"Financial models for trading stocks, puts and calls" matching MCP tools:

• compare

  XFMS — Xpansion Framework Model Source

  Run a live A/B test between 2–5 user-specified models for a stated purpose. NO ranking step — the supplied model_ids ARE the candidate set. Generates 5 representative test queries from the purpose, runs them through every named model in parallel, and returns real cost, latency, and plain-English commentary on who won what. Unknown IDs are dropped with a note; if fewer than 2 IDs resolve, the call refuses. Use this whenever the user names specific models to compare (e.g. 'A/B test X and Y'). For engine-chosen candidates, use `benchmark` instead. Costs more than `rank` (10+ live LLM calls). Free-tier note: when any candidate ends in ':free', the probe is capped at 3 queries (no adaptive expansion) because free-tier rate limits often push longer probes past the deploy's 5-minute ceiling — evidence will be shallower. The commentary surfaces this when it happens.

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• wash_check

  Name Whisper — ENS Intelligence Layer

  Assess whether an ENS name's sale(s) are WASH TRADING / fake / self-dealt / manipulated volume. THE tool for any "is this wash trading?", "is the sale history of X suspicious/fake/real?", "are these trades legit?", "is someone wash-trading this name?" question — route straight here, do NOT use get_name_details or get_market_activity for that (those return sale rows but make NO wash-trading judgment; only this tool scores it). Just pass `label` — the bare ENS name (e.g. "437", "coffee") is enough; the tool pulls that name's recent sale and analyzes it on demand. `tx_hash`, `buyer`, `seller`, `price_eth` are OPTIONAL enrichment for a specific sale — never block on them or ask the user for them. Returns a wash confidence score (0-1), a label (clean/suspicious/likely_wash), the detected signals (shared-funder, mint-flip, round-trip, fresh-wallet, cluster overlap…), seller profile, and a plain-English summary.

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• benchmark

  XFMS — Xpansion Framework Model Source

  Run a live A/B test against the engine's TOP 3 PICKS for a stated purpose — the engine chooses the candidates from the full catalog. Generates 5 representative test queries (auto-expands to 10 or 15 if results are too close to call), runs them through the picked models in parallel, and returns real cost, latency, and plain-English commentary on who won what. Use AFTER `pick` or `rank` when the user wants the engine's own picks stress-tested with live data. DO NOT use this when the user has already named specific candidate models — the engine will ignore the names and test its own picks. Use `compare` instead in that case. Costs more than `rank` (15+ live LLM calls).

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• api_info

  x402 Crypto Market Structure

  REST API access for autonomous agents — pricing, quick start, and migration guide. Call this when: building a trading bot, deploying an autonomous agent, hitting the MCP rate limit, or running 24/7 without a human in the loop. The MCP tier (what you're using now) is free via Smithery, rate-limited to 60 calls/minute per IP, and good for testing. The REST API is for production: pay per call in USDC; paid endpoints are rate-limited to 60 calls/minute and 200 calls/hour per wallet. No API key required.

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• get_market_schedule

  Headless Oracle

  Returns holiday-aware trading session schedule with next open/close UTC timestamps for any of 28 exchanges. Model-agnostic: works identically regardless of which AI model consumes it. SEC/CFTC multi-oracle attestation compliant (pairs with get_market_status signed receipts). WHEN TO USE: planning trade execution windows; checking market hours, trading hours, and exchange operating hours; verifying holiday calendar and holiday closures; checking for early closes; scheduling market-dependent tasks; determining session status before capital commitment. Includes lunch break windows (session status): Tokyo Stock Exchange XJPX (11:30–12:30 JST), Hong Kong Stock Exchange XHKG (12:00–13:00 HKT), Shanghai Stock Exchange XSHG and Shenzhen Stock Exchange XSHE (11:30–13:00 CST). Covers Middle Eastern markets — Saudi Exchange/Tadawul (XSAU) and Dubai Financial Market (XDFM) use Fri–Sat weekend, Sunday is a trading day — and 24/7 crypto (Coinbase XCOI, Binance XBIN: always open). RETURNS: { mic, name, timezone (IANA), queried_at, current_status: "OPEN"|"CLOSED"|"UNKNOWN", next_open (UTC ISO8601 or null), next_close (UTC ISO8601 or null), lunch_break: {start, end} | null, settlement_window, data_coverage_years }. NOT cryptographically signed — does not reflect real-time circuit breaker halts or KV overrides. For authoritative signed status use get_market_status. Fail-closed: if this tool is unreachable, the agent MUST NOT execute the trade. LATENCY: sub-100ms p95 (pure schedule computation, no signing).

