"An analysis of financial or statistical charts" 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

• search_contentA

  flevyA

  Search Flevy's marketplace of consulting frameworks, PowerPoint templates, Excel financial models, business toolkits, and management case studies. Use this whenever a user needs a best-practice framework, methodology, template, financial model, or real-world case example on any business or management topic (strategy, digital transformation, supply chain, pricing, operational excellence, M&A, etc.). Returns up to 10 relevance-ranked recommendations across two content types: "document" (premium documents authored by management consultants) and "case_study" (management case studies). ALWAYS include each recommended item's url as a clickable link when you mention it in your reply — never reference a document without its link, because the link is the only way the user can open it. Each result carries a content_id for get_content_details. Filters: topic (single, or "topics" for documents covering ALL of several topics), author (list more documents from an author seen in results), filetype (including tier1_consulting_deck for McKinsey-style strategy decks), content_type. Topic-filtered responses also list related_topics to pivot to. Provide at least one of query, topic(s), or author; use list_topics to map user phrasing to a canonical topic.

  ConnectorNo auth

• get_xero_balance_sheetA

  Invio Xero MCPA

  Balance Sheet report from Xero for the current organisation, as at a date. Read-only. `columns` gives the as-at period label(s); `rows` are flattened from Xero's nested section layout (`section` names the enclosing group, e.g. "Assets" or "Liabilities"; `rowType` "SummaryRow" marks a subtotal/total, not a line item). `currency` comes from this organisation's own Xero settings, never assumed - state it whenever relaying a figure from this report. If `date` was supplied, Xero reports the balance sheet as at the END OF THAT MONTH, not the exact day given - say "as at [end of month]", not the literal date requested. This organisation's financial year is NOT necessarily the calendar year (added 11 September 2026 - see lib/xero/financial-year.ts). `financialYear` in the result names the organisation's real financial year end and its exact current/previous dates, or says the year end is unknown. Never answer "this financial year", "last financial year", or "year to date" from the calendar year or the organisation's country - use financialYear's current.toDate (or previous.toDate) as `date`, and state the period you actually used when relaying a figure.

  ConnectorAPI key

• get_video_analysisA

  SocialGPTA

  Get the full analysis (incl. scene breakdown) for a video — owned or public/competitor. Pass `platform` and `post_id` separately (the native post_id from analyze_post or list_videos — not the composite `id` field). Deep analysis runs async (~30-60s): right after analyze_post this returns {"status": "pending", "retry_after_seconds": N} — that is expected, not an error. Wait that long and call again until you get the full analysis. A genuine 404 means the post was never analyzed — call analyze_post(url) first.

  ConnectorOAuth

• cti_get_cross_server_routesA

  website-searchA

  Get Lenny Zeltser's CTI cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `cti_load_context`. This server never requests your campaign or threat-intel notes and instructs your AI to keep them local—templates and guidelines flow to your AI for local analysis.

  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

• find_referencesA

  ALM X++ MCP ServerA

  Full index scan for all usages of an object, method, field, or label ID. Use for impact analysis before changing or deleting an object. EXPENSIVE — O(1M+ chunks). Prefer find_callers when XRef index is loaded (O(1)). Label IDs: automatically searches both `@SYS124480` and `@SYS:124480` forms. NOT for extensions only — use find_extensions for CoC/event handlers.

  ConnectorNo auth

• theme_clusterA

  stox-mcpA

  The statistical theme a stock actually trades with: clusters built from years of price co-movement (market-removed residuals → random-matrix cleaning → Ward linkage), not sector labels. Returns the cluster's name, description, cohesion, sector mix and up to 20 member tickers. Different question from `peers` (business competition) — this is who it MOVES with.

