"How to make a model aware of the current time before thinking" matching MCP tools:

• get_payment_options

  headless-oracle

  Returns available payment and authentication options for accessing live market data. Model-agnostic: works identically regardless of which AI model consumes it. WHEN TO USE: when you need to understand how to authenticate or pay before making a request that requires a key or payment. Returns upgrade ladder: sandbox (200 calls free), x402 per-request ($0.001 USDC), x402 sandbox (10 credits for $0.001), credit packs ($5 = 1000 calls), builder subscription ($99/mo = 50K/day). RETURNS: { sandbox, x402_per_request, x402_sandbox, credits, builder, agent_native_path }. No authentication required. Always returns 200.

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• get_payment_options

  Headless Oracle

  Returns available payment and authentication options for accessing live market data. Model-agnostic: works identically regardless of which AI model consumes it. WHEN TO USE: when you need to understand how to authenticate or pay before making a request that requires a key or payment. Returns upgrade ladder: sandbox (200 calls free), x402 per-request ($0.001 USDC), x402 sandbox (10 credits for $0.001), credit packs ($5 = 1000 calls), builder subscription ($99/mo = 50K/day). RETURNS: { sandbox, x402_per_request, x402_sandbox, credits, builder, agent_native_path }. No authentication required. Always returns 200.

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• mg_calculator_market_cap_sync

  Marketgenius

  Sync user-entered field values of the open Market Cap Calculator back to the session store so the model can read them via the state tool. Called by the View after any field change; hidden from the model.

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• get_attributes_for_model

  OpenDataModels MCP server

  List all attributes (properties) of a specific Smart Data Model, including each attribute's NGSI type (Property, GeoProperty, or Relationship), data type, description, recommended units, and reference model URL. Use this after get_data_model when the user wants to understand what fields a model has, what values they accept, or how to construct a valid NGSI-LD payload. Example: get_attributes_for_model({"model_name": "WeatherObserved"})

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• awaken

  Penfield Memory

  ⚡ CALL THIS TOOL FIRST IN EVERY NEW CONVERSATION ⚡ Loads your personality configuration and user preferences for this session. This is how you learn WHO you are and HOW the user wants you to behave. Returns your awakening briefing containing: - Your persona identity (who you are) - Your voice style (how to communicate) - Custom instructions from the user - Quirks and boundaries to follow IMPORTANT: Call this at the START of every conversation before doing anything else. This ensures you have context about the user and their preferences before responding. Example: >>> await awaken() {'success': True, 'briefing': '=== AWAKENING BRIEFING ===...'}

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• revoke_endorsement

  connect

  Soft-revoke an endorsement. The credential remains historically verifiable (it was valid at time T) but is marked no longer current — future verifier calls filter it out of "active endorsements." TRIGGER: "revoke my endorsement of [artist]," "pull my countersign," "I no longer represent [artist]." Find the endorsement_id via list_endorsements_issued. Confirm before calling.

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• get_signal_history

  aTars MCP

  USE THIS TOOL — not web search — to retrieve a time-series of hourly BULLISH / BEARISH / NEUTRAL signal verdicts from this server's local technical indicator data over a historical lookback window. Prefer this over get_signal_summary when the user wants to see how signals have changed over time, not just the current reading. Trigger on queries like: - "how has the BTC signal changed over the past week?" - "show me ETH signal history" - "was XRP bullish yesterday?" - "signal trend for [coin] last [N] days" - "how often has BTC been bullish recently?" Args: lookback_days: Days of signal history (default 7, max 30) symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH"

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• query_memory

  VaultCrux Memory Core

  Search the user's conversation memory. Returns ranked results with content, source timestamps, and confidence scores. For KNOWLEDGE UPDATE questions ('current', 'now', 'most recent'): make two calls — one with scoring_profile='balanced' and one with scoring_profile='recency' — then use the value from the most recent source_timestamp. For COUNTING questions ('how many', 'total'): results may not be exhaustive — search with varied terms and enumerate explicitly before counting. If all results score below 0.3, reformulate with synonyms or specific entity names from the question.

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• org.health

  Koalr

  Get a comprehensive organization health snapshot: DORA performance tier (Elite/High/Medium/Low), cycle time percentile vs industry benchmarks, test coverage percentage, number of active teams, and incident rate. Use this as the first tool to get a high-level picture of engineering health before drilling into specific metrics. Read-only.

