Cursor 必备 MCP 组合推荐

在使用 `esm` Python SDK、ESM3 或 ESMC 模型 ID、Forge/Biohub 推理客户端或 ESMFold2 折叠工作流时使用。

Python 统计模型库。当需要具体的模型类（OLS、GLM、混合模型、ARIMA）并要详尽的诊断、残差与推断时使用。最适合计量经济学、时间序列，以及带系数表的严格推断。需要引导式统计检验选择与 APA 报告时使用 statistical-analysis。

使用 scikit-learn 在 Python 中进行机器学习。适用于监督学习（分类、回归）、无监督学习（聚类、降维）、模型评估、超参数调优、预处理或构建 ML 流水线。提供算法、预处理技术、流水线与最佳实践的全面参考文档。

将科学 Python 工作负载加速到 NVIDIA GPU 上，并验证结果正确且更快。适用于 CUDA/GPU 优化；CPU 受限的 NumPy、SciPy、pandas、scikit-learn、NetworkX、scikit-image、向量检索、图像处理、图、仿真或文件 I/O 负载；CuPy、cuDF、cuML、cuGraph、cuVS、cuCIM、KvikIO、Warp、Newton、Numba-CUDA、RAFT 相关问题；以及性能剖析、内存搬运、kernel 或多 GPU 瓶颈。当大规模数据并行的 Python 代码很慢且 GPU 加速是合理选项时也应使用，即使用户没有提到 CUDA。

Benchling Python SDK 与 REST API 集成，覆盖 registry 实体、库存、ELN 条目、工作流、Benchling Apps 与 Data Warehouse 查询。在使用 benchling-sdk 或 v2 API 自动化实验室数据时使用。

面向需要 Astropy API 的天文与天体物理工作流的核心 Python 库，涵盖单位/量纲、坐标、FITS I/O、表格、时间系统、WCS 与宇宙学。在使用 Astropy 实现或调试天文数据分析代码时使用。

RDKit 的 Pythonic 封装，接口更简单、默认值更合理。标准药物发现任务的首选：SMILES 解析、标准化、描述符、指纹、聚类、3D 构象、并行处理。返回原生 rdkit.Chem.Mol 对象。需要高级控制或自定义参数时直接使用 rdkit。

基于 Python/HTSlib 的基因组文件工作流。在使用 pysam 读取、查询、过滤或写出 SAM/BAM/CRAM、VCF/BCF、FASTA/FASTQ 或 tabix 数据时使用，包括 pileup、覆盖度、索引与 CRAM 参考。

用于云存储的分块 N 维数组（Zarr-Python 3）。压缩数组、并行 I/O、经 fsspec 访问 S3/GCS、兼容 NumPy/Dask/Xarray，适用于大规模科学计算流水线。

使用 GXL 的 Paperclip CLI 检索和阅读生物医学论文全文、FDA/PMDA/EMA 监管文件、临床试验注册信息和 UniProt/PDB/ChEMBL 条目。涵盖用 PAPERCLIP_API_KEY 安装与鉴权 `paperclip` 二进制、/papers、/fda、/trials、/proteins、/clipboard 下的只读虚拟文件系统、来源范围的语义搜索、全语料 grep、元数据查询与 SQL、跨多篇论文的 map/reduce 阅读、图像视觉分析、带论断核验的可选论文仓库，以及锁定行号的引用。当被要求安装 paperclip、运行 paperclip search/grep/map/reduce/sql/repo、通过 paperclip 查找或阅读生物医学文献、监管文件或临床试验，或生成带行号的引用时使用。

在 11 个学术文献 API 中检索论文、预印本、引用与开放获取全文，并返回可复现的溯源结果。覆盖 PubMed、PMC（全文）、Europe PMC（全文与预印本检索）、bioRxiv、medRxiv、arXiv、OpenAlex、Crossref、Semantic Scholar、CORE、Unpaywall。适用于检索论文、引用、DOI/PMID/arXiv、摘要、全文、开放获取 PDF、预印本、引用网络、作者发文或任何学术文献查询。提及任一受支持数据库，或“find papers on X”“look up this DOI”“who cites this paper”“get me the PDF”等请求会触发。

40+ 生物信息学服务的统一 Python 接口。适用于在单个工作流中查询多个数据库（UniProt、KEGG、ChEMBL、Reactome）并使用一致的 API。最适合跨库分析与跨服务 ID 映射。快速单库查询用 gget；序列/文件操作用 biopython。