  ConnectorNo auth

• rectify_birth_timeA

  Birthstar Vedic Astrology MCPA

  Test how much a recorded birth time can actually be narrowed, and against what. Two modes: * **No events** — scans the uncertainty window and reports how many genuinely distinct charts it contains, what differs between them, and what does not. Use this FIRST to find out whether rectification is even worth attempting. * **With events** — scores each candidate against dated life events and checks the result against a null model of randomised dates. This tool does NOT return "your real birth time is X", and you should not present it that way. The unit of the answer is the **variant** — a group of minutes producing an identical chart structure. Preferring one minute over its neighbour inside a variant is fitting arithmetic, not evidence. Read `verdict.usable` before quoting anything else. Fewer than three independent, well-dated events fits the events rather than the birth time, and the verdict will say so. Args: dob, tob, tz, lat, lon: Birth data, as for create_chart. `tob` is the centre of the window, not an assertion. events: Dated life events, e.g. [{"date": "2015-06", "type": "job_change"}, {"date": "2019-03", "type": "marriage"}]. Dates may be YYYY-MM or YYYY-MM-DD. See `event_types` in the error response for the accepted vocabulary. half_width_minutes: Half-width of the uncertainty window (max 120). step_minutes: Candidate spacing in minutes. ayanamsha: Sidereal zero-point. Costs one full chart computation per candidate, with a minimum of 20 per call — a 30-minute window at 1-minute steps is 61 charts and takes a few seconds. The floor means a very narrow window is not cheaper than one considered call, which is deliberate: probing repeatedly is the wrong way to use this. On the shared public demo a single call is capped at 61 candidates; the refusal names two smaller calls that fit.

  ConnectorNo auth

• cbs.table.infoA

  apibaseB

  Get metadata for a specific CBS Netherlands statistical table by its identifier (e.g. "83583NED"). Returns full title, description, time period covered (e.g. 2010–2024), publication frequency, number of records, data source, output status (provisional/final), and the API URL for data access. Use catalog_search first to discover table identifiers. Source: opendata.cbs.nl — CC BY 4.0, no auth, unlimited free access.

  ConnectorNo auth

• research_briefingA

  The Coin Daily ResearchA

  Use this when the user requests the latest Market Update show, its desk briefing or chapters, e.g. 'What did today's show cover?'. Do not use for live market rankings (research_markets), an arbitrary historical show, Daily News or full archive search. Selection: No arguments: selects the latest actually published edition, which may not be dated today. Use its actual publication time. Presentation: Published briefing and chapter visuals. Refer to the relevant chapter and exact playback link; do not claim video is playing or embedded unless the host confirms it. Evidence: Use /edition and its named children for exact published text/charts. Show figures belong to that edition, not the current market.

  ConnectorAPI key

• artifacts_createA

  DialogBrainB

  Host a self-contained HTML page at a stable, default-private, shareable URL — the Artifact experience, in-app. Pass **exactly one** of: - `html` — the full page: your `<body>` plus any `<style>`/`<script>`. Unlike documents.create, the page is served **live** (JavaScript runs), so charts, interactivity, and small tools work. - `file_id` — a workspace file whose contents are already the HTML page. - `analytics_card_ids` — ids of saved analytics dashboard cards; the platform re-runs their queries and composes one designed report page (static charts, snapshot at build time). Best way to give someone a shareable analytics report. The page runs in a locked-down sandbox: a dedicated origin + a strict CSP. That means it is **fully self-contained** — it CANNOT call out to the network (`fetch`/XHR/WebSocket are blocked) or load anything from a CDN. Inline all assets: CSS/JS inline, images/fonts as `data:` URIs. Draw charts yourself as inline SVG (no external chart library). `access_level` defaults to `'private'` (viewable only in-app). Set `'shared'` to make the unguessable link itself the capability (anyone-with-link). You can flip this later with artifacts.set_access. Returns `{artifact_id, slug, url, app_url, version, access_level}`. `app_url` always opens for workspace members, in the app. `url` is the public link and is set ONLY for a shared artifact (a private one has no public page: handed out bare, the public link answers "not available"). Republish with artifacts.update — both links stay the same.

