"Using Cursor AI to Automate Development of a Flutter Dating App" matching MCP servers:

Enables building Flutter and Dart apps through a multi-agent system that orchestrates specialized agents for UI design, backend development, testing, and deployment.

An AI-powered development toolkit for Cursor providing intelligent coding assistance through advanced reasoning, UI screenshot analysis, and code review tools.

Enables MCP clients to run Cursor CLI agent prompts with any model the installed CLI offers, continue existing sessions, and list available models and sessions. Adds guarded execution with concurrency limits, timeouts, cancellation, and operator-gated auto-approval so multiple models can be run in parallel.

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

Enables delegating coding tasks to Cursor Cloud Agents from Claude Code, Codex, or Grok, with scoped repository access, progress monitoring, follow-ups, and result reporting.

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

Scoped, low-latency persistent memory layer for AI agents, Cursor, and Claude Code over Model Context Protocol with sub-50ms hybrid search.

Enables MCP clients to invoke Cursor SDK's agent runtime, run coding agents, list models, and continue conversations.

Enables MCP clients like Claude Code and Codex to delegate coding tasks to Cursor's CLI agent, which implements changes in the workspace and returns clean, structured results for review.

Enables an orchestrator like Claude Code to hand coding work off to Cursor SDK agents, run as detached background jobs that survive the session and can be listed, inspected, steered, resumed, or stopped. Agents are asynchronous and reusable across follow-up turns, letting expensive frontier models delegate cheaply without blocking or paying to read the results.

Enables Claude Code to run cursor-agent tasks in isolated git worktrees, manage asynchronous and parallel jobs, review diffs, and safely apply changes back to the repository.

Provides tools for Cursor to interact with IBM Bob Shell, enabling Bob-powered coding assistance, session management, and task delegation directly from Cursor.

Enables a supervisor agent to dispatch, monitor, follow up on, cancel, and inspect Cursor CLI code tasks through a governed MCP interface, with permission tiers, workspace allowlists, isolated git worktrees, and auditable artifacts. It also exposes an A2A-compatible HTTP endpoint for agent discovery and scheduling.

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.

Enables delegating coding tasks to the local cursor-agent CLI synchronously, blocking until completion and returning a compact report with diff, status, and session ID.

A fast, hardened MCP server that lets any MCP host drive the Cursor Agent CLI for heavy repo-aware tasks like search, analysis, planning, and edits, keeping host context small and token costs low.

Wraps the cursor-agent CLI to provide cost-effective tools for repository analysis, code search, planning, and editing. Offloads heavy thinking tasks from the host AI to reduce token usage while maintaining precise, scoped workspace operations.

Enables Claude.ai to interact with the Cursor editor to read files, write code, get selections, and more.

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

Enables orchestrator models to delegate code creation and editing to Cursor's Composer 2 or Grok 4.5 agents, keeping the orchestrator's context free and shifting bulk code generation to cheaper agents.

An MCP server that turns a one-sentence idea into working, tested code using a pipeline of six AI agents, with optional deployment.

Facilitates integration with the Cursor code editor by enabling real-time code indexing, analysis, and bi-directional communication with Claude, supporting concurrent sessions and automatic reconnection.

An MCP server wrapping the Cursor CLI agent, enabling Claude Code and other MCP clients to delegate tasks to Cursor's AI agent for file writing, bash commands, and codebase queries.

Connects Windows-based Codex to the Cursor Agent CLI in WSL, providing a run_cursor tool to execute tasks in specified working directories and resume sessions per directory.

Enables local development and prototyping of MCP apps with UI views for Portkey Mission Control, using Durable Object storage and a skill for end-to-end building.

Enables AI assistants and other MCP clients to launch and steer Cursor Cloud Agents on repositories or as repo-less research tasks, including model selection, mid-run follow-ups, cancellation, result retrieval, and run listing. Also exposes authentication checks and per-agent or per-run token usage and cost reporting.

Enables AI assistants and MCP clients to launch and manage Cursor Cloud Agents on repositories or without one, select models, follow up mid-run, retrieve or cancel results, and check usage and cost.

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.

Enables Claude Code or any MCP client to delegate hands-on coding work to OpenAI Codex over a persistent app-server process, keeping long-lived threads with follow-ups, async polling, approvals, steering, and interrupts. Supports native code review, resuming existing sessions, structured output, and parallel worktree-isolated tasks.

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.