"Using the Linear App" matching MCP servers:

Enables MCP clients to start new Codex conversations and continue existing threads, exposing codex and codex-reply tools over stdio via the Codex app-server protocol.

MCP server that lets Claude Code drive the local Codex CLI as a sub-agent for concurrent queries and optional file/shell actions, using the CLI's existing login and sessions.

Delegate tasks from Claude Code to other models (Codex CLI, DeepSeek, OpenRouter, etc.) without leaving the app.

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.

Enables AI assistants to interact with iOS Simulators and Android Emulators, allowing autonomous app development, UI interaction, profiling, and debugging through natural language.

A local MCP bridge that lets a compatible host start, monitor, steer, interrupt, resume, and approve Codex app-server work while enforcing repository-root security.

Two-way MCP bridge between Claude and Codex: send prompts into a live Codex Desktop thread and messages into a running Claude Code session, keeping each conversation in its own app. Native Desktop tasks on Windows and macOS; CLI/app-server mode on Linux and WSL.

Enables coding agents to install and manage Paydirt's iOS SDK for user feedback, trial cancellation, and subscription cancellation, with Slack integration and app building.

An MCP server that reverse-engineers a rebuild spec (CLAUDE.md, config, and mutation-tested tests) from an existing app, enabling coding agents to rebuild the app cleanly against that spec.

Enables a supervisor agent to create, coordinate, steer, inspect, and interrupt multiple Codex agents as a subagent pool within an MCP host, running them alongside the host's own subagents.

Bridges MCP clients such as Claude Code and Cursor to independent Codex app-server sessions, letting them start, poll, steer, review, compact, cancel, and answer prompts for asynchronous Codex tasks over local stdio or a remote authenticated WebSocket. Runs read-only by default, with workspace-write sandboxing only when a user explicitly enables it, and reports job status, model listing, and progress back to the client.

An open engine that gives AI persistent, reusable UI components with a writable component registry, versioned data storage, and a shell runtime, enabling AI to create, save, and reuse single-purpose apps.

MCP server for Emergent.sh that enables AI assistants to create, monitor, and interact with full-stack app projects, including responding to agent questions and taking preview screenshots.

Provides LLM Agents with AI-powered mentorship for code review, design critique, writing feedback, and brainstorming using the Deepseek API, enabling enhanced output in various development and strategic planning tasks.

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

This project aims to build a Claude Code MCP server and implement its associated tools (explain\_code, review\_code, fix\_code, edit\_code, test\_code, simulate\_command, your\_own\_query). The server is implemented using Node.js and the MCP SDK. It receives tool requests from clients via Stdio, dynamically

A desktop MCP service that integrates voice assistants into Mac workflows, enabling Obsidian memory, app control, Claude Code sessions, pending actions, and multi-language HTTP access.

Two AIs. One answer. ChatGPT and Claude discuss with each other until they agree, through your own signed-in CLIs: no API keys. Both read your project (never change it) and search the web. Plugin for Claude Code, Codex, Claude Desktop and the ChatGPT app.

Generates compiled Flutter apps from JSON Product Requirements Documents. Exposes endpoints for PRD validation, schema, payment terms, and build status.

An MCP server that provides TypeScript 7 native language server capabilities (go to definition, find references, hover types, diagnostics) to coding agents, using the Go-based tsc compiler for fast and accurate semantic analysis.