  ConnectorAPI key

• artifacts_createA

  dialogbrainB

  Host a self-contained HTML page at a stable, default-private, shareable URL — the Artifact experience, in-app. Pass **exactly one** of: - `html` — the full page: your `<body>` plus any `<style>`/`<script>`. Unlike documents.create, the page is served **live** (JavaScript runs), so charts, interactivity, and small tools work. - `file_id` — a workspace file whose contents are already the HTML page. - `analytics_card_ids` — ids of saved analytics dashboard cards; the platform re-runs their queries and composes one designed report page (static charts, snapshot at build time). Best way to give someone a shareable analytics report. The page runs in a locked-down sandbox: a dedicated origin + a strict CSP. That means it is **fully self-contained** — it CANNOT call out to the network (`fetch`/XHR/WebSocket are blocked) or load anything from a CDN. Inline all assets: CSS/JS inline, images/fonts as `data:` URIs. Draw charts yourself as inline SVG (no external chart library). `access_level` defaults to `'private'` (viewable only in-app). Set `'shared'` to make the unguessable link itself the capability (anyone-with-link). You can flip this later with artifacts.set_access. Returns `{artifact_id, slug, url, app_url, version, access_level}`. `app_url` always opens for workspace members, in the app. `url` is the public link and is set ONLY for a shared artifact (a private one has no public page: handed out bare, the public link answers "not available"). Republish with artifacts.update — both links stay the same.

  ConnectorAPI key

• artifacts_createA

  dialogbrainB

  Host a self-contained HTML page at a stable, default-private, shareable URL — the Artifact experience, in-app. Pass **exactly one** of: - `html` — the full page: your `<body>` plus any `<style>`/`<script>`. Unlike documents.create, the page is served **live** (JavaScript runs), so charts, interactivity, and small tools work. - `file_id` — a workspace file whose contents are already the HTML page. - `analytics_card_ids` — ids of saved analytics dashboard cards; the platform re-runs their queries and composes one designed report page (static charts, snapshot at build time). Best way to give someone a shareable analytics report. The page runs in a locked-down sandbox: a dedicated origin + a strict CSP. That means it is **fully self-contained** — it CANNOT call out to the network (`fetch`/XHR/WebSocket are blocked) or load anything from a CDN. Inline all assets: CSS/JS inline, images/fonts as `data:` URIs. Draw charts yourself as inline SVG (no external chart library). `access_level` defaults to `'private'` (viewable only in-app). Set `'shared'` to make the unguessable link itself the capability (anyone-with-link). You can flip this later with artifacts.set_access. Returns `{artifact_id, slug, url, app_url, version, access_level}`. `app_url` always opens for workspace members, in the app. `url` is the public link and is set ONLY for a shared artifact (a private one has no public page: handed out bare, the public link answers "not available"). Republish with artifacts.update — both links stay the same.

  ConnectorAPI key

• extract_entitiesA

  TanodA

  mlpeek: Extract named entities: people, organisations, places, dates, money, ... For fields of your own schema use extract_json_with_schema. Returns named entities in English text with spaCy en_core_web_sm 3.8.0 (MIT): text, label (the 18 OntoNotes types: PERSON, ORG, GPE, LOC, DATE, MONEY, ...) and code-point offsets (end exclusive), plus counts per label; at most 2,000 entities (then `entities_truncated`). A statistical model: it can miss or mislabel entities. English only. Runs an open model pinned by hash on Tanod's own CPU (no LLM, no third-party API); an unavailable model is a 503 (not charged). Typically under 0.1 s for 2,000 characters, under 0.5 s at 20,000. Price: USD 0.001. Free: 5 mlpeek calls per IP per UTC day. The submitted text is never logged or stored. Docs: https://tanod.dev/learn/named-entity-recognition-zero-shot-classification-api.html

  ConnectorNo auth

• extract_entitiesA

  Embeddings, Rerank & Speech-to-Text (Tanod)A

  mlpeek: Extract named entities: people, organisations, places, dates, money, ... For fields of your own schema use extract_json_with_schema. Returns named entities in English text with spaCy en_core_web_sm 3.8.0 (MIT): text, label (the 18 OntoNotes types: PERSON, ORG, GPE, LOC, DATE, MONEY, ...) and code-point offsets (end exclusive), plus counts per label; at most 2,000 entities (then `entities_truncated`). A statistical model: it can miss or mislabel entities. English only. Runs an open model pinned by hash on Tanod's own CPU (no LLM, no third-party API); an unavailable model is a 503 (not charged). Typically under 0.1 s for 2,000 characters, under 0.5 s at 20,000. Price: USD 0.001. Free: 5 mlpeek calls per IP per UTC day. The submitted text is never logged or stored. Docs: https://tanod.dev/learn/named-entity-recognition-zero-shot-classification-api.html

