aipricepatterns

AI Price Patterns provides historical market memory for AI agents through semantic vector search across years of financial market data.

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What it can do

  • Pattern Search: Search for similar historical price patterns in the RLX database.
  • Get Track Record: Public forecast track record: every closed bar the engine logs its own forecast BEFORE the outcome is known, then grades it against reality. Returns direction hit rate, p10-p90 band
  • Search By Sketch: Search for historical patterns similar to a custom 'sketched' price trajectory (Sketch-to-Search). Useful when you want to find matches for a hypothetical or hand-drawn pattern.

What data it sees

Do you need an account

No: the server works without sign-in

AI Price Patterns provides historical market memory for AI agents through semantic vector search across years of financial market data.

Use it to discover similar market regimes, analyze historical price patterns, retrieve market context, and accelerate quantitative research.

Designed for algorithmic trading, quantitative finance, reinforcement learning, and autonomous AI agents.

Features: • Semantic vector search • Historical market memory • Pattern similarity discovery • Market regime analysis • Quantitative research • Remote HTTP MCP • Works with Claude, Cursor, ChatGPT, Codex, VS Code and other MCP-compatible clients.

How to connect

How to connect aipricepatterns to Claude

The server address to paste into Claude settings:

https://aipricepatterns--sott095.run.tools

  1. Open Claude (claude.ai or the desktop app).
  2. Go to Settings → Connectors.
  3. Click Add custom connector.
  4. Paste the server address copied below into Remote MCP server URL and click Add.
  5. In a chat, click + → Connectors and switch the new connector on.

Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

Authorization

After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

How to connect aipricepatterns to ChatGPT

The server address to paste into ChatGPT settings:

https://aipricepatterns--sott095.run.tools

  1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
  2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
  3. Open Settings → Connectors and click Create.
  4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
  5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
  6. In a new chat open + → Apps/Connectors and enable the connector.

OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

Authorization

On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

How to connect aipricepatterns to Cursor

The server address to paste into Cursor settings:

https://aipricepatterns--sott095.run.tools

Fastest: click Open in Cursor below and confirm the prompt.

Manually:

  1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
  2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
  3. Save the file. The server appears in the MCP list; authorize it there if asked.

Authorization

If the service needs sign-in, an authorize button appears next to the server in the MCP list.

Server tool list (12)

Raw names from tools/list. Only developers need these.

pattern_searchSearch for similar historical price patterns in the RLX database.
get_track_recordPublic forecast track record: every closed bar the engine logs its own forecast BEFORE the outcome is known, then grades it against reality. Returns direction hit rate, p10-p90 band coverage vs the nominal 80%, mean abs error, the active conformal calibration scale, and recent forecast-vs-actual rows. Use this to verify the engine's calibration before trusting its forecasts.
search_by_sketchSearch for historical patterns similar to a custom 'sketched' price trajectory (Sketch-to-Search). Useful when you want to find matches for a hypothetical or hand-drawn pattern.
backtest_strategyPerform a full strategy backtest over a historical period (Walk-forward analysis). Use this for testing general rules or long-term performance.
get_pattern_metricsRetrieve advanced statistical metrics and forecast distributions for a pattern search result.
get_trading_decisionReturn a compact trader decision card for a symbol/interval: TRADEABLE, WATCH, or SKIP with direction, confidence, evidence, risk, reasons, and caveats.
forecast_private_memory_from_dataCreate or reuse a private dataset, import candle data, and return a compact forecast card in one call. Ideal for users who want to upload exchange or ML-derived candle history, inspect analogues immediately, and only then decide whether to run RLXBT.
detect_market_regimeClassify current market state into one of the known market regimes.
get_live_polymarket_trade_decisionAuto-discover the active BTC Up/Down 15m Polymarket market, combine live Polymarket pricing with pattern memory and intrabar momentum, and return BUY_YES, BUY_NO, or SKIP with entry guardrails.
get_api_guideReturns the full documentation and workflow guide for this MCP server. Call this first to understand all available tools, their use cases, and how to combine them. Includes: tool catalog, recommended workflows for Polymarket research, historical analog analysis, and example calls.
find_market_analogsFind historical price patterns similar to the current (or specified) market state. Returns a list of past dates when the same pattern occurred, the price outcome after each analog, and aggregate statistics (win rate, median return, percentile range). Use cases: (1) pre-news analysis — filter by timeOfDayUTC to find analogs that happened near a specific event time (e.g., FOMC at 14:00 UTC); (2) regime research — understand historically what happens after this pattern; (3) Polymarket context — combine with get_polymarket_probabilities to validate signal with historical evidence. Returns a plain-English summary suitable for agent reasoning.
get_mcp_compatibility_manifestReturn the versioned MCP compatibility manifest, including canonical tools, aliases, and JSON argument schemas for remote clients.