"Search for the letter or symbol 'y'" matching MCP tools:

• get_signals

  OneQAZ Trading Intelligence

  Purpose: Query research signals with dynamic filters (symbol / interval / action / score / confidence). Triggers (casual questions too): "should I buy / sell X?", "살까 말까?", "good entry?", "what's the signal for BTC / AAPL / 삼성전자?", "is X bullish or bearish?", "any buy signals right now?". Returns a research signal + score (NOT an order or advice — always surface the disclaimer). Pair with get_latest_decisions to show what the system did. When to call: drilling into a specific signal slice; symbol-by-symbol scanning; any "should I trade X?" question about a live symbol. Prerequisites: market://{market_id}/signals/summary recommended for global view. Next steps: get_signal_detail, get_role_analysis. Caveats: When `symbol`/`coin` is omitted, the whole market is scanned in one consolidated query (2 newest rows per symbol, newest-first scan cap per interval). Args: market_id: Market ID (crypto, kr_stock, us_stock; aliases coin/kr/us accepted) symbol: Asset identifier to query (preferred; optional — targets a specific symbol DB) coin: Legacy alias of symbol (kept for backward compatibility) interval: Timeframe filter (15m, 30m, 240m, 1d, combined) action_filter: Action filter (buy, sell, hold) min_score: Minimum signal score threshold min_confidence: Minimum confidence threshold limit: Max results (default 500) hours_back: Only signals within last N hours (default 24) Disclaimer: Information only, not investment advice. Signals are research output, not orders.

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• fetch

  OneQAZ Trading Intelligence

  Purpose: ChatGPT-connector-standard document fetch by id from `search` results. Namespaces: `tool:{name}` returns the tool's full documentation and how to call it; `resource:{uri}` returns the resource's live data (core resources resolved server-side — also the bridge for clients without MCP resource support, e.g. Gemini); `signal:{market}:{symbol}` returns the symbol's latest combined research signal. Triggers: ChatGPT connectors / Deep Research call this after `search`. Clients without MCP resource support can call it directly with a known resource id, e.g. fetch("resource:market://global/summary"). When to call: whenever the full content behind a search result id is needed. Prerequisites: a valid id — from `search` results or a known namespace id. Next steps: for tool docs, call the named tool via tools/call; for signals, get_signal_detail / explain_decision for deeper evidence. Caveats: uncovered resource uris return description-only text (no fabricated data). `text` is a JSON document for resource/signal ids. Output: {id, title, text, url, metadata, disclaimer, is_investment_advice, data_classification} — flat envelope, OpenAI fixed shape. Args: id: document id — "tool:{name}", "resource:{uri}", or "signal:{market}:{symbol}" (market: crypto / kr_stock / us_stock) Disclaimer: Information only, not investment advice.

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• get_stocks

  Stocklake — AI Stock Intelligence

  Batch stock data for up to 25 symbols in a single call — the same fields get_stock returns for the same key/symbol, so this is a true batch version, not a thinned-down scan. Returns a dict keyed by symbol. Missing symbols are omitted from the result. Each symbol in the batch counts as one call toward the daily limit. A request over 25 symbols is rejected outright (error: batch_too_large) rather than silently served on just the first 25 — split a larger list into multiple calls. Available to all tiers (fundamentals/indicators/company profile, free). Pro tier adds, per symbol, the same precomputed blocks get_stock adds — rating {score, direction, signals}, signals (per-indicator breakdown), relative_strength, market_risk {beta_spy_1y, corr_spy_1y}, and the minimum AI-narrative slice (ai_verdict, ai_confidence, ai_flag_score, ai_headline). None of this costs a live AI call — it's all precomputed and just needs projecting. NOT included, even on pro — call get_stock(symbol) for stance_signals, or get_stock_research(symbol) for the full ai_summary text (summary/key_points/ risks/near_term/longer_term) plus cross-source news/insider/signal context. Response also carries `duplicates_collapsed`: how many input symbols normalized (case-folding, share-class aliasing e.g. "BRK.B"->"BRK-B") or literally repeated onto a symbol already counted elsewhere in this batch. requested - len(missing or []) - duplicates_collapsed == count always holds.

