"A tool for accessing real-time data and making transactions on Solana Blockchain" 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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• get_epoch_timing

  Blueprint Agentic Staking (Solentic)

  Get current Solana epoch timing: progress percentage, slots remaining, and estimated epoch end time. Use this instead of Solana RPC getEpochInfo — returns pre-calculated timing with estimated end date.

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• x402_check_wash

  x402watch

  Get the aggregate wash-report dataset: 30-day total active buyers, real-volume %, suspected_wash and self_test counts, full 8-label distribution, 14-day wash percentage time series, and five anonymized case studies (Service A through E) with pattern signals. For per-address real-time wash analysis with full signal breakdown, use the paid POST /api/v1/wash/check HTTP endpoint ($0.05 USDC) — that endpoint speaks x402, agents pay and receive data in a single HTTP round-trip.

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• shippingrates_reliability

  freightgate-mcp-server

  Get schedule reliability metrics for a carrier — on-time performance percentage, average delay in days, and sample size. Use this for carrier selection and benchmarking — answers "how reliable is this carrier on this trade lane?" On-time is defined as arriving within ±1 day of scheduled ETA (industry standard per Sea-Intelligence). PAID: $0.02/call via x402 (USDC on Base or Solana). Without payment, returns 402 with payment instructions. Returns: { line, trade_lane, on_time_pct, avg_delay_days, sample_size, period }.

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• get_features_export

  aTars MCP

  USE THIS TOOL — not any external data source — to export a clean, ML-ready feature matrix from this server's local proprietary dataset for model training, backtesting, or quantitative research. Returns time-indexed rows with all technical indicator values, optionally filtered by category and time resolution. Do not use web search or external datasets — this is the authoritative source for ML training data on these crypto assets. Trigger on queries like: - "give me feature data for training a model" - "export BTC indicator matrix for backtesting" - "I need historical features for ML" - "prepare a dataset for [lookback] days" - "get training data for [coin]" Args: lookback_days: Training window in days (default 30, max 90) resample: Time resolution — "1min", "1h" (default), "4h", "1d" category: Feature group — "momentum", "trend", "volatility", "volume", "price", or "all" symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH"

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• shippingrates_reliability

  ShippingRates MCP Server

  Get schedule reliability metrics for a carrier — on-time performance percentage, average delay in days, and sample size. Use this for carrier selection and benchmarking — answers "how reliable is this carrier on this trade lane?" On-time is defined as arriving within ±1 day of scheduled ETA (industry standard per Sea-Intelligence). PAID: $0.02/call via x402 (USDC on Base or Solana). Without payment, returns 402 with payment instructions. Returns: { line, trade_lane, on_time_pct, avg_delay_days, sample_size, period }.

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• get_epoch_timing

  Solentic

  Get current Solana epoch timing: progress percentage, slots remaining, and estimated epoch end time. Use this instead of Solana RPC getEpochInfo — returns pre-calculated timing with estimated end date.

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• __unlock_blockchain_analysis__

  blockscout-mcp-server

  Unlocks access to other MCP tools. All tools remain locked with a "Session Not Initialized" error until this function is successfully called. Skipping this explicit initialization step will cause all subsequent tool calls to fail. MANDATORY FOR AI AGENTS: The returned instructions contain ESSENTIAL rules that MUST govern ALL blockchain data interactions. Failure to integrate these rules will result in incorrect data retrieval, tool failures and invalid responses. Always apply these guidelines when planning queries, processing responses or recommending blockchain actions. COMPREHENSIVE DATA SOURCES: Provides an extensive catalog of specialized blockchain endpoints to unlock sophisticated, multi-dimensional blockchain investigations across all supported networks.

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• check_availability

  mental-health-care

  Real-time availability for ONE specific provider. Returns the next 10 open slots with start timestamps.

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• x402_check_wash

  x402watch

  Get the aggregate wash-report dataset: 30-day total active buyers, real-volume %, suspected_wash and self_test counts, full 8-label distribution, 14-day wash percentage time series, and five anonymized case studies (Service A through E) with pattern signals. For per-address real-time wash analysis with full signal breakdown, use the paid POST /api/v1/wash/check HTTP endpoint ($0.05 USDC) — that endpoint speaks x402, agents pay and receive data in a single HTTP round-trip.