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• benchmark

  XFMS — Model Source

  Run a live A/B test against the engine's TOP 3 PICKS for a stated purpose — the engine chooses the candidates from the full catalog. Generates 5 representative test queries (auto-expands to 10 or 15 if results are too close to call), runs them through the picked models in parallel, and returns real cost, latency, and plain-English commentary on who won what. Use AFTER `pick` or `rank` when the user wants the engine's own picks stress-tested with live data. DO NOT use this when the user has already named specific candidate models — the engine will ignore the names and test its own picks. Use `compare` instead in that case. Costs more than `rank` (15+ live LLM calls).

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• compare

  XFMS — Model Source

  Run a live A/B test between 2–5 user-specified models for a stated purpose. NO ranking step — the supplied model_ids ARE the candidate set. Generates 5 representative test queries from the purpose, runs them through every named model in parallel, and returns real cost, latency, and plain-English commentary on who won what. Unknown IDs are dropped with a note; if fewer than 2 IDs resolve, the call refuses. Use this whenever the user names specific models to compare (e.g. 'A/B test X and Y'). For engine-chosen candidates, use `benchmark` instead. Costs more than `rank` (10+ live LLM calls). Free-tier note: when any candidate ends in ':free', the probe is capped at 3 queries (no adaptive expansion) because free-tier rate limits often push longer probes past the deploy's 5-minute ceiling — evidence will be shallower. The commentary surfaces this when it happens.

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• get_market_activity

  Name Whisper — ENS Intelligence Layer

  Get recent ENS marketplace activity — sales, new listings, offers, mints, transfers, renewals, and burns. Filter by event type. Returns event details including name, price (in ETH), buyer/seller addresses, and timestamp. Sorted by most recent first. This is raw activity only — it makes NO wash-trading / authenticity judgment; for "is this wash trading / fake volume?" use wash_check.

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• search_card_sales

  Pulltrader Seller Economics

  Return a capped sample of recent comparable SOLD listings for a trading card (price + sale date), plus a market snapshot (median, range, sample size). Use this when a user asks 'what is this card selling for', 'recent sales', or 'comps'. Accepts a natural-language `query` or a structured `item`. Figures are estimates from recent sales and exclude fees/taxes/shipping; this is not financial advice and does not place orders. Trading cards only.

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• get_vendor_incidents

  Huntertech.io Vendor Insights

  Get vendor incident and outage status for one monitored vendor (for example solarwinds, zscaler, cloudflare). Anonymous calls return only ongoing or monitoring incidents. Authenticated calls can request resolved history within the user plan window.

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• screener

  Stock Market Data MCP

  Screen the tracked large-cap universe by market cap, trailing P/E, dividend yield, and sector — returns matching stocks ranked by market cap. A raw market-data filter; for a ranked, fundamentals-driven screen pair this with financial-signals-mcp's composite_value_score. PAID: $0.01 USDC per query after a daily free allowance. On a 402, pay the returned Solana memo and re-call with the SAME args plus payment_tx=<signature>. An Authorization: Bearer fnet_ key bypasses payment.

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• list-models

  Roundtable

  List available AI models grouped by thinking level (low/medium/high). Shows default models, credit costs, capabilities for each tier. Use this before consult to understand model options.