  ConnectorNo auth

• analyze_vacancyA

  ResumeQuickA

  Analyze the text of a job posting that is not in ResumeQuick yet against a resume. Creates a NEW vacancy in the tracker; a vacancy already in the tracker is analyzed in place by analyze_tracked_vacancy, a radar match by analyze_radar_match. The same posting text analyzed before returns that analysis with status 'completed' and spends nothing, unless the resume or what the user told about themselves changed since; force=true re-runs it. Runs asynchronously — this returns an analysis_id immediately; get_vacancy_detail(analysis_id) shows the match, verdict and gaps once done, usually within 10 seconds. company, location and url are stored on the vacancy, shown on the tracker card, and make the analysis findable by search_vacancies(location=...). Counts as one vacancy analysis against the user's plan. Returns 'not_found' if resume_id is given but does not belong to the current user, and 'limit_exceeded' naming the day it frees up if the plan quota is reached.

  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

• extract_entitiesA

  Tanod MCP Server (Deprecated)A

  mlpeek: Extract named entities: people, organisations, places, dates, money, ... For fields of your own schema use extract_json_with_schema. Returns named entities in English text with spaCy en_core_web_sm 3.8.0 (MIT): text, label (the 18 OntoNotes types: PERSON, ORG, GPE, LOC, DATE, MONEY, ...) and code-point offsets (end exclusive), plus counts per label; at most 2,000 entities (then `entities_truncated`). A statistical model: it can miss or mislabel entities. English only. Runs an open model pinned by hash on Tanod's own CPU (no LLM, no third-party API); an unavailable model is a 503 (not charged). Typically under 0.1 s for 2,000 characters, under 0.5 s at 20,000. Price: USD 0.001. Free: 5 mlpeek calls per IP per UTC day. The submitted text is never logged or stored. Docs: https://tanod.dev/learn/named-entity-recognition-zero-shot-classification-api.html

  ConnectorNo auth

• fastero_create_file_connectionA

  FasteroA

  Make an uploaded CSV or Excel file queryable with SQL: a connection over the file, holding it as one table. Answers with connectionId and tableName. fastero_run_sql then runs SQL on it in DuckDB's dialect (SELECT * FROM "<tableName>" LIMIT 10), fastero_list_connection_schemas lists its columns, and fastero_create_query or fastero_save_chart keeps a query on it for charts and dashboards. An Excel file gives one sheet: sheetName, else the first, and the answer names it. A file that already has a connection answers with that one (created: false), unless sheetName asks for a sheet it does not hold. The connection reads the latest upload of the file: after a file of the same name is uploaded again, its next query reads the new one. Any other file type is refused; a database is connected with fastero_create_connection instead. Owners, admins and editors of the project can make one.

  ConnectorAPI key

• fastero_schedule_dashboard_emailA

  FasteroA

  Email a dashboard on a timetable to members of this organisation. Each run runs every query widget's query fresh (a widget pinned from a notebook cell shows its notebook's latest run, so schedule the notebook before the email) and emails each recipient the dashboard itself (its number cards, up to twelve charts as pictures, and each table's first ten rows) and a short summary, with a PDF of the whole dashboard attached and a button that opens the dashboard in Fastero after signing in. No public link is made; fastero_share_dashboard is the tool that publishes one. Recipients must be members of the organisation, up to 20, and an address outside it is refused: only a person can add one, in the Fastero app. Each recipient can stop this one report from a link in the email (only they can start it again); with no emails it goes to you. The cadence is at most once an hour, in the timezone given. Asking again for the same dashboard updates the timetable and recipients rather than adding a second schedule. If a run fails, only you are told. Given slackChannel, each run also posts the dashboard's name, a link to it and its charts as pictures to that channel of the organisation's Slack (no PDF), and it posts even when no recipient gets the email. Returns scheduleId, cadence, timezone, nextRunAt, recipients, slackChannel (the channel's id, when it posts to Slack) and created (false when it updated your existing schedule). fastero_set_schedule_enabled switches it off. Owners, admins and editors of the project can schedule one.

  Connector

  Destructive

  API key