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

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.

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.

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 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.

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

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

Enables Codex to rank available tools and skills, rerank code and documentation search results, and triage saved output artifacts using Jev-based relevance scoring while leaving final decisions to Codex.

Enables local auditing of trading strategies through MCP checkers for point-in-time data provenance, pre-trade order validation, and regime-fragility testing, while deferring promotion verdicts to a hosted service.

Enables MCP clients to open websites, capture screenshots at multiple breakpoints, and run automated design audits for issues like overflow, small tap targets, low contrast, missing alt text, tiny text, and clipped content.

An MCP relay that adds a use_jev tool to every connected server, letting the Jev model autonomously select and execute tool calls while the calling model supplies any required text values. It enables agents to delegate multi-step tool use across all configured MCP servers through a single unified interface.

Provides a safe trading toolkit for AI agents with market data, indicators, paper trading, and guarded broker integration.

Enables AI assistants to connect to brokerage accounts in read-only mode so users can inspect balances, positions, and orders, and provides a local lab for backtesting strategies and simulated trading with pretend money.

Enables Codex to delegate code reviews, coding tasks, image/video generation, and background investigations to Grok via MCP tools.

Enables any MCP client to drive the user's real Chrome profile through a Chrome extension bridge, with tools for navigation, accessibility snapshots, ref-based interactions, console/network reading, screenshots, tab management, and restricted script evaluation.

Enables AI agents to automate simulated stock trading on the Tonghuashun trading system, including checking account balances and positions, viewing orders and deals, placing market orders, and canceling pending orders via the MCP protocol.

Enables AI agents to log trades from chart screenshots, validate them against custom strategy rules, import statements from MT5/TradingView and other brokers, and review R-based statistics in a local dashboard.

Enables local AI agents to connect to KH paper trading accounts via stdio MCP, supporting stock and option orders, account history, and competition standings.

Multi-agent system for long-term fund investment decision support, integrating analysis, risk control, and MCP tools to assist with fund trading decisions.

Enables conversational control of a Korean stock paper trading simulator. Users can view positions, adjust strategy parameters, and run backtests through natural language in Claude Desktop.

A read-only MCP server that exposes Interactive Brokers and Moomoo brokerage accounts as tools, enabling natural-language queries across positions, trade history, realized P&L, and sector exposure in one merged view.