"Using a cursor to code or implement functionality" matching MCP servers:

Enables users to control the cursor in Figma through verbal commands using an agentic AI agent, streamlining the design process with a new interaction method.

MCP server that lets you drive Claude Code sessions hands-free by voice from any MCP client, enabling remote models to send prompts, monitor progress, and get results read back.

An autonomous MCP server that uses the Claude Code CLI to solve coding problems without permission prompts.

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.

Enables AI agents to call tools through a security gateway that intercepts requests, enforces deterministic policy and risk checks, blocks or escalates high-risk actions for human approval, and keeps tool credentials and audit logs protected.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

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.

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

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 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.

An MCP server integration that enables Cursor AI to communicate with Figma, allowing users to read designs and modify them programmatically through natural language commands.

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.

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.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

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.

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.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.