"Executing Orders on Alpaca Trading Platform" matching MCP servers:

Bridges the ChatGPT web UI to a local development environment over MCP, letting the model read and patch files, run real shell commands and terminals, execute tests, and control the desktop (screen, mouse, keyboard, clipboard) within user-approved folders. It adds parallel workers, goal/loop long-task control, plugin tools, and a security-hardening layer with risk-tiered shell policy, audit logging, and credential sanitization.

Connects ChatGPT to local files, terminals, and the desktop through MCP with Chrome integration, letting users read and edit project files, run commands, and follow tool results as they arrive. It also adds durable multi-agent workers, Goal/Loop task tracking, mid-task corrections, and Compact & Resume for carrying session and worker history into a fresh chat.

Orchestrates multiple Claude Code agents across iTerm2 sessions with process-level isolation, enabling collaborative AI development workflows on multiple codebases with task-based inter-agent communication and persistent state management.

MCP server that enables AI agents to analyze legacy code, plan and execute software migrations, generate modern source code, and validate production-ready artifacts through a multi-agent pipeline.

Enables ChatGPT to work on a local project by reading and editing files, running shell commands, keeping terminals and desktop sessions open, and splitting work across durable workers whose context persists between tasks. Long-running work can be steered mid-flight, tracked with Goal, and carried into fresh chats via Compact & Resume.

Lets ChatGPT work directly on a local project by reading and editing files, running shell commands and tests, keeping terminals open, and using the user's desktop, all paired with an approved workspace folder. It also splits independent jobs across persistent workers that retain context, while riding the user's existing ChatGPT plan rather than Codex quota.

MCP server that packages DeepSeek agents as callable tools, offering a bare model for quick Q&A and a full agent capable of executing real coding and file-modifying tasks in a workspace.

Bridges Warp's Oz coding agent to any IDE or MCP client (Claude Code, Cursor, Codex), plus native @oz in VS Code Copilot Chat. Cross-platform (macOS/Linux/Windows), independent project using only Warp's documented public oz CLI + MCP interfaces.

An MCP (Model Context Protocol) server that enables integration with the Simplifier Low Code Platform. This server provides tools and capabilities for creating and managing Simplifier Connectors and BusinessObjects through the platform's REST API.

A cross-platform MCP server implementing the Ralph Loop iterative development technique where a worker model does the work and a reviewer model provides cross-model review until approval.

Enables coding agents to design first by interviewing users, refining specs in digestible chunks, producing bite-sized TDD plans, and autonomously executing them through subagents with a server-verified red/green testing gate.

Enables AI agents to orchestrate tasks as a DAG with automated validation loops, executing validation commands, tracking statuses, and allowing iterative code fixes until tasks pass.

An MCP server that enables Claude and other LLM clients to access Hanzo AI platform capabilities and provide powerful code management tools for analyzing, modifying, and understanding projects.

Enables agents to generate typed client code from OpenAPI, GraphQL, Protobuf, and SQL specs using MetaEngine's code-generation platform.

Enables multiple AI coding agents to collaborate on a project by coordinating tasks, file leases, and messages through a shared hub, preventing conflicts and enabling parallel development.

Enables MCP-compatible clients to run reusable, task-specific coding agents defined in Markdown files, executing them through a chosen coding CLI backend and returning results to the same conversation. Supports shared agent, model, and permission configuration plus session continuation across multiple calls.

Enables AI coding assistants like Cursor and Claude to engage in real-time two-way dialogue, allowing them to pause for clarification and request user confirmation before executing tasks. It features a modern UI for managing interaction prompts, predefined options, and project analysis to reduce errors and API costs.

Enables any MCP-compatible client to run reusable task-specific agents defined in Markdown files, executing them through a chosen coding CLI backend and returning the results to the same conversation. Supports shared backend/model configuration, permission levels, and session continuation across calls for longer work.

Enables task-specific coding agents defined in Markdown files to be run from any MCP-compatible client, executing them with a chosen coding CLI backend and returning the result to the same conversation. The same agent definitions can be reused across clients with shared backend and model configuration, and continued across multiple calls through sessions.

A project intelligence platform for AI coding agents that scans, audits, generates, and monitors context files (CLAUDE.md, AGENTS.md, etc.) with drift detection and repair capabilities.

A zero-dependency MCP server that allows multiple coding agents to coordinate work on the same repository using file locks, task claims, and status messages.

Connects ChatGPT to Roblox Studio's built-in MCP, enabling natural-language reading and writing of game data, including executing Luau code and modifying scripts and instances.

Enables running reusable Markdown-defined coding agents (such as reviewers, test writers, or investigators) from any MCP-compatible client, executing them through a configurable coding CLI backend. Results return to the same conversation, with optional session continuation and shared model and permission settings.

Enables any MCP-compatible client to run reusable, Markdown-defined coding agents—such as reviewers, test writers, or investigators—by executing them through a chosen coding CLI backend and returning the results to the same conversation. Supports sharing agent definitions across clients, centralized backend and model configuration, and continued sessions across multiple calls.

Enables users to run reusable, task-specific coding agents defined in Markdown files from any MCP-compatible client, executing them through a chosen coding CLI backend and returning the result to the same conversation. Supports shared backend and model configuration, permission levels, and session continuation across multiple calls.

Enables MCP-compatible clients to run reusable, task-specific coding agents defined in Markdown files, executing them through a chosen coding CLI backend and returning results to the same conversation. Supports shared agent settings, multiple backends, and continued sessions across calls.

Lets any MCP-compatible client run reusable, task-specific coding agents defined in Markdown files, executing them through a chosen coding CLI backend and returning the results to the same conversation. Supports shared backend/model configuration, permission levels, and session continuation across multiple calls.

Enables AI agents to browse, create, and manage apps on the FreeAppStore platform, including provisioning repositories, writing code, and deploying live.

Enables STDIO-compatible AI assistants to queue coding work onto the official Google Antigravity CLI and track status, read reports or patches, query capabilities, or cancel running tasks without blocking. Supports trusted direct execution plus optional isolated or read-only modes depending on the platform.

Enables running reusable, task-specific coding agents defined in Markdown files from any MCP-compatible client, executing them with a chosen coding CLI backend and returning results to the same conversation. Supports configurable backends, models, permission levels, and session continuation for longer tasks.