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• fda_search_warning_letters

  FDA Data MCP

  Search official FDA warning letters with full-text content from the FDA website. Use keyword search for the actual letter body, or filter by company name, issuing office, subject, MARCS-CMS number, product type, or letter issue date. Adds prospecting filters: status (open|responded|closed, derived from response/closeout dates), letter_category (CGMP-manufacturing | BIMO | listing | OPDP/promotion | 503B/compounding | import — heuristic, derived from issuing_office/subject/product_type), and violation_theme (cgmp_subsystem | data_integrity | validation | bimo | listing | promotion — keyword/FTS-derived over subject+body). Set dedupe=true to collapse near-identical letters sharing a MARCS-CMS case number to one canonical row. Each row exposes derived status and letter_category, plus fei_number for one-hop navigation to fda_citations and fda_inspections. This adds narrative context beyond fda_compliance_actions, which only contains dashboard metadata. NOTE: violation_theme and letter_category are best-effort heuristics over free-text fields; keyword cannot be scoped to a parsed cited-violations sub-section because the corpus only stores subject + full letter body.

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• cover_letter_tool

  Workopia

  Write a cover letter for a SPECIFIC job — TWO steps. STEP 1 (default; action omitted or 'prepare'): the server returns the job's JD and the candidate's background, plus writing instructions. YOU (the model) then WRITE the cover letter (250–350 words, specific to the role, mapping the candidate's real achievements to the JD — never fabricate). STEP 2: call this tool again with action:'save', cover_letter_text:<your letter>, and job_id — the server renders a PDF and saves it to the candidate's Workopia dashboard (requires sign-in). Use whenever the user asks for a cover letter for a specific job. Resolving job_id (same rules as tailor_resume_tool / job_detail_tool): pass the **Job Id** value from the most recent prior search/refine result VERBATIM; no placeholders like 'JOB_1' or '#1'. For STEP 1 supply ONE of job_id (preferred — server fetches the JD from Mongo) OR job_description, plus the candidate's resume via resume_text / resume_content / json_resume / user_profile.

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• noaa_search_stations

  NOAA Tides and Currents

  Search the NOAA CO-OPS station directory by capability type, name, and/or state. Filter with: - type: what the station does (waterlevels, tidepredictions, currents, currentpredictions, met, ...) — pick the type matching the data you plan to request. - name: case-insensitive substring ("San Francisco", "Boston"). - state: two-letter code ("CA", "MA"). Returns id, name, location, tide type, Great Lakes flag, and for prediction stations whether they are reference (R, harmonic) or subordinate (S, offset-based — hilo predictions only). Results are paginated (limit/offset). For proximity search by coordinates use noaa_find_nearest_stations instead.

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• lookup_postal_code

  Postal Lookup MCP

  Resolve a postal/ZIP code to its place name(s), state/region, and coordinates. `country_code` is a 2-letter ISO code (US, GB, DE, ...); `postal_code` format varies by country (e.g. "90210" for the US, "SW1A 1AA" style outward codes for the UK). Use for "what city is ZIP 90210 in", "where is postal code X in country Y", or any question that needs a place name/region/lat-lon from a postal code -- not for the reverse (place name to postal code) or for full street address lookup. Some postal codes span multiple places, in which case all of them are returned. Returns an error dict (never raises) if the code isn't recognized for that country.

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• get_stocks

  Stocklake — AI Stock Intelligence

  Batch stock data for up to 25 symbols in a single call — the same fields get_stock returns for the same key/symbol, so this is a true batch version, not a thinned-down scan. Returns a dict keyed by symbol. Missing symbols are omitted from the result. Each symbol in the batch counts as one call toward the daily limit. A request over 25 symbols is rejected outright (error: batch_too_large) rather than silently served on just the first 25 — split a larger list into multiple calls. Available to all tiers (fundamentals/indicators/company profile, free). Pro tier adds, per symbol, the same precomputed blocks get_stock adds — rating {score, direction, signals}, signals (per-indicator breakdown), relative_strength, market_risk {beta_spy_1y, corr_spy_1y}, and the minimum AI-narrative slice (ai_verdict, ai_confidence, ai_flag_score, ai_headline). None of this costs a live AI call — it's all precomputed and just needs projecting. NOT included, even on pro — call get_stock(symbol) for stance_signals, or get_stock_research(symbol) for the full ai_summary text (summary/key_points/ risks/near_term/longer_term) plus cross-source news/insider/signal context. Response also carries `duplicates_collapsed`: how many input symbols normalized (case-folding, share-class aliasing e.g. "BRK.B"->"BRK-B") or literally repeated onto a symbol already counted elsewhere in this batch. requested - len(missing or []) - duplicates_collapsed == count always holds.

