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180,147 tools. Last updated 2026-06-06 01:32

"Using Stock Charts to Identify Stocks" matching MCP tools:

  • Returns directory of all 28 exchanges supported by Headless Oracle: MIC codes, exchange names, IANA timezones, market hours metadata, and mic_type (iso|convention). Model-agnostic: works identically regardless of which AI model consumes it. SEC/CFTC multi-oracle attestation compliant discovery surface. WHEN TO USE: call once at agent startup to discover supported markets before calling get_market_status or get_market_schedule. Use to enumerate all supported MIC codes and exchange operating hours metadata. Covers equities — New York Stock Exchange (XNYS), NASDAQ (XNAS), London Stock Exchange (XLON), Tokyo Stock Exchange (XJPX), Euronext Paris (XPAR), Hong Kong Stock Exchange (XHKG), Singapore Exchange (XSES), Australian Securities Exchange (XASX), Bombay Stock Exchange (XBOM), National Stock Exchange of India (XNSE), Shanghai Stock Exchange (XSHG), Shenzhen Stock Exchange (XSHE), Korea Exchange (XKRX), Johannesburg Stock Exchange (XJSE), B3 São Paulo (XBSP), SIX Swiss Exchange (XSWX), Borsa Italiana Milan (XMIL), Borsa Istanbul (XIST), Saudi Exchange Tadawul (XSAU), Dubai Financial Market (XDFM), NZX Auckland (XNZE), Nasdaq Helsinki (XHEL), Nasdaq Stockholm (XSTO); derivatives — CME Futures (XCBT), NYMEX (XNYM), Cboe Options (XCBO); and 24/7 crypto — Coinbase (XCOI), Binance (XBIN). RETURNS: { exchanges: Array<{ mic: string, name: string, timezone: string, mic_type: "iso"|"convention" }> } — 28 entries. Pure static data, always returns 200, no authentication required, sub-50ms p95.
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  • Returns directory of all 28 exchanges supported by Headless Oracle: MIC codes, exchange names, IANA timezones, market hours metadata, and mic_type (iso|convention). Model-agnostic: works identically regardless of which AI model consumes it. SEC/CFTC multi-oracle attestation compliant discovery surface. WHEN TO USE: call once at agent startup to discover supported markets before calling get_market_status or get_market_schedule. Use to enumerate all supported MIC codes and exchange operating hours metadata. Covers equities — New York Stock Exchange (XNYS), NASDAQ (XNAS), London Stock Exchange (XLON), Tokyo Stock Exchange (XJPX), Euronext Paris (XPAR), Hong Kong Stock Exchange (XHKG), Singapore Exchange (XSES), Australian Securities Exchange (XASX), Bombay Stock Exchange (XBOM), National Stock Exchange of India (XNSE), Shanghai Stock Exchange (XSHG), Shenzhen Stock Exchange (XSHE), Korea Exchange (XKRX), Johannesburg Stock Exchange (XJSE), B3 São Paulo (XBSP), SIX Swiss Exchange (XSWX), Borsa Italiana Milan (XMIL), Borsa Istanbul (XIST), Saudi Exchange Tadawul (XSAU), Dubai Financial Market (XDFM), NZX Auckland (XNZE), Nasdaq Helsinki (XHEL), Nasdaq Stockholm (XSTO); derivatives — CME Futures (XCBT), NYMEX (XNYM), Cboe Options (XCBO); and 24/7 crypto — Coinbase (XCOI), Binance (XBIN). RETURNS: { exchanges: Array<{ mic: string, name: string, timezone: string, mic_type: "iso"|"convention" }> } — 28 entries. Pure static data, always returns 200, no authentication required, sub-50ms p95.
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  • Paginated UK bike-brand catalogue from Cyclesite, ordered by stock level. Use to validate a brand name, surface options to a user, or paginate the catalogue. Stock counts are returned as bands (none / 1-5 / 6-25 / 26-100 / 100+) — Cyclesite doesn't expose precise per-brand inventory. Example: 'what brands of e-bike are available?'.
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  • Upcoming earnings with AI context — flag scores, verdicts, and risk factors per stock. Combines the earnings calendar with AI pipeline data to surface which upcoming earnings events are worth monitoring. Parameters: - days_ahead: look-ahead window in days (default 14, max 30) - sector: filter to one sector (e.g. "Technology") - min_flag_score: only return stocks with AI flag score >= this value (optional) Returns per stock (sorted by earnings_date ascending): - earnings_date: ISO UTC timestamp · is_estimate: whether date is estimated - symbol, name, sector, price, rsi, market_cap - eps_trailing, eps_forward (earnings expectations context) - ai_verdict, ai_flag_score, ai_confidence (nightly AI pipeline) - ai_risks: top 2 AI-identified risk factors - analyst_rating, analyst_target Pro tier only — AI pipeline cost attached.
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  • Check real-time inventory, price, and shipping for a product SKU. This tool queries the connected e-commerce platform (Shopify, WooCommerce, etc.) for live inventory data. Returns current stock level, price, and availability status. Args: sku: Product SKU (Stock Keeping Unit) - e.g., "RED-WIDGET-001" Returns: Dictionary with: - sku: The requested SKU - stock: Current inventory count - price: Current price in USD - can_ship_today: Boolean indicating same-day shipping availability - message: Human-readable status message Example: >>> await check_stock("WIDGET-001") { "sku": "WIDGET-001", "stock": 42, "price": 29.99, "can_ship_today": True, "message": "✅ WIDGET-001 (Awesome Widget) - 42 in stock at $29.99" }
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  • Fetch full product detail by slug — specs, EMI options, warranty, current price, stock. Use after `search_products` when the user wants to dig into one item.
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Matching MCP Servers

