"A production-ready Task Management MCP server for AI agents and autonomous workflows" matching MCP servers:

Enables AI agents to build and edit Roblox Studio places by inspecting, generating terrain, geometry, and code, with validation and iteration.

Run dynamic, multi-agent workflow scripts — agent(), parallel(), pipeline() — over real coding agents (Claude Code and OpenAI Codex), with deterministic journaling, resume, token budgets, and git-worktree isolation.

A local MCP server that lets Hermes supervise Claude Code, delegating focused coding, research, or review tasks to the Claude Code CLI and managing worker sessions, background jobs, cancellations, and read-only reviews.

An autonomous task decomposition and execution agent that plans, executes, verifies, and commits code changes for engineering goals.

Enables AI tools to interact with browsers for enhanced frontend development, providing context to LLMs through tools like API call analysis, screenshots, element selection, and documentation ingestion.

Enables orchestrating multiple AI CLI agents (Claude Code, Codex, Gemini CLI, Copilot CLI) through a unified MCP interface for task delegation, cross-agent comparison, and specialized tools like code review and debugging.

Enables delegating coding tasks to multiple AI CLI agents (Claude Code, Antigravity, Codex, Cursor) with session memory and diff inspection.

Enables ChatGPT to drive sandboxed coding tasks via the Agents API, with independent review and exact-tree draft pull request publication for allowlisted repositories.

A transport-agnostic MCP server that integrates multiple AI coding agents (Claude Code, Gemini, and Codex) with built-in tools for command execution, calculations, and streaming capabilities. Supports both STDIO and HTTP transports for flexible deployment.

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.

MCP server that wraps AI CLI tools — Claude Code, Antigravity CLI, and Codex CLI — so any MCP client can call them as tools.

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.

Provides GitHub Copilot with 160+ AI agent personas and 1,400+ specialized skills, enabling developers to activate expert roles like backend architect or security engineer through natural language.

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.

Enables any MCP-compatible client to run reusable, Markdown-defined task agents against a chosen coding CLI backend, returning results to the same conversation and optionally continuing a session across calls.

Enables users to define reusable, task-specific agents in Markdown and run them from any MCP-compatible client using a chosen coding CLI. Supports shared backend and model configuration plus optional session continuity across calls.

Lets a coding agent hand a plain-language app idea to a hosted AI software team that shapes, designs, builds, tests and deploys it, returning a one-time link into the full build workspace. Also lists your apps with their stage, pending approvals and live addresses after a standard OAuth sign-in.

Enables AI assistants and other MCP clients to launch and steer Cursor Cloud Agents on repositories or as repo-less research tasks, including model selection, mid-run follow-ups, cancellation, result retrieval, and run listing. Also exposes authentication checks and per-agent or per-run token usage and cost reporting.

Enables an orchestrator like Claude Code to hand coding work off to Cursor SDK agents, run as detached background jobs that survive the session and can be listed, inspected, steered, resumed, or stopped. Agents are asynchronous and reusable across follow-up turns, letting expensive frontier models delegate cheaply without blocking or paying to read the results.

Enables AI assistants and MCP clients to launch and manage Cursor Cloud Agents on repositories or without one, select models, follow up mid-run, retrieve or cancel results, and check usage and cost.