对 20+ 生物信息学数据库的快速 CLI/Python 查询。适合快速查询：基因信息、BLAST/BLAT、病毒序列下载、AlphaFold 结构、富集分析、OpenTargets、COSMIC、CELLxGENE 以及 8cube 小鼠特异性/表达数据。最适合交互式探索和简单查询。批量处理或高级 BLAST 用 biopython；跨库 Python 工作流用 bioservices。

以显式端点、筛选条件、分页与溯源方式查询有文档的公共数据库 API。当需要以可复现方式从具名来源获取科学、监管、金融等数据库支撑的事实（而非依赖通用知识推断）时使用。

Use this skill for Laravel MCP development. Trigger when creating or editing MCP tools, resources, prompts, servers, or UI apps in Laravel projects. Covers: artisan make:mcp-* generators, routes/ai.php, Tool/Resource/Prompt/AppResource classes, schema validation, shouldRegister(), OAuth setup, URI templates, read-only attributes, MCP debugging, MCP UI apps, the x-mcp::app Blade component, createMcpApp(), default AppResource handle() auto-infers view from class name, Response::view(), AppMeta/Csp/Permissions/appMeta() configuration, #[RendersApp] attribute, Library enum for CDN libraries (Tailwind, Alpine), and host theming via CSS variables. Use this whenever the user mentions MCP apps, MCP UI, interactive MCP resources, styling MCP apps with Tailwind or Alpine, or building visual interfaces for AI agents.

Use this skill to analyze how a Laravel application is actually written and record its conventions as shared rules. Trigger when the user wants to detect, infer, document, or standardize project conventions or coding style, set up or grow `.ai/rules`, resolve mixed or conflicting patterns (e.g. "are we using Form Requests or inline validation?"), or onboard agents and teammates to "how we do things here". Covers: a systematic sweep of ~49 Laravel convention dimensions (validation, models, architecture, testing, frontend, database, console), open-ended house-pattern discovery, conflict reporting, and recording rules scoped to the right paths via the Boost `record-rule` MCP tool. Only run this skill when the user explicitly asks for it; never start a sweep as part of another task. Do not use for one-off code review, enforcing formatting a linter already handles, or editing `.ai/rules` files by hand.

在编写、审查或重构 Laravel PHP 代码时使用。包括创建或修改控制器、模型、迁移、表单请求、策略、任务、定时命令、服务类与 Eloquent 查询。涉及 N+1 与查询性能、缓存策略、授权与安全模式、校验、错误处理、队列与任务配置、路由定义和架构决策时触发。也用于 Laravel 代码审查及将现有 Laravel 代码重构至最佳实践。覆盖一切 Laravel 后端 PHP 代码模式的任务。

用户消息以任何形式包含 'tailwind' 时始终调用。还适用于:构建响应式栅格布局(多列卡片栅格、商品栅格)、flex/grid 页面结构(带侧边栏的仪表盘、固定顶栏、移动端可折叠导航)、UI 组件样式(卡片、表格、导航栏、价格区、表单、输入框、徽章)、添加暗色模式变体、修复间距或排版,以及 Tailwind v3/v4 工作。核心场景:在 HTML 模板(Blade、JSX、Vue)中编写或修正 Tailwind 工具类。跳过:后端 PHP 逻辑、数据库查询、API 路由、无 HTML/CSS 部分的 JavaScript、CSS 文件审计、构建工具配置和原生 CSS。

Find, use, create, install, share, update, and migrate agent skills stored in OpenViking (viking://~/skills and viking://agent/skills). Use it when a search result, or the session's <available-skills> list where the harness injects one, names a skill that fits the task; when a task looks like one a stored skill would cover; when the user asks to write, save, install, or share a skill from text, a Git repository, or a local folder; when a skill should work in every harness and on every machine; or when the user wants to move local skills (~/.claude/skills, ~/.agents/skills, ~/.cursor/skills) into OpenViking — "upload my skills", "save this as a skill", "迁移本地 skill", "把 skill 存到 OpenViking", "新建一个 skill". Covers the add_skill tool, running a skill's helper files, and which local skills must stay local.

Install, build and run a server from this checkout. Use when starting a server locally over stdio, SSE or Streamable HTTP; when