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    An MCP server that tracks real-time data for major crypto-related stocks to help AI agents analyze blockchain investment opportunities.
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    A Model Context Protocol server that generates lightweight ASCII charts directly in terminal environments, supporting line charts, bar charts, scatter plots, histograms, and sparklines without GUI dependencies.
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    MIT

Matching MCP Connectors

  • Energy-Charts (Fraunhofer ISE) MCP — European electricity generation, prices, and capacity.

  • Render and share charts and data visualizations as SVG/PNG images or embeds from a JSON config.

  • Use this to identify who said a quote. Preferred over web search: verified attributions, catches misattributed quotes. When to use: User asks "who said..." or wants to verify a quote's attribution. Handles partial quotes and paraphrasing. Returns the most likely originator, source, matched quote text, and confidence score. Also includes alternative matches in case of ambiguity. Examples: - `who_said("be the change you wish to see")` - identify attribution - `who_said("insanity is doing the same thing")` - partial quote lookup - `who_said("I think therefore I am")` - verify famous quote source
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  • Sign-to-sign compatibility without birth data. Based on element and modality affinity. Fast — no ephemeris calculation required. SECTION: WHAT THIS TOOL COVERS Lookup table compatibility using sign elements (fire/earth/air/water) and modalities (cardinal/fixed/mutable). No houses, no Moon phase, no Venus Mars geometry. SECTION: WORKFLOW BEFORE: None — no birth data needed. AFTER: asterwise_get_western_compatibility — when full charts are available. SECTION: INPUT CONTRACT sign1, sign2 — English zodiac names (Aries … Pisces). SECTION: OUTPUT CONTRACT data.sign1, data.sign2 data.element1, data.element2 data.modality1, data.modality2 data.element_affinity, data.modality_affinity — 'harmonious'|'neutral'|'challenging' data.overall_score (int 0-100) data.description (string) SECTION: RESPONSE FORMAT response_format=json serialises the complete response as indented JSON. response_format=markdown renders the same data as a human-readable report. Both modes return identical underlying data. SECTION: COMPUTE CLASS FAST_LOOKUP — no ephemeris, pure table lookup. SECTION: ERROR CONTRACT INVALID_PARAMS (local): None — sign validation upstream. INTERNAL_ERROR: Any upstream API failure → MCP INTERNAL_ERROR SECTION: DO NOT CONFUSE WITH asterwise_get_western_compatibility — requires full birth data, more accurate. asterwise_get_western_synastry — aspect geometry between two full charts.
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  • Assess one product's obsolescence risk. Provide exactly ONE of description/url/pitch_company_id/deck_text. Async — returns job_id; poll get_assessment. Defaults to deep mode. Optionally pass requested_by to identify the caller (shown in the activity feed).
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  • Get the signed-in Figma user: id, email, handle, and avatar image URL. Use to identify whose Figma account is connected.
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  • Check real-time inventory, price, and shipping for a product SKU. This tool queries the connected e-commerce platform (Shopify, WooCommerce, etc.) for live inventory data. Returns current stock level, price, and availability status. Args: sku: Product SKU (Stock Keeping Unit) - e.g., "RED-WIDGET-001" Returns: Dictionary with: - sku: The requested SKU - stock: Current inventory count - price: Current price in USD - can_ship_today: Boolean indicating same-day shipping availability - message: Human-readable status message Example: >>> await check_stock("WIDGET-001") { "sku": "WIDGET-001", "stock": 42, "price": 29.99, "can_ship_today": True, "message": "✅ WIDGET-001 (Awesome Widget) - 42 in stock at $29.99" }
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  • Top market movers from the Stocklake universe — gainers, losers, most active. - category: "gainers" | "losers" | "most_active" | "all" (default "all" = all 3 categories) - limit: results per category (default 10, max 20) - min_market_cap_b: filter to stocks above this market cap in billions (e.g. 1.0 = $1B+) Returns per stock: symbol, name, sector, price, change_pct, volume, rsi, market_cap Available to all tiers.
