"MCP server that acts as a professor/teacher for AI agents" 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 DeepSeek as a real sub-agent inside Claude Code / Codex CLI — not just a single LLM call. DeepSeek gets its own 7-tool agent loop (Read/Write/Edit/Bash/Glob/Grep/NotebookEdit) inside a sandboxed workspace.

Enables Codex to delegate review and implementation tasks to the local Qoder CN CLI as background jobs, with two permission tiers and polling-based status updates.

Exposes the local Claude Code CLI as a subagent for Codex, enabling background review and implementation jobs with two fixed permission tiers.

Delegates work from MCP clients (like Claude Code) to the Codex CLI, allowing spawning of autonomous Codex subagents for tasks.

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

Exposes a running DeepSeek Harness as an MCP endpoint so any other agent or script can create workspaces and sessions, hand coding tasks to the DSH agent, read and write files, run shell commands, and invoke permitted harness tools under the same sandbox, transcript, and permission policy as the DSH UI.

Enables dispatching entire autonomous multi-agent engineering swarms directly from IDEs like Cursor and Windsurf via a single MCP endpoint, with streaming progress updates and verified git diffs returned to the editor.

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.

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 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 AI coding tools to call Grok and Antigravity CLIs as peer reviewers for code review, planning, debugging, and collaborative sessions.

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.

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 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.

Routes work from your coding agent across 20+ free-tier LLMs to cut costs 10-100x using a round-robin dispatch pool with cooldown-aware auto-fallback.

Enables Claude Code to delegate tasks to OpenAI's Codex CLI (GPT-5.4) with structured execution traces, parallel execution, session persistence, and adversarial code review.

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

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 users to run reusable Markdown-defined coding agents from any MCP-compatible client, delegating tasks such as code review, test writing, investigation, and documentation to a chosen coding CLI backend and returning results to the same conversation.

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

Enables users to define reusable task-specific agents in Markdown and run them through any MCP-compatible client using a chosen coding CLI backend, returning results to the same conversation. Supports shared backend/model configuration, permission modes, and optional cross-call session continuation.

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.

Enables users to define reusable Markdown-based coding sub-agents and run them through any MCP-compatible client with a chosen coding CLI backend, returning results to the same conversation.

Enables users to define task-specific agents in Markdown files and run them through a chosen coding CLI (Codex, Claude Code, Cursor, and others) from any MCP-compatible client, with results returned to the same conversation. Supports shared model and permission settings plus optional session continuity across multiple calls.

Enables users to define reusable Markdown-based coding agents and run them through MCP-compatible clients using a chosen coding CLI backend, with shared model and permission settings plus optional session continuation.

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.