"Using Claude and Cursor AI for Full Stack Development" matching MCP servers:

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.

Uses Claude as an independent second-model reviewer inside Codex, performing reviews on disposable Git snapshots with structured findings.

Provides 8 specialized AI agents (Frontend, Backend, Database, API, DevOps, Testing, Security, Performance) for full-stack web development, powered by high-speed Cerebras inference and integrated with OpenCode CLI.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

An MCP server that lets Claude spawn Cursor subagents as async, bounded workers, enabling non-blocking task delegation with asynchronous completion notifications.

An MCP server providing 82 tools for persistent memory, governance, and consciousness continuity for AI instances. Enables local-first, runtime-reflexive operation with cross-device access and recursive self-awareness.

Enables Claude Code to delegate tasks to Cursor's headless agent, run adversarial reviews, and verify findings with prosecutor/advocate roles.

Monitors your Cursor usage and provides a conserve flag to the agent, helping you manage request quota by batching questions, preferring defaults, and cutting unnecessary confirmations.

Allows AI assistants to access and analyze your Cursor conversation history, enabling personalized coding assistance based on your actual development patterns.

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 MCP clients to delegate bounded tasks to an explicitly selected Cursor model with durable, restart-safe run state, idempotent runs, and fail-closed security defaults.

Enables two-way delegation between Codex and Cursor agents with background jobs, handoff plans, and isolated worktrees, allowing either editor to offload investigation, review, planning, or implementation to the other and continue the same native session later.

Provides a local groundedness verifier as an MCP server, returning a verdict on whether a draft answer is supported by provided document excerpts.

MCP server for step-by-step mathematical reasoning and planning, enabling AI agents to execute calculations and perform GUI actions like opening PowerPoint.

Connects Claude Code with multiple AI models (Gemini, Grok-3, ChatGPT, DeepSeek) simultaneously, allowing users to get diverse AI perspectives, conduct AI debates, and leverage each model's unique strengths.

Enables offline AI agent automation with embedded local LLM (Qwen 2.5), sandboxed file operations through AgentFS, and dynamic skill loading. Exposes capabilities via MCP with tri-state safety guards for private, air-gapped environments without network connectivity or API costs.

Wraps the Claude Agent SDK as MCP servers, letting you spawn multiple specialized Claude Code agents — each with its own model, tools, system prompt, and personality — from any MCP client.

Provides tools for Chain of Consciousness provenance logging and Agent Rating Protocol reputation scoring to establish trust and accountability for AI agents. It enables tamper-evident activity tracking, integrity verification, and bilateral reputation management.

A Model Context Protocol (MCP) server that provides intelligent search capabilities for discovering relevant Claude Agent Skills using vector embeddings and semantic similarity. This server implements the same progressive disclosure architecture that Anthropic describes in their Agent Skills enginee

Enables Claude Code sessions to communicate with each other, allowing discovery, messaging, and synchronous queries across sessions.