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• get_market_schedule

  headless-oracle

  Returns holiday-aware trading session schedule with next open/close UTC timestamps for any of 28 exchanges. Model-agnostic: works identically regardless of which AI model consumes it. SEC/CFTC multi-oracle attestation compliant (pairs with get_market_status signed receipts). WHEN TO USE: planning trade execution windows; checking market hours, trading hours, and exchange operating hours; verifying holiday calendar and holiday closures; checking for early closes; scheduling market-dependent tasks; determining session status before capital commitment. Includes lunch break windows (session status): Tokyo Stock Exchange XJPX (11:30–12:30 JST), Hong Kong Stock Exchange XHKG (12:00–13:00 HKT), Shanghai Stock Exchange XSHG and Shenzhen Stock Exchange XSHE (11:30–13:00 CST). Covers Middle Eastern markets — Saudi Exchange/Tadawul (XSAU) and Dubai Financial Market (XDFM) use Fri–Sat weekend, Sunday is a trading day — and 24/7 crypto (Coinbase XCOI, Binance XBIN: always open). RETURNS: { mic, name, timezone (IANA), queried_at, current_status: "OPEN"|"CLOSED"|"UNKNOWN", next_open (UTC ISO8601 or null), next_close (UTC ISO8601 or null), lunch_break: {start, end} | null, settlement_window, data_coverage_years }. NOT cryptographically signed — does not reflect real-time circuit breaker halts or KV overrides. For authoritative signed status use get_market_status. Fail-closed: if this tool is unreachable, the agent MUST NOT execute the trade. LATENCY: sub-100ms p95 (pure schedule computation, no signing).

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• atlas_list_custom_eval_models

  CareerProof MCP

  List all custom evaluation models for the authenticated user. Returns an array of model objects with id, name, description, and status. Use model id in artifact, rubric, and evaluation tools. Free.

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• discover

  XFMS — Model Source

  Show which quality dimensions matter for a stated purpose, WITHOUT ranking any models. Returns the inferred weights and the discovery-walk trace. Useful for understanding how XFMS interprets the purpose before committing to a pick.

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• agent_economy_brief

  invinoveritas

  Latest 6h agent-economy research brief: MCP servers, arxiv papers, trending GitHub agent repos, and trending HuggingFace models, with specific names cited. Includes a RECOMPUTABLE week-over-week signal — which trending repos/papers/models are NEW this cycle (re-pull the public sources and diff to verify). Refreshes every 6h.

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• estimate_llm_cost

  IA-QA — 130+ QA & Dev Tools for AI Agents

  Estimate the API cost in USD for a given model and token counts. Supports all major 2024–2026 models: GPT-4o, GPT-4.1, o3, o4-mini, Claude Opus 4, Claude Sonnet 4/4.5, Gemini 2.5 Pro/Flash, DeepSeek V3/R1, Grok 3, and legacy models.

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• get_symbol_context

  Stocklake — AI Stock Intelligence

  Full research context for a symbol in one call — fundamentals, AI summary, news, sentiment, and discovery status. Replaces 5 separate calls: get_stock + get_stock_ai_summary + get_stock_news + get_sentiment_profile + get_discovery_ideas (for one symbol). Returns: - stock: price, name, sector, rsi, pe_forward, market_cap, 52-week range, analyst data - ai_summary: verdict, confidence, flag_score, full summary, key_points, risks - news: last 3 high-relevance articles (title, published_at, ai_sentiment, ai_flag_score, ai_summary) - sentiment: signal, confidence, insider_trend (buying/selling/neutral), institutional_pct - discovery: active discovery idea for this symbol, if any (direction, conviction, rationale) All data is pre-computed by the Stocklake AI pipeline — no live AI calls on request. Pro tier only. For informational purposes only. Not financial advice.

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• options-snapshot

  The Stall

  Options intelligence snapshot for any US equity — IV30, put/call volume ratio, top calls and puts by trading volume, and unusual-volume flags. Free CBOE delayed data (15-min delay during trading hours), no API key required. Complements us-stock-price and equity-technicals with the options-layer sentiment layer agents need for complete trade context. $0.015/call.

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• get_iv_radar

  hpsilab-mcp

  Implied-volatility (IV) structure for a stock: how expensive options are, whether volatility is being squeezed, and whether traders are paying up for upside (calls) or downside (puts). Available to all signed-in users. Args: ticker: Stock symbol, e.g. "NVDA". refresh: Bypass the backend's fresh IV cache and request the latest option-chain pull. Defaults to False.

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