"An email management MCP server" matching MCP servers:

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.

Wraps the local Qoder CLI into an MCP server, enabling any MCP client to delegate coding tasks to a local Qoder agent with session management, sandboxed permissions, and model selection.

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.

Turns any MCP-over-stdio client into a supervisor for a long-lived DeepSeek Harness coding agent: dispatch a goal, interrupt or steer it mid-flight, and collect results — with conversations that survive process restarts and crashes. Also supports running many conversations at once, approval round-trips, and completion notifications instead of polling.

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.

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

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.

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

An MCP (Model Context Protocol) server that enables integration with the Simplifier Low Code Platform. This server provides tools and capabilities for creating and managing Simplifier Connectors and BusinessObjects through the platform's REST API.

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.

Enables AI assistants to scaffold, edit, live-preview, and deploy full-stack apps with built-in database, email, and push notification capabilities through natural language.

A coordination layer for coding agents that provides memorable identities, inbox/outbox messaging, searchable message history, and file lease management to prevent conflicts. Uses Git for human-auditable artifacts and SQLite for fast queries, enabling multiple agents to collaborate across projects without stepping on each other.

Enables acceptance gates for AI coding-agent runs by recording evidence, running deterministic validation, applying a quality gate, and rendering auditable outcomes.

An MCP server that enables Claude and other LLM clients to access Hanzo AI platform capabilities and provide powerful code management tools for analyzing, modifying, and understanding projects.

A bridge between Gemini and GLM-4.5 models that provides 25 tools for automating complex coding tasks, file management, and system operations. It features a security-hardened architecture with sandboxing, persistent memory, and automatic file backups.

Enables intelligent task management, multi-agent workflows, and cross-IDE project management through the BMAD methodology, with features like time tracking, quality gates, and project templates.

An MCP bridge for the Pi coding agent running in WSL, enabling task execution, research, review, and session management through MCP.

Vyuha is an MCP server that enables coding agents to collaborate on a repository by providing tools for ticket creation, worktree management, code review, and staged deployment, all from local files.

Bridges the ChatGPT web UI to a local development environment over MCP, letting the model read and patch files, run real shell commands and terminals, execute tests, and control the desktop (screen, mouse, keyboard, clipboard) within user-approved folders. It adds parallel workers, goal/loop long-task control, plugin tools, and a security-hardening layer with risk-tiered shell policy, audit logging, and credential sanitization.

Enables coding agents to control other application windows by providing primitives for clicking, typing, capturing screenshots, and window management. Supports macOS, Windows, and Linux.

Enables AI agents to build games with the Cocos4 engine by providing high-level scaffolding tools and transparently proxying native MCP tools.

Enables Codex to delegate code reviews, coding tasks, image/video generation, and background investigations to Grok via MCP tools.

An MCP server that lets any MCP-capable agent spawn and drive Claude Code sessions — effectively turning Claude Code into an orchestratable sub-agent fleet.

Connects ChatGPT to local files, terminals, and the desktop through MCP with Chrome integration, letting users read and edit project files, run commands, and follow tool results as they arrive. It also adds durable multi-agent workers, Goal/Loop task tracking, mid-task corrections, and Compact & Resume for carrying session and worker history into a fresh chat.

An interactive task loop MCP server for Cursor IDE that enables continuous web application development through a persistent terminal-based task processing system. It automates file management and project operations by processing user input in a continuous loop using integrated Cursor rules.

Enables an autonomous build loop where Jev makes typed routing and completion decisions while Claude Code writes code, runs checks, and requires independent review before declaring tasks done.

An MCP orchestration server that coordinates multiple AI coding agents using Copilot CLI for parallel task execution with dependency management, file locking, and observability.

dev-brain-mcp

Multi-agent AI orchestrator that runs parallel coding agents in isolated sessions with self-improving intelligence, exposed via an MCP server for task execution and management.