"A guide for performing chart analysis on stocks" matching MCP tools:

• list_creator_videosA

  SocialGPTA

  List a public/competitor creator's videos by platform + handle. Sort by 'recent' or 'top' (best-performing); optionally with analysis inline. Only returns creators already in the analysis library — for one you haven't ingested yet this returns reason="creator_not_in_library" with a next_step of analyze_creator(platform, username), not an error. When more videos exist beyond this page the response includes next_cursor — pass it back as cursor (same sort/filters) to fetch the next page; when next_cursor is absent you have everything.

  ConnectorOAuth

• data_to_chartA

  Ciro Cesar Maciel — Free ToolsA

  Draws a chart from a CSV table and returns it as an image. WHEN TO USE: the user wants to see data as a chart, or needs a chart image for a document, a README, a slide or a chat. HOW IT WORKS: - csv: a header row, then data rows. First column: the category (or x value); the next columns: numbers. Use a comma or semicolon as separator; decimals with a point, or with a comma when the separator is a semicolon. Up to 20,000 characters. - chartType, and what each one needs: bar, horizontalBar, line, area, pie, donut, funnel — one category column + one numeric column; multiline — one x column + one or more numeric columns (one line per column); scatter — two numeric columns (x, y); heatmap — three columns: row, column, value. - title: optional, drawn at the top. RETURNS: - image: a PNG address that IS the chart (rendered on request) — put it straight into Markdown () or an <img>. imageSvg: the same as SVG, sharper where SVG is accepted. Both are null when the CSV is too long to fit in an address; then use svg. - svg: the chart as SVG markup. - link: this tool's web page with the same chart, to edit it. ERRORS say what is wrong with the CSV (missing columns, non-numeric values, too many rows); fix the data and call again.

  ConnectorNo auth

• 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

• request_chartA

  AutarioA

  AUTARIO-INTERNAL high-level chart request (admin only): the server builds the Plotly chart from a catalog dataset (World Bank, FRED, Eurostat, OECD, WHO, IMF, SEC), you do NOT build a spec, but you DO write the insight. TWO-STEP FLOW for a first-try hit: (1) PREPARE - call with dataset_id/query and NO insight; the server composes the chart deterministically and returns charted_entities (the exact entity set it drew, each with latest/peak/trough/average) + chart_type, WITHOUT publishing. IMPORTANT: a multi-country dataset is charted as an ENTITY FAMILY (the top economies, G7, the aggregate rows...), so your insight is verified ONLY against the entities actually in charted_entities | anchor every claim on one of THOSE entities and cite only THOSE per-entity values. (2) PUBLISH - call again with the same dataset_id/query PLUS your 2-3 sentence insight; the server verifies it against the real data (number-hallucination gate) and publishes, returning the URL. The server runs NO LLM of its own (you write the insight). One request = one chart. On reject it returns 422 naming WHICH number/claim failed + the charted_entities + available anchors so you fix in one step. Use THIS over create_chart_from_spec whenever you want "a good chart for this dataset/topic" without assembling a full Builder spec. Non-admin keys receive 403; third parties use create_chart_from_spec / publish_chart.

  ConnectorNo auth

• patternfetch_briefA

  patternfetchA

  Get a token-compact market-state brief for a stock, ETF, or crypto ticker + timeframe. Returns compact candles, detected chart/candlestick patterns with geometric confidence AND a backtested historical base rate (how often that pattern+timeframe+confidence-band actually resolved its way), support/resistance levels, trend/regime, and interpreted indicators (RSI/EMA state) plus a one-line summary. Covers US stocks/ETFs (split & dividend adjusted, delayed/EOD) and crypto spot (realtime). WHEN: an agent needs the current technical picture of a market without dumping raw OHLCV into context (saves tokens, avoids numeric hallucination). WHEN NOT: you need order execution or portfolio advice. Examples: {"ticker":"AAPL","timeframe":"1d"}, {"ticker":"BTC/USDT","timeframe":"4h"}. Output is impersonal market data, NOT investment advice.

