"Using Hummingbot and LLMs for Automated Trading" matching MCP tools:

• 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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• 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_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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• get_latest_decisions

  OneQAZ Trading Intelligence

  Purpose: Track-B (signal-driven) paper-trading decision log (Track B = the signal-engine decision path — indicator/Thompson-sampling driven; Track A = the LLM judgement path, see get_llm_trading_decisions). Triggers (casual questions too): "what did the system decide?", "최근에 뭐 샀어? 팔았어?", "why did you buy X?", "show recent buy/sell calls", "오늘 매매 판단 뭐 했어?", "any trades triggered today?". When to call: review recent automated decisions and their outcomes. Prerequisites: market://{market_id}/status recommended for context. Next steps: get_trade_history, get_signals. Caveats: paper-trading decisions only — no real-money order routing. Args: market_id: Market ID (crypto, kr_stock, us_stock; aliases coin/kr/us accepted) limit: Max results (default 10) decision_filter: Filter by decision (buy, sell, hold) hours_back: Only decisions within last N hours Disclaimer: Information only, not investment advice.

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• book_demo

  gethal.ai

  Submits a demo request. The prospect receives a confirmation email and must click the link in it before the request reaches a human at A Cloud Frontier. Use only when a real person has explicitly asked for a demo and provided their own working email address. Do NOT call this for testing, evaluation, or crawling purposes — automated and unconfirmable requests are rejected.

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• apikeys_rotate_api_key

  DataNexus MCP

  ⚠️ DESTRUCTIVE — requires human confirmation before use in automated pipelines. Revoke the current API key and issue a replacement. Returns the new key once — store it immediately. Pass keys as the X-DataNexus-Key header.

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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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• aeo_generate

  mcp

  Génère (sans appliquer) un artefact AEO, déterministe et gratuit. Types : jsonld, robots, llms, meta, faq (params faqs[]), ai-txt, humans-txt, security-txt, sitemap. jsonld/robots/llms/meta/faq sont applicables (cf. aeo_apply) ; ai-txt/humans-txt/security-txt/sitemap sont à publier par l’agence.

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• identify_card

  Pulltrader Seller Economics

  Resolve a natural-language trading-card description into structured fields (player/athlete, year, set, card number, parallel, grader, grade, sport/category). Use this first when a user names a card in prose and you need its canonical fields before looking up sales or market value. Returns a confidence level and which fields were resolved. This does NOT price the card or return sales — use search_card_sales or summarize_card_market for that. Trading cards only.

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• colorize_image

  Sats4AI - Bitcoin-Powered AI Tools

  Colorize black-and-white or grayscale photos. DDColor (dual-decoder, ICCV 2023) — vivid, natural colorization. Impossible for text/vision LLMs. 5 sats per image, pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='colorize_image'.

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• plan_change_verification

  Reality Graph Verification Tools

  Turn explicit change characteristics into a risk tier, required automated checks, manual scenarios, evidence, release blockers, role handoff, and canonical Reality Graph guidance. Use before implementation or review. It does not inspect code and never invents a confidence score.

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• get-quickstart-guide

  JxBrowser MCP Server

  Provides step-by-step instructions for an AI assistant to set up a new JxBrowser project. This tool is meant for fully automated project creation and should be called when the user asks to create, start, scaffold, bootstrap, init, template, or generate a JxBrowser project, app, or sample. CRITICAL RULES: 1. NEVER call this tool before knowing the user’s preferences. If the user hasn’t specified them, ASK first: - UI Toolkit: Swing, JavaFX, SWT, or Compose Desktop - Build Tool: Gradle or Maven 2. Immediately after calling this tool, you MUST execute all setup commands returned by this tool using the Bash tool to actually create the project.

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• rank

  XFMS — Model Source

  Rank LLMs for a stated purpose. Returns a shortlist with weights, scores, and plain-English rationale per pick. Use when the user wants to see and compare alternatives, not just one answer.

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• search_cards

  Tcgdex

  Search Pokémon TCG (and other trading card games) cards by name in the TCGdex card database. Returns brief matches (id, localId, name, image thumbnail). Use get_card with an id for full card details.

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• search_pairs

  Dexscreener

  Free-text search across all DEX Screener chains for trading pairs matching a token name, symbol, or address. Returns up to 30 pairs with price USD, liquidity, 24h volume, and chain/DEX info.

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• count

  Cleanor

  Accurately count characters (Unicode code points), UTF-16 units, words, lines and UTF-8 bytes in text. LLMs are notoriously bad at counting, so always use this tool for "how many characters/words" questions.

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• get_price_coin

  webbersites-x402-data-api

  Current USD spot price and 24-hour percent change for any crypto asset by CoinGecko id. Cheap, high-volume price lookups for trading and analytics agents. ($0.001 per call, paid via x402)

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• regex

  x402 Trading & On-Chain Intelligence

  Apply a regex to text and return all matches + capture groups (deterministic; LLMs guess regex wrong). Send { pattern, text, flags? }. [x402 paid tool — price $0.003; POST /api/regex]

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• get_ticker_summary

  Gloria AI

  Get a 24-hour AI-generated summary for any crypto ticker or topic (paid via x402). Returns decision-grade bullet points combining Gloria's curated news with real-time web search. Designed for fund managers and trading agents. Payment is handled via the x402 protocol using USDC on Base network. This tool returns the payment endpoint and instructions.

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• escalate_to_human

  Agent Broker

  Hand off an in-flight task to a human operator with a full context bundle: transcript, prior actions, identifiers, and a recommended next step. EXAMPLE USER QUERIES THAT MATCH THIS TOOL: user: "I'm stuck — get a human at smb_xyz to call me back" -> call escalate_to_human({"smb_id": "smb_xyz", "reason": "agent_blocked", "summary": "Cannot resolve via automated channels"}) WHEN TO USE: Use when automated resolution has failed after channel-fallback exhaustion, when the task requires human judgment, or when the customer has explicitly requested human contact. WHEN NOT TO USE: Do not use as a first resort. Escalate only after automated resolution attempts. COST: $0.2 per_escalation LATENCY: ~2000ms EXECUTION: async_by_default (use get_outcome to retrieve result)

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