"A server that supports Server-Sent Events (SSE)" matching MCP servers:

An authenticated OpenAI-compatible inference gateway with an async job broker that bridges a coding agent to a ChatGPT MCP worker, enabling ChatGPT to process inference requests via a tunnel.

Enables structured, step-by-step problem-solving through dynamic thinking processes that can be revised, branched, and adjusted as understanding deepens. Supports breaking down complex problems into manageable steps with the ability to revise previous thoughts and explore alternative reasoning paths.

A stdio MCP server that lets Claude Code delegate coding tasks to an OpenCode instance (optionally attached to an internal LLM gateway), with follow-up replies, status polling, output/diff retrieval, cancellation, and cleanup handled in a single session. It supports managed or attach modes, sandbox and approval policies, parallel fan-out delegations, and read-only review workflows.

Enables ChatGPT Desktop and Codex to delegate substantial work to a locally installed Grok Build agent. Supports consultations, background builder/tester jobs, cancellation, session discovery, and transcript export.

MCP server that lets any agent or MCP host delegate tasks to the Cursor CLI agent for fast, headless execution. Supports task delegation, project discovery, file analysis, and follow-up sessions.

Enables a DeepSeek Harness agent to delegate bounded coding tasks to a local ZCode runtime, follow their progress through events, and review the resulting diffs before accepting or continuing the work. It also exposes model catalog, default-model, and setup-diagnostics tools for managing those delegated tasks.

A TypeScript MCP server for launching, tracking, and managing external coding-agent runs across local and remote backends like Codex and Claude Code. It allows top-level agents to orchestrate subagents through tools for spawning tasks, polling events, and handling interactive sessions.

Provides access to the Superpowers skills library - expert-crafted workflows and best practices that guide AI assistants through proven techniques for coding tasks. Supports both community skills and custom personal skills.

Enables MCP clients to drive local Codex on a target Git repository: inspect repo state, start and follow up on tasks, review events and diffs, and record audit evidence for research governance.

A zero-cost MCP server that forces AI to self-correct code using prompt injection and context isolation.

Persistent, local memory for AI coding agents that learns how you work, not just what you said. Supports Claude Code, Codex CLI, Cursor, and any MCP client.

An MCP server that implements a structured workflow for LLM-based coding, guiding development through feature clarification, documentation generation, phased implementation, and progress tracking.

A domain-agnostic MCP server for autonomous experimentation, generalizing Karpathy's autoresearch pattern into a reusable server that any AI agent can drive, pointed at any domain defined by a JSON configuration.

Assist LLM writing Waterloo Docstrings, a format with emphasis on machine-verifyable normativity.

Enables AI coding agents to generate standardized code using scaffolding templates, enforce architectural patterns, and validate outputs programmatically. Supports creating projects from boilerplates and adding features to existing codebases while maintaining team conventions.

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.

Connects MCP clients such as Claude, Cursor, and VS Code to an OpenCode server's headless API so coding work can be delegated, answered, and monitored. It supports asking questions, launching foreground or background jobs, supplying required input and permissions, and reviewing resulting changes across projects.

A server component of the Model Context Protocol that provides intelligent analysis of codebases using vector search and machine learning to understand code patterns, architectural decisions, and documentation.

MCP server that lets Claude, ChatGPT, or VS Code build a complete, machine-checked model of your domain and generate an app from it.

Routes coding tasks to local and remote LLMs with intelligent cost-quality optimization, supports benchmarking and code search.