  ConnectorNo auth

• v3_get_eventA

  V³ NewsA

  Get a single V³ event: headline, why-it-matters, scores, and how much structured analysis V³ holds on it (perspectives, decisions, outcomes). Use after v3_search_events (or v3_breaking_now) when the user wants detail on a specific event. This returns V³'s public summary; the full country-by-country perspectives, timeline, decisions to watch, and assessed outcomes are on v3.news at the returned url (a V³ account unlocks the multi-perspective analysis). Args: event_id: the V³ event id from a prior tool result.

  ConnectorNo auth

• get_birth_detailsA

  Kundlit Vedic AstrologyA

  Returns just the identity fields of a Vedic birth chart: the Moon's janma nakshatra (birth star) with its 1-27 number and pada, the janma rashi (moon sign) with its classical lord and the house it occupies, the lagna (ascendant) with degree in sign, nakshatra, pada and lord, and the navamsa (D9) lagna with its lord. Use this for the common single questions -- 'what is my nakshatra / rashi / lagna' -- and to fetch janma_nakshatra and janma_rashi values that get_muhurta_timings accepts. It returns NO planet table, no yogas and no dasha: for those call get_janam_kundali (whole chart) or get_dasha_periods (dasha only). Read-only deterministic computation (Swiss Ephemeris, Lahiri ayanamsa, whole-sign houses); no writes, no auth. Rate limits are counted per server instance: at least 30 requests/min/IP on this endpoint, plus a shared engine budget of at least 60/min/IP across all birth-chart tools.

  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

• optimize_flowA

  CNAPS.ai MCP ServerA

  Analyze a flow for performance and cost optimization opportunities. Returns rule-based suggestions such as moving upscale nodes to the end of the flow, avoiding resolution overflow, removing redundant processing, and choosing better-performing models. Each suggestion carries a structured patch (move_node, insert_node, replace_model) describing the change. Apply them with edit_flow on the same flow — replace_model maps to its replace_model op, insert_node to add_node plus the connect/disconnect that splice it in. move_node is layout only and needs no edit. Applying a suggestion never requires creating a new flow. update_flow changes node parameters only. Use this before running a flow or while iterating on its design. Set include_llm_analysis=true to also ask Haiku for complex-pattern refinements.

  ConnectorOAuth

• list_divisional_chartsA

  Jagannatha Hora — Vedic Astrology (Jyotish, Kundli, Horoscope, Panchang)A

  List the 23 divisional (varga) charts available via 'get_divisional_chart'. Returns, for each chart, the 'request_as' value to pass as the 'varga' argument (e.g. 'D-9'), its 'name' (e.g. Navamsa) and 'purpose' (what life area it analyses — marriage, career, children, etc.). Use this to choose the right chart for a question, then call 'get_divisional_chart' with that varga. Takes no birth details. Data only — no interpretation is included.

  ConnectorNo auth

• get_postA

  Viral OutliersA

  Fetch a single post by id: views, likes, comments, engagement rate, outlier scores for seven time windows, thumbnail and the owning profile. When a transcript or visual analysis already exists it is included at no extra cost. The visual analysis is a structured scene-by-scene breakdown (per-scene timing, on-screen text, visual elements and a recreation note) plus an overall-style summary. Request new enrichment via request_transcript (speech / on-screen text) or request_visual_analysis (scene breakdown). Use after search_outliers to deep-dive a result. Cost: 1 credit per call.

