"Detecting Patterns and Conformations in Trading Charts" matching MCP servers:

An MCP server that turns chart requests into permanent, hosted Image-Charts URLs, enabling agents to generate charts that render anywhere without client-side libraries.

Provides access to self-contained, runnable implementation patterns across multiple programming languages via MCP tools for searching and retrieving documentation and code examples.

A Model Context Protocol server that generates lightweight ASCII charts directly in terminal environments, supporting line charts, bar charts, scatter plots, histograms, and sparklines without GUI dependencies.

Provides advanced charting widgets (uPlot time series, ECharts box plots and parallel coordinates) for Urano Desktop/Cloud via MCP tools that build uiSpec JSON for rendering.

Exposes the 23 Gang of Four design patterns to AI coding agents for generation, canonical examples, AST-based detection, validation, and anti-pattern refactoring in Python codebases.

Enables querying hyperlocal weather forecasts and historical data from multiple sources (NWS, Open-Meteo, PurpleAir) through natural language, including current conditions, forecasts, source comparisons, and accuracy metrics.

An MCP server that enables AI assistants to programmatically create and manage flowcharts, ERDs, and swimlane diagrams. It provides tools for manipulating diagram structures, performing auto-layouts, and exporting to Mermaid or Markdown formats.

An MCP server that enables AI agents to query RevenueCat's subscription analytics API using natural language, retrieving metrics like MRR, churn, and revenue.

An MCP server providing curated Swift and SwiftUI best practices from leading iOS developers, including patterns and real-world code examples from Swift by Sundell, SwiftLee, and other trusted sources.

An MCP server that gives AI agents access to RevenueCat's Charts & Metrics API. Query MRR, churn, trial conversion, revenue, and 17 more subscription metrics directly from Claude, Cursor, or any MCP client.

A modern Python MCP server for rendering customizable charts (line, bar, pie, scatter, area, combined dashboards) with Plotly, supporting export to PNG, SVG, and base64, and terminal charts with ANSI output.

Provides AI systems with structured thinking frameworks and reasoning tools to maintain consistent problem-solving patterns across conversations. Enables multi-step reasoning, decision analysis, and systematic troubleshooting through invocable mental models.

Provides AI agents with real-time financial market intelligence including regime detection, adaptive signals, macro context chains, and cross-market analysis for crypto, US, and Korean stocks.

Enables AI assistants to generate UI components and web interfaces from natural language descriptions using the Magic Patterns API.

Enables AI assistants to access and analyze NOAA electronic navigational charts with S-57 format parsing, supporting coordinate-based chart discovery, navigation feature extraction, and maritime safety queries.

Pattern-intelligence MCP server for ServiceNow Discovery that enables AI agents to read, search, validate, author, surgically edit, and reason about Discovery patterns, including NDL grammar, SNMP OIDs, data sources, and emulator blueprints.

Enables querying European electricity generation, prices, and capacity data from Fraunhofer ISE's Energy-Charts platform.

Enables AI-powered cryptocurrency trading and analytics across multiple exchanges and blockchains, with integrated Telegram bot and live trading capabilities.

Provides React design and rendering patterns from patterns.dev as MCP tools and resources for Claude Code.

Provides foundational trading utilities by fetching market data through Akshare and computing technical indicators like RSI and MACD using TA-Lib. It enables users to retrieve candlestick data and technical analysis series via a standardized MCP interface.