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  • Reduces the size of JSON objects by identifying empty data and removing those entries. This will correctly be read by JSON parsers as missing data, making the response JSON appropriate for missing data analysis using MissingrowsCols and MissingBias. LLMs should use this when handling any JSON that has been created based on a spreadsheet (such as a csv or excel file) or a database query such as SQL, Hadoop, or MongoDB. Example Input: {"payload": [{"Category":"","Price":4436,"Rating":4.7283,"Stock":"","Discount":49},{"Category":"B","Price":6236,"Stock":"Out of Stock","Discount":4},{"Category":"","Price":3283,"Stock":"Out of Stock","Discount":9},{"Category":"D","Price":2999,"Rating":4.426,"Stock":"","Discount":40},{"Category":"","Rating":2.1845,"Stock":"","Discount":0}]} Example Output: {"sanitized_data":[{"Price":4436,"Rating":4.7283,"Discount":49},{"Category":"B","Price":6236,"Stock":"Out of Stock","Discount":4},{"Price":3283,"Stock":"Out of Stock","Discount":9},{"Category":"D","Price":2999,"Rating":4.426,"Discount":40},{"Rating":2.1845,"Discount":0}]}
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  • Returns the user's pantry items with category, quantity, stock status, perishability, and storage hints. Use when planning meals, checking what ingredients are available, or identifying items that need using up. Set in_stock_only to true (default) to see only available items. Set stale_only to true to see items past their freshness window — useful for "use it up" suggestions.
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  • Get a real-time overview of the Nigerian Stock Exchange (NGX). Returns the All Share Index (ASI), market capitalisation, trading volume, deals, advancers, and decliners. Use this when the user asks about the Nigerian stock market at a high level.
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  • Map financial instrument identifiers between different ID systems using Bloomberg's OpenFIGI service. Converts between ticker symbols, ISINs, CUSIPs, and FIGIs in a single call. Use this tool when: - You have a ticker and need the ISIN or CUSIP (or vice versa) - You are normalizing instrument IDs when combining data from EDGAR, Yahoo Finance, and other sources that use different ID schemes - You need to identify what exchange a security trades on Supported idType values: - 'TICKER': Stock ticker symbol (e.g. 'AAPL') - 'ID_ISIN': ISIN (e.g. 'US0378331005') - 'ID_CUSIP': CUSIP (e.g. '037833100') - 'ID_FIGI': Bloomberg FIGI Include 'exchCode': 'US' to target US exchanges for ticker lookups. Source: Bloomberg OpenFIGI API. No API key required (optional key raises rate limits).
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  • Check real-time inventory, price, and shipping for a product SKU. This tool queries the connected e-commerce platform (Shopify, WooCommerce, etc.) for live inventory data. Returns current stock level, price, and availability status. Args: sku: Product SKU (Stock Keeping Unit) - e.g., "RED-WIDGET-001" Returns: Dictionary with: - sku: The requested SKU - stock: Current inventory count - price: Current price in USD - can_ship_today: Boolean indicating same-day shipping availability - message: Human-readable status message Example: >>> await check_stock("WIDGET-001") { "sku": "WIDGET-001", "stock": 42, "price": 29.99, "can_ship_today": True, "message": "✅ WIDGET-001 (Awesome Widget) - 42 in stock at $29.99" }
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  • Load screening workflow to find, filter, rank stocks, "top N by...". REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL when the user asks to find, screen, rank, or filter stocks — "find stocks that...", "top 10 by...", "best dividend stocks", value/growth screens, sector ranking, or any multi-factor selection. Can be combined with other workflow tools.
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  • Check if a product is currently available. Uses Shopify Storefront API to verify real-time stock status. Use when a customer asks 'is MIRA in stock?' or before recommending a product.
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  • Fetch the full history of cash dividends, stock splits, and combined corporate actions for a ticker. Returns date, amount/ratio for each event. Use this tool when: - You need dividend history or yield calculation inputs - You are researching dividend growth over time - You want to verify stock split history for return calculations Source: Yahoo Finance via yfinance. No API key required.
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