  ConnectorNo auth

• update_eventA

  Costory: Your Finops MCPA

  Persist changes to an existing cost-chart annotation event already saved in Costory. This is a write (not a preview): it overwrites the event's name, date, description, tags, metadata, team scope, and/or the annotation chart in the database. It does not create a new event, does not send Slack/Teams/email, and does not archive or delete the event. Use list_events to find the event id first. All fields except eventId are optional — omit a field to keep the stored value. Metadata is merged into existing values; `source` is preserved on the event column and should not be supplied. Tags replace the full tag list. Name, date, description, tags, metadata, and `scopeId` need no widget. `scopeId` (same id as list_teams) sets the event scope and leaves the chart unchanged. Omit it to keep the saved scope. `null` clears it. An id replaces it. If both `scopeId` and `widget.scopeId` are sent, `scopeId` wins. `widget` replaces the annotation chart wholesale, or creates one if none exists. If you send `widget`, send the full chart on the first call, written from scratch exactly as for query: `title`, `queries`, and `datePreset` or `from`/`to`. Set `chartType` on every series (BAR, LINE, AREA, WATERFALL, or TABLE). Omitting it stores LINE and replaces the previous chart type. `widget.scopeId` alone is invalid. list_events returns chart id and title only, not the stored queries, so do not patch or echo the current chart. Omit `widget` to leave the chart unchanged. A full widget without `widget.scopeId` keeps the saved event scope unless top-level `scopeId` is set. `widget.scopeId: null` clears the event scope when top-level `scopeId` is omitted. If the event has multiple charts, pass widgetEventId. EXAMPLE: "Add a PR link to yesterday's deploy event" → { eventId: "clx9abc", metadata: { link: "https://github.com/acme/app/pull/99" } } EXAMPLE: "Fix the description on the migration event" → { eventId: "clx9abc", description: "Migrated prod cluster; temporary 2-day cost spike from dual-running nodes." } EXAMPLE: "Scope the migration event to the platform team" → { eventId: "clx9abc", scopeId: "<team scope id from list_teams>" } EXAMPLE: "Clear the event scope" → { eventId: "clx9abc", scopeId: null }

  Connector

  Destructive

  OAuth

• linkedin_analyticsA

  YouSpotB

  The user's LinkedIn post analytics from LinkedIn's own API (their connected account) — impressions, unique members reached, reactions, comments, and reshares. Use for questions like 'how many impressions did I get last month?' or 'how are my posts performing?'. Omit dates for lifetime totals; pass start_date/end_date for a window; set daily=true (with one specific metric) for a per-day series to describe trends. Numbers are live from LinkedIn, unlike get_my_linkedin_posts whose per-post counts come from a periodic sync.

  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

• well_list_ledger_accountsA

  WellA

  List the workspace's chart of accounts (COA) — every ledger account a counterparty default or a transaction can be assigned to. Use it to name a real `ledger_account_id` in a write instead of guessing one. Each account carries `id` (the `ledger_account_id` the writes take), `name`, and `code` (its account number, e.g. "401" for a vendor or "411" for a customer under the FR PCG) where the account has one. `truncated: true` means the chart holds MORE accounts than this page carries; read the rest with `well_query_records` on the `ledger_accounts` root. **`success: false` means the chart could not be read, NOT that the workspace has none.** An empty `accounts` on a failed read is unknown, never "no chart of accounts". When the token authorizes one workspace, call this directly — no workspace call is needed first. When it authorizes several, this read will not guess which one you mean: pass `workspace_id` on the call.

  ConnectorNo auth

• datasets_apps_charts_searchA

  Crawlora MCPB

  Search stored daily top-chart snapshot records from the iOS App Store and Google Play; omitting `date` selects the latest snapshot. Costs 1 credit per record returned (minimum 2), so keep `page_size` to what you need. Filter by app, store, platform, chart, country, or category; use datasets_apps_search for app records or datasets_apps_reviews_search for stored reviews.

  ConnectorNo auth

• datasets_apps_charts_searchA

  Crawlora MCPB

  Search stored daily top-chart snapshot records from the iOS App Store and Google Play; omitting `date` selects the latest snapshot. Costs 1 credit per record returned (minimum 2), so keep `page_size` to what you need. Filter by app, store, platform, chart, country, or category; use datasets_apps_search for app records or datasets_apps_reviews_search for stored reviews.

