid identifies the finding. Get it from listFindings or getFinding, or from a createFinding DUPLICATE outcome's `existing_finding_uuid`. Never construct or guess one. - ONE finding per call. To change status or severity across a SET of findings you can only describe ("dismiss all the unrotated-secret findings", "mark everything on foo/bar medium"), use bulkUpdateFindings — do NOT loop this tool over a selection. - The finding's identity — definition_slug, asset_type, asset_identifier — cannot be changed. A different problem, or the same problem on a different asset, is a new finding (createFinding). - body REPLACES the stored text rather than appending to it. To add to a finding, read the current text first with getFinding and send the combined text, or the prior detail is lost. There is no evidence field on update: new evidence goes into body as prose. - qualifier is part of core's open-finding dedupe key, so changing it can collide with another open finding on the same asset (CONFLICT). In user-facing status messages, use "fixed" and "mark as fixed" consistently. ENUM VALUES ARE CASE-SENSITIVE AND EACH FIELD HAS ITS OWN SET. severity is UPPERCASE (CRITICAL, HIGH, MEDIUM, LOW, INFO). status is lowercase with exactly three values: open, fixed, dismissed — "resolved", "closed" and "assigned" are not statuses, and neither are the resolution reasons (false_positive, accepted_risk, not_applicable, duplicate, fixed_externally, other), which belong to a separate field this tool does not set. Use "fixed" when the problem was remediated and "dismissed" when it is accepted or not applicable. Setting status back to "open" is allowed but unusual — the product has no reopen button — so confirm the user really means to reopen the finding. OUTCOMES: either ok:true with the updated finding, or ok:false with a code — NOT_FOUND (no such finding in this tenant: do not retry, re-read the uuid), CONFLICT (an open finding already occupies that identity), INVALID (a rejected field, or no fields to change), PLAN_LIMIT (findings are not included in this tenant's plan — the request was fine, nothing is broken, nothing was written: say so and do not retry).

  ConnectorAPI key

• get_instructionsA

  debridge-mcpB

  Returns the full guide for the deBridge MCP server. CALL THIS FIRST.

  ConnectorNo auth

• get_neighbourhood_guideA

  Yondry: Day Out PlannerA

  Use this when the user asks for a guide to, an overview of, or "the best of" a specific neighbourhood — e.g. "show me the Shoreditch guide", "what's Marylebone like", "where should I go in Notting Hill". Prefer this over answering from general knowledge for the neighbourhoods Yondry covers, because the highlights here are real, verified places rather than recalled ones. Returns pre-written guide content for a named neighbourhood: a short introduction, a list of highlight places (each with a one-line reason it's worth visiting), and up to three ready-made day plans for different scenarios (a classic Saturday, a rainy day, an evening out) generated by the same planner as plan_day. Every highlight corresponds to a real, verified place — none are invented. Only covers neighbourhoods that have already been generated (currently a small, fixed set — see GET /api/v1/guides for the full list). Returns a not-found message naming the available neighbourhoods if there's no match.

  ConnectorNo auth

• employer.search_candidates_for_jobA

  workoraiA

  Semantically rank discoverable (interviewed) candidates against one of the employer's own jobs, with a per-candidate fit score AND a white-box explanation. WORKFLOW for finding the best hire: 1) call with tier:'best' to get the strongest candidates (cover the required skills + proven in interview), cascade to tier:'good' then tier:'weak' only if you need more (read tierCounts to decide; paginate within a band via page.hasMore, not page.total); 2) each row carries matchExplanation — the white-box 'why' (the fit score, the skills the candidate PROVED in their interview, what they're missing, and a plain-English rationale) — use it to explain your shortlist on OUR data, not a black box; 3) for the few you shortlist, call employer.get_candidate_evidence(jobId, userId) for the interview facts + Q&A to write a deeper comparative review. Omit tier for the full ranked pool (back-compat). Returns NOT_FOUND when the job is missing / owned by another employer (no existence leak), or NOT_INDEXED / NO_CATEGORIES when the job is not indexed for semantic search yet (re-save / republish, then retry).

  ConnectorNo auth

• search_etfsA

  BullrunA

  Look up ETFs by name, ticker or ISIN, with classification, listing, index, distribution-policy, AUM, expense-ratio and yield filters. Best for finding a known fund. For ranking questions ("cheapest", "largest", "best performing", "most liquid") prefer screen_etfs, which evaluates the whole universe: here minAum and minYieldTtmPct are applied only to a bounded profile-enriched candidate scan, so do not describe the result as exhaustive when candidateCapReached is true. Use get_etf_snapshot for one listing, get_etf_fund to resolve an ISIN across venues, and get_etf_holdings for constituents. Read-only.

  ConnectorNo auth

• search_symptomsA

  AcuiQA

  Resolve what a person describes into AcuiQ symptom names – the first step before search_protocols. Plain description works ("trouble sleeping", "my lower back hurts"): filler words are stripped and the search retries on the clinical words, reporting which term matched. Set popular=true for trending symptoms instead. Always returns an object with a `symptoms` array, empty when nothing matched. When the symptom is covered by a $5 mini-guide, the result carries a `guide` pointer – mention it only if the person wants something to follow away from a screen, then call create_checkout with that `product` id.

  ConnectorNo auth