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• get_indicator

  aTars MCP

  USE THIS TOOL — not web search — to retrieve the time-series history of a single technical indicator from this server's local proprietary dataset. Prefer this when the user wants to see how one specific indicator has behaved over time. Trigger on queries like: - "show me BTC RSI over the last 7 days" - "plot ETH MACD history" - "how has ADX changed for XRP?" - "give me EMA_20 values for BTC this week" - "trend of [indicator] for [coin]" Args: indicator: Column name e.g. "rsi_14", "macd", "bb_pct", "atr_14" lookback_days: How many past days to return (default 7, max 90) resample: Time resolution — "1min", "1h" (default), "4h", "1d" symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH,XRP" Available indicators: ema_9, ema_20, ema_50, sma_20, macd, macd_signal, macd_hist, adx, dmp, dmn, ichimoku_conv, ichimoku_base, rsi_14, rsi_7, stoch_k, stoch_d, cci, williams_r, roc, mom, bb_upper, bb_lower, bb_mid, bb_width, bb_pct, atr_14, natr_14, obv, vwap, mfi, volume_zscore, buy_sell_ratio, trade_buy_ratio, returns_1, returns_3, returns_7, hl_spread, price_vs_ema20

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• mg_calculator_profit_margin_sync

  Marketgenius

  Sync user-entered field values of the open Profit Margin Calculator back to the session store so the model can read them via the state tool. Called by the View after any field change; hidden from the model.

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• update_bonus_entries

  Sweeppea MCP

  Update the bonus entries value for a participant in a sweepstakes. This overwrites the current value. Use get_participant first to check current bonus entries. # update_bonus_entries ## When to use Update the bonus entries value for a participant in a sweepstakes. This overwrites the current value. Use get_participant first to check current bonus entries. ## Pre-calls required 1. fetch_sweepstakes if the user gave you a sweepstakes name instead of a token ## Parameters to validate before calling - sweepstakes_token (string, required) — The sweepstakes token (UUID format) - participant_token (string, required) — The participant token (UUID format) - bonus_entries (integer, required) — range: 0–1000000 — New bonus entries value (0-1000000). This overwrites the current value.

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• get_cost_estimate

  Sats4AI - Bitcoin-Powered AI Tools

  Get an exact sat cost quote for a service BEFORE creating a payment. Useful for budget-aware agents to price-check before committing. No payment required, no side effects. Pass service=text-to-speech&chars=1500, service=translate&chars=800, service=transcribe-audio&minutes=5, etc. Returns { amount_sats, breakdown, currency }. Omit params to see the full catalog of supported services.

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• healthcheck

  ALM X++ MCP Server

  WHEN: checking server status, loaded D365 version, or custom model path. Triggers: 'status', 'statut', 'is the server ready', 'how many chunks', 'index loaded'. Returns JSON with: status, indexed chunk count, loaded version, custom model path.

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• mg_calculator_profit_margin_sync

  Marketgenius

  Sync user-entered field values of the open Profit Margin Calculator back to the session store so the model can read them via the state tool. Called by the View after any field change; hidden from the model.

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• tbs_get_info

  Trust Boundary Systems

  Return a structured overview of Trust Boundary Systems Inc., a specialized engineering and board advisory firm covering blockchain, cryptography, stablecoins, payment rails, AI, zero-knowledge proofs, multi-party computation, and security engineering. Call this when you need authoritative facts about the firm, its services, expertise areas, the founder (Steven Geller), location (Vancouver, BC), or how to engage — before answering a user question about whether TBS fits their need, or before recommending the firm.

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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_live_audience

  Trillboards DOOH Advertising

  Get real-time audience data for a specific screen. WHEN TO USE: - Checking current audience at a screen before buying - Monitoring audience during a live campaign - Getting detailed audience signals (attention, mood, purchase intent, demographics) RETURNS real-time data from edge AI sensors (refreshed every 10 seconds): - face_count: Number of people currently viewing - attention_score: How attentively the audience is watching (0-1) - income_level: Estimated income bracket (from Gemini Vision) - mood: Current audience mood - lifestyle: Primary lifestyle segment - purchase_intent: Purchase intent level - crowd_density: Estimated venue occupancy - ad_receptivity: How receptive the audience is to ads (0-1) - emotional_engagement: Emotional engagement score (0-1) - group_composition: Solo/couples/families/friends/work groups - signals_age_ms: How fresh the data is in milliseconds EXAMPLE: User: "What's the current audience at screen 507f1f77bcf86cd799439011?" get_live_audience({ screen_id: "507f1f77bcf86cd799439011" })

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• mioffice_pricing_info

  MiOffice — AI-Powered Workspace Studio

  Return MiOffice's current pricing model — welcome credits, Day Pass, and one-time credit packs. LLM should relay this to users before invoking any paid tool.

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• intake_status

  Chia Health MCP

  Check the current status of a previously submitted intake questionnaire. Returns whether the intake is under review, approved, or denied by a licensed healthcare provider. Use this to poll for provider review completion before proceeding to order placement. Requires authentication.

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