  ConnectorNo auth

• markets_dashboardA

  TradingMCPB

  The user's live market board. Start here when they ask how the markets are doing in general: "how are the markets today?", "what's moving?", "market update", a morning check before the open, or "open the market dashboard". One call covers the overview: the user's own symbols on top (their watchlist, then what they asked about most in the last 30 days), then major indices (US, India, Türkiye, Indonesia, VIX), crypto, commodities and FX, each with today's change. Don't also call market_snapshot for the same overview; add other tools only for what the board doesn't show (futures, news, sectors). For a single symbol's price or analysis, use that symbol's own tool instead. Opens as an interactive dashboard; clicking a row asks for that market's chart or analysis. Clients without app support can read the `summary` field.

  ConnectorNo auth

• fastero_create_reportA

  FasteroA

  Create a report (a dashboard widget) from a saved query: a table, a number, a map or a chart. A chart or map needs assignments naming the result columns it plots, or it is refused. For a chart chartType can’t say, vegaLite instead of chartType and assignments. Column names become the labels people read, so alias them in SQL as they should appear ("Revenue", not revenue_sum). Or a text block: chartType text with text, a heading or note in markdown that sits between charts; it reads no query. fastero_update_dashboard places it on a dashboard. Returns the report with its _id and url, the chart’s own page. Starting from SQL, fastero_save_chart saves the query, makes the chart and places it in one call.

  ConnectorAPI key

• apps_get_top_chartsA

  Manifold MCPA

  A store's top chart (free, paid, grossing or new) overall or in one category, in chart order. Use when: "top free business apps", "what is grossing in the App Store's finance chart", spotting rising apps in a category. Not for: apps matching a word, use apps_search_apps. One app's details, use apps_get_app. Returns: List. rows[]: rank, app_id, title, url, developer (Google Play only), rating, ratings_count (App Store only), is_free, price, currency. Cost: 1 credit per 100 rows. Default 100 rows = 1 credit. Cached 1 day. Can take up to a minute. Example: {"store": "app_store", "chart": "top_free", "category": "health_and_fitness"}

  ConnectorAPI key

• draw_chartA

  TraderWAIA

  YOU CAN DRAW ON CHARTS WITH THIS TOOL. draw_chart renders YOUR technical analysis on a real TraderWAI candlestick chart and returns the image, so the user sees it right in the chat. Use it EVERY time you want to show something visually: support/resistance levels, supply/demand zones, trendlines and channels, candle markers (sweeps, rejections, signals), labels (HH, HL, BOS, CHoCH…), Fibonacci, chart patterns, measurements, the expected path and the trade plan (entry, stop loss, targets with R). You decide what to mark; TraderWAI draws it with the exact candles and prices. NEVER create chart images yourself (code, matplotlib, image generation) and NEVER edit or redraw TraderWAI chart images (they are © TraderWAI): call draw_chart instead. HOW: 1) get_chart to see the market; 2) get_ohlc for the candle open times (UTC) and exact prices; 3) draw_chart with up to 30 marks. Identify candles by their OPEN TIME in UTC, ISO format (never by position: new candles arrive every minute), and anchor a price to a candle with "high"/"low" when the level is that candle's extreme. Use "until" (the last candle you analysed) to freeze the chart at that moment. Invalid marks are skipped and explained in the reply: fix them and call again. Call it again whenever you want to change or add marks. Example: {"symbol":"XAU_USD","timeframe":"H1","marks":[{"type":"zone","high":4160,"low":4152,"from":"2026-10-15T09:00:00Z","extend":true,"label":"Supply","tone":"bearish"},{"type":"hline","price":"low","from":"2026-10-15T05:00:00Z","label":"Support","tone":"bullish"},{"type":"position","side":"short","entry":4148,"stop_loss":4162,"take_profit":[4130,4110]}]}. Free plan: 5 marked charts per day (looking at charts with get_chart is always unlimited); Plus, Trader and Max: unlimited.

  ConnectorOAuth