"MCP server for personalized AI course creation at aicourse.aiee.dev using remote streamable HTTP" matching MCP servers:

Enables MCP clients to interact with OpenCode 2.x/3.x servers through direct /api/... HTTP routing and ~85 tools spanning sessions, messages, files, config, providers, projects, input, TUI, and workflows. Runs as a zero-dependency, pure-JavaScript stdio bridge with no SDK or build step.

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 agent-style remote development over SSH with file operations and command execution, exposing native tools for searching, editing, and transferring files on remote machines.

A Model Context Protocol (MCP) server that enables remote access to OpenCode AI coding agent, allowing MCP-compatible clients to leverage OpenCode's capabilities.

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 AI clients to securely inspect and edit approved code, use semantic code intelligence, run builds/tests, supervise bounded processes, inspect Git, and execute owner-approved SSH commands on engineering workstations.

Use Codex as a subagent inside Claude Code: async dispatch into a long-lived codex app-server, results pushed back into the Claude session automatically, steer/interrupt mid-task, and Codex's built-in code review.

Forecast time series in CSV files: deterministic skforecast workflows and the script that ran.

Bridges Claude Code CLI with Cursor IDE to use your existing Claude subscription without separate API costs.

Turns product ideas into implementation-ready planning packages including PRD, requirements, user flow, wireframes, data schema, API contracts, and SDK boundaries, with an MCP handoff for coding agents.

Provides AI-powered development tools including code generation, refactoring, debugging, performance optimization, and test generation, along with smart prompts for code analysis and documentation, and a built-in knowledge base of coding best practices.

Integrates AI Consensus into coding agents, routing decisions through three frontier AI models for independent analysis and cross-examination, returning a recommendation and strongest dissent.

Enable Claude (or any other LLM) to interactively debug your code (set breakpoints and evaluate expressions in stack frame). It's language-agnostic, assuming debugger console support and valid launch.json for debugging in VSCode.

Enables managing Linux hosts and local coding agents from an MCP client through shell commands, files, background jobs, system information, instruction and skill discovery, and optional Claude Code, Codex, or Cursor CLI conversations. It provides privileged remote access with token authentication and can run longer work in the background.

Enables IDE integration with a multi-agent AI pipeline for solving, reviewing, and optimizing code through adversarial peer review and security filtering.

Enables AI-powered coding assistance including file editing, code generation, explanation, review, and shell command execution, using multiple free AI providers with automatic fallback.

Enables primary AI orchestrators to delegate token-heavy coding tasks to economical models via OpenRouter, running sandboxed autonomous ReAct loops with filesystem operations and git audit tools while reducing token costs.

Enables AI agents to delegate complex coding tasks, refactorings, and automated code reviews to OpenAI Codex and Google Antigravity CLIs, running them autonomously in YOLO mode with process supervision.

Enables running multiple AI CLI tools (Claude, Codex, Gemini, Forge, OpenCode) as background processes with automatic permission handling, allowing LLMs to execute async multitasking and combine different AI models.

Enables developers to delegate asynchronous coding tasks to a cloud-based autonomous agent, creating tasks, reviewing and approving execution plans, sending feedback, monitoring sessions, and retrieving diffs and Pull Requests directly from an MCP-compatible IDE. It also supports configurable mock mode for local testing without consuming API credits.