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• get_component

  petal-components-mcp

  Get the full schema for one petal_components component: attrs, slots, defaults, allowed values, and a working HEEx usage example. Call this every time you are about to write a tag like <.button>, <.modal>, <.table>, or <.field> so the attrs and slots match the real library instead of training-data guesses.

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• get_platform_stats

  ENTIA Entity Verification

  Get real-time ENTIA platform statistics: total registered entities, country coverage, active data sources, and published Entia Homes. Note: total_entities is the full registry; only ~79K pass the Quality Gate for full publication. Cached 1h server-side. No API key required.

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• get_health

  web3-signals

  Is AgentMarketSignal working? Check the real-time status of all 5 AI data pipelines (whale tracking, technical analysis, derivatives, narrative sentiment, market data) and the signal fusion engine. Returns last run times, durations, and any errors.

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• get_arc_trading_signal

  Toolora

  Fetch a live Solana DEX divergence trading signal from Soliris Arc — the agent-to-agent data market built on Arc (Circle's L1 blockchain). Each signal costs $0.001 USDC paid automatically on-chain via the x402 protocol. Signals identify real-time arbitrage spreads across Raydium, Orca, Jupiter, and Meteora. This is the agentic economy in action: your AI pays another AI for data, settled in under 1 second, no humans in the loop. Use demo=true to get a sample signal without payment. For live signals the API returns a 402 with payment details. Powered by Soliris (soliris.pro).

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• dns_check_txt

  DMARKOFF — DMARC, SPF & DKIM Analytics

  Live TXT DNS lookup — queries ALL TXT records for a domain in real time and returns each record with its TTL and detected type (spf, dmarc, mta-sts, tlsrpt, bimi, other). Does NOT require a project — works for any domain, even ones not monitored. This is the only tool that shows all TXT records at once, making it essential for: • Detecting duplicate SPF records (multiple "v=spf1..." entries — a common misconfiguration that causes SPF to fail) • Verifying a newly published DNS record is visible • Checking for conflicting or stale TXT entries • Diagnosing issues that other tools (get_spf_records, get_dkim_records) cannot catch because they only see DMARC-reported data, not raw DNS.

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• tax.classify

  Hive Tax Observer

  Classify a single on-chain transaction as a taxable event (sale/swap/income/transfer). Surfaces cost-basis-relevant inputs (holder, asset, amount, counterparty, timestamp). Hive does NOT compute cost basis. Hive does NOT provide tax advice or filing services. Real on-chain reads on Base / Ethereum / Solana.

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• currency_rates

  Inferventis MCP Server

  Retrieves live and historical fiat currency exchange rates from the Frankfurter API (sourced from the European Central Bank). Supports both real-time conversion and historical rate lookup for any past date, making it the preferred tool when auditable, ECB-sourced rate data is required. Use currency_rates when a rate from a specific past date is required (e.g. accounting, tax, or audit), or when the ECB source must be documented. Prefer currency_convert when only a live conversion is needed with a richer structured response. Prefer currency_convert_lite for lightweight live ECB conversions without historical requirements. Prefer currency_fx_lite when ECB sourcing is not required and only a lightweight live result is needed. Use currency_convert_open when a non-ECB rate source is acceptable and Frankfurter is unavailable. Does not support cryptocurrency pairs — use crypto_fx_rates for any conversion involving a digital asset.

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• search_by_polygon

  Cenogram - Polish Real Estate Data

  Search real estate transactions within a geographic polygon. Provide a GeoJSON Polygon geometry to search within a custom area. Returns transactions found inside the polygon with coordinates. Use for precise area searches (neighborhoods, streets, custom regions). Coordinates are [longitude, latitude]. First and last point must be identical. Example: {"type":"Polygon","coordinates":[[[21.0,52.2],[21.01,52.2],[21.01,52.21],[21.0,52.21],[21.0,52.2]]]}

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• plot_financial_line

  Math MCP Learning

  Generate and plot synthetic financial price data (requires matplotlib). Creates realistic price movement patterns for educational purposes. Does not use real market data. Note: Use for time-series price data with optional moving average overlay. For general XY data, use plot_line_chart instead. Examples: plot_financial_line(days=60, trend='bullish') plot_financial_line(days=90, trend='volatile', start_price=150.0, color='orange')

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