"How to compare the master branch with a feature branch using Cursor" matching MCP servers:

Enables git-branch-style A/B experimentation for long-running tasks, allowing users to create, compare, promote, discard, or roll back parallel conversation branches via MCP tools.

An MCP server that enables AI assistants to diagnose network and service problems by walking a structured funnel of cURL timing metrics, identifying which hop is at fault, and providing targeted recommendations.

Enables multi-model code review by fanning out issues to multiple LLMs simultaneously, diffing their unique insights, optionally running debate rounds, and dispatching subagents to implement fixes with git commits.

Enables Cursor AI to read and modify Figma designs programmatically via the Model Context Protocol.

AI 規格大師 — MCP server bridging specs (Linear / JIRA / GitHub Issues / Notion / Markdown / Figma) to tests, with bidirectional traceability and a spec-quality coach. Sibling to mk-qa-master.

Enables unified administrative control over Cloudflare, Porkbun, Docker, Proxmox VE, Nginx Proxy Manager/NPMPlus, Uptime Kuma, Authentik, and Coolify. Exposes service discovery and action execution through three MCP tools with roughly 150 cataloged operations for managing DNS, containers, VMs, proxies, monitors, users, and related infrastructure.

MCP server bridging product ideas to prioritized roadmaps + spec drafts. Hands directly off to mk-spec-master. (AI 規劃大師)

Enables pixel-perfect image comparison and visual regression testing via tools to compare local images, screenshots, and URLs with detailed diff statistics.

Enables evaluation of patent feature-separation results by listing records, checking alignment with claims and original text, and running deterministic quality gates plus a Judge audit.

mcp-test-runner is an MCP server that lets your AI client (Claude / Cursor / Codex / Gemini) drive your entire QA loop end-to-end: * Run tests across pytest / Jest / Cypress / Go / Maestro — single MCP surface, one env var to switch * Analyze a URL (Web DOM probe) or a live mobile screen (Maestro hierarchy) to extract testable modules + candidate cases * Generate runna

Enables humans to review AI-generated code changes through a GUI: agents freeze git diffs and add findings/diagrams, while reviewers annotate and save decisions returned as an exact correction prompt.

A local knowledge graph MCP server that provides AI agents with permanent, structured memory about codebases, enabling semantic search, blast radius analysis, and convention enforcement.

An MCP server that converts Markdown files containing Mermaid diagrams into PDF documents by rendering diagrams as SVG images. It provides a specialized tool to automate document conversion while ensuring all visual charts are correctly embedded in the final output.

Provides structured external memory for AI assistants, enabling persistent context, branch notes, tacit knowledge, and checklists to overcome AI memory loss and context confusion.

Enables coordinating multiple AI coding sessions by tracking features, decisions, and approval gates in a per-project Postgres database, with atomic IDs and commit-stamped append-only history.

Enables remote control of the Cursor AI agent via chat platforms like GitHub Issues or Telegram, allowing users to start sessions and receive summaries and prompts in a chat thread.

Enables progress-triggered text-to-speech in Cursor Agent, with speak and stop controls and voice matching the system UI language.

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.

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.

A FastMCP server for Cursor platform APIs enabling spend guardrails, cloud agent monitoring, and inter-agent inbox messaging.