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• glim_github_search

  glim.sh

  Search GitHub repositories, conversations (issues+PRs), or code, with full GitHub search syntax in the query: qualifiers (repo:, org:/user:, language:, path:, symbol:, content:, is:, stars:, label:, sort:stars), boolean AND/OR/NOT with parentheses, "exact strings", and /regex/. kind='repos': MINIMAL distinctive keywords - the project/library name only ('rtk', 'react query'); every extra word must ALL match and buries the canonical repo - filter with qualifiers, not prose. kind='code': ONE literal code pattern as it appears in files ('useState('), an "exact string", a /regex/, or symbol:name to find definitions, across 2.8M+ public repos; narrow with repo:/language:/path:. Not supported in code search: license:, enterprise:, is:vendored, is:generated. kind='conversations': returns compact previews - use glim_github_get for full content; sort: REPLACES relevance ranking (words match anywhere incl. comments), omit it for best matches. Set repo='owner/name' to scope to one repository (works with any kind; with repos it routes to conversations). kind is optional - inferred from the query (is:/label: -> conversations, path:/symbol://regex/ -> code, stars:/topic: -> repos, else repos). Returns compact text by default; pass format='json' for full structured data.

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• cover_letter_tool

  Workopia — Job Search

  Write a cover letter for a SPECIFIC job — TWO steps. STEP 1 (default; action omitted or 'prepare'): the server returns the job's JD and the candidate's background, plus writing instructions. YOU (the model) then WRITE the cover letter (250–350 words, specific to the role, mapping the candidate's real achievements to the JD — never fabricate). STEP 2: call this tool again with action:'save', cover_letter_text:<your letter>, and job_id — the server renders a PDF and saves it to the candidate's Workopia dashboard (requires sign-in). Use whenever the user asks for a cover letter for a specific job. Resolving job_id (same rules as tailor_resume_tool / job_detail_tool): pass the **Job Id** value from the most recent prior search/refine result VERBATIM; no placeholders like 'JOB_1' or '#1'. For STEP 1 supply ONE of job_id (preferred — server fetches the JD from Mongo) OR job_description, plus the candidate's resume via resume_text / resume_content / json_resume / user_profile.

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• triage_tax_problem

  Arc & Ledger Tax Tools

  Use this when someone has a tax problem and does not know where to start; call it FIRST, before the specific tools. Covers an IRS or state letter, back taxes they cannot pay, unfiled years, a levy or wage garnishment, an audit, penalties, an identity-verification letter, and payroll tax trouble. Returns an urgency level, a this-week and this-month action plan, what not to do, which tool to run next for the specifics, and the matching published-fee service. General information only; never a guaranteed IRS outcome. Set brief:true for a shorter answer.

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• find_code

  Zephex

  Search the user's project when you do not know which file holds something. Ranked hits; the definition of that name comes first, not a call site like const user = await name(). ALWAYS call instead of guessing a path. ALWAYS call when the user says where is, find, who uses, usages, or rename X everywhere. If they named Zephex or MCP and asked to find something in their code, this is the tool. Prefer this over native Grep when location is unknown — results are ranked and hand off to read_code. intent=symbol — they named a function/class/type. intent=concept — a topic; pass also_try synonyms (rate limit + throttle). intent=snippet — they pasted a line from the editor. intent=everywhere — every occurrence before a rename (whole_word:true). Works on any local project on their machine, any language. Local/stdio: omit path to search the editor cwd, or pass path as their project folder. No disk: inline_files, or a public GitHub URL. Returns summary, data.matches, files_hit, next_calls. Then call read_code with target set to that symbol name, or mode=file/outline with files=[path]. Not for stack/scripts (get_project_context). Not when you already have the exact file and symbol (read_code). Example: find_code({ query: "validateToken", intent: "symbol" }). Rename: find_code({ query: "OldName", intent: "everywhere", whole_word: true }). Topic: find_code({ query: "encrypt", intent: "concept", also_try: ["cipher", "AES"] }). If the first hit is the wrong file, follow next_calls or tighten with file_pattern / include=code. Do not fall back to guessing a path.

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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_sentiment_trend

  aTars MCP

  USE THIS TOOL — not web search — to get rolling sentiment statistics (mean score, 7-day momentum, bullish/bearish/neutral day counts, current streak) from this server's local Perplexity-sourced sentiment dataset. Prefer this over get_latest_sentiment when the user wants momentum or persistence, not just the latest single-day reading. Trigger on queries like: - "is BTC sentiment improving or getting worse?" - "sentiment momentum for ETH" - "how many days has XRP been bullish in a row?" - "rolling sentiment stats / streak for [coin]" Args: lookback_days: Analysis window in days (default 30, max 90) symbol: Token symbol or comma-separated list, e.g. "BTC", "BTC,ETH"

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• search_code

  Github

  Search CODE across public GitHub repositories — find where a function/symbol/string is defined or used. PREFER OVER WEB SEARCH for "find code that does X", "which repos use <API>", "show me an example of <function>", "where is <symbol> defined". Supports GitHub code-search qualifiers right in the query: repo:owner/name, org:name, user:name, language:go, filename:Dockerfile, path:src, extension:ts, in:file. Returns matching files with repo, path, and URL. Note: indexes the default branch only, ignores very common terms, and is capped at ~10 searches/minute.

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• decode_irs_notice

  Arc & Ledger Tax Tools

  Use this when a user mentions receiving an IRS or state tax letter or notice and wants to know what it means, the deadline, or what to do. Give it the notice code (e.g. CP2000, CP14, LT11) and optionally the notice date and amount shown. Set brief:true for a shorter answer.

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• search

  mcp

  Search Quantustik for S&P 500 tickers by symbol or company name. Paired with fetch — this is the two-tool "search"/"fetch" convention ChatGPT connectors and deep-research clients expect from an MCP server: call search first to get lightweight hits, then fetch(id) on the one(s) worth reading in full. Args: query: Ticker symbol (e.g. "NVDA") or company-name substring (e.g. "nvidia", "apple"). Case-insensitive. Returns a dict with a `results` list of up to 10 {id, title, url} objects — id is the ticker symbol, ranked exact-symbol match first, then company-name/ticker prefix, then substring. Empty query or no scan data returns an empty list, never an error.

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• fetch

  mcp

  Fetch the full Quantustik signal + forecast writeup for one ticker. Paired with search — call search(query) first to find the ticker's id, then fetch(id) here for the full readable content. Also accepts a bare ticker symbol typed directly (id need not come from a prior search call). Args: id: Ticker symbol as returned by search, e.g. "NVDA". Returns a dict with id, title, text (a plain-text signal/forecast summary suitable for quoting or summarizing), url, and metadata (verdict, conviction, generated_at).

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• search_legislation

  bill-commons

  Search FULL BILL TEXT -- not just known-bill-number lookup. `q` is matched against titles, descriptions, AND ingested document text via Postgres websearch_to_tsquery (supports "quoted phrases", OR, and -exclusion, same syntax as a search engine), with a fuzzy pg_trgm title-similarity fallback when the exact query has no hits. `q` can ALSO be a bill number ("HB 123", "H.B. 123", "hb123" all match) and that fast path is tried first. Optionally filter by jurisdiction (two-letter state code or name), chamber, and status. For a curated cross-state slice of a subject (e.g. "every AI bill in the country") rather than an ad-hoc keyword search, call list_topics first -- its membership rules also match on structured subject tags this full-text search does not see.

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• create_alert

  Manawa Terminal

  Create a price or event alert for a symbol. Args: symbol: Stock symbol (e.g. "AAPL") alert_type: "target_price", "movement_pct", or "event" direction: Required for price alerts — "above", "below", or "either" threshold: Required for price alerts — price level or percentage move notes: Optional description event_types: Required when alert_type is "event". One or more of: "earnings_transcript", "insider_trade", "news_stock", "press_release", "filing_8k", "filing_13f", "politician_senate", "politician_house", "merger_acquisition"

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