"Features of Grid Trading Strategies" matching MCP servers:

Jungle Grid MCP Server lets AI agents submit, estimate, monitor, and retrieve logs for GPU workloads through Jungle Grid. It enables agentic execution for inference, training, fine-tuning, and batch jobs without manually choosing GPU providers or infrastructure.

An MCP server that enables AI models like Claude to interact with the Trading Simulator API for checking balances, viewing prices, and executing trades with automatic chain detection.

A meta-server that aggregates multiple MCP servers into a single interface, reducing token usage by 98%+ through progressive tool discovery and direct code execution that processes data between tools without consuming context window space.

Chain of Draft Server is a powerful AI-driven tool that helps developers make better decisions through systematic, iterative refinement of thoughts and designs. It integrates seamlessly with popular AI agents and provides a structured approach to reasoning, API design, architecture decisions, code r

An MCP server that uses Groq's API to expose raw chain-of-thought tokens from Qwen's qwq model, enabling LLMs to think step-by-step before responding.

A Node.js-based trading bot that integrates with the Zerodha platform to provide automated stock trading operations through MCP tools including session management, buy/sell operations, and portfolio tracking.

tradefloor generates simulated stock markets for testing trading strategies and AI agents. This local MCP server lets an assistant evaluate and rank strategies across many reproducible markets, run stress scenarios such as a rate shock or a recession, and explain why a

Backtest PineScript v6 strategies locally from your AI agent: transpiles Pine to C++ and runs it on the deterministic, TradingView-validated PineForge engine via Docker. Tools for single backtests, parameter-grid sweeps, and Binance OHLCV fetch — no API key, data never leaves your machine.

A Model Context Protocol server that connects LLMs to the Compiler Explorer API, enabling them to compile code, explore compiler features, and analyze optimizations across different compilers and languages.

MCP server to expose VS Code editing features to an LLM for AI coding

A Model Context Protocol server that enables natural language interaction with Snowflake databases through AI guidance, supporting core database operations, warehouse management, and AI-powered data analysis features.

A Model Context Protocol server implementation that enables secure remote command execution via SSH, with features for managing and using SSH credentials.

Local-first MCP server for building and running reproducible Backtrader strategies offline, with tools to inspect datasets, manage drafts, and execute backtests via controlled subprocess runs. It supports multiple hosts including Claude, Codex, OpenCode, and OpenClaw through stdio.

LLM Driven Trading Platform Orchestration - Strategy Design, Research & Implementation

Enables AI assistants to interact with Interactive Brokers trading accounts to retrieve market data, check positions, and place trades. Includes pre-configured IB Gateway and handles OAuth authentication automatically.

A Model Context Protocol server that enables LLMs to analyze options chains, calculate Greeks, and evaluate basic options strategies through Yahoo Finance data.

A minimal reference implementation of an MCP server that responds with "Hello, World" via Streamable HTTP. Serves as a baseline for integration testing and MCP client development with production-ready features including health checks, metrics, and containerized deployment.

Alpaca’s official MCP Server lets you trade stocks, ETFs, crypto, and options, run data analysis, and build strategies in plain English directly from your favorite LLM tools and IDEs

Enables execution and management of Babashka scripts using the Model Context Protocol, offering features like caching, command history access, and configurable timeouts for enhanced scripting workflows.

A server based on Model Context Protocol that enables AI models to interact with MySQL databases through a standardized interface, supporting features like query execution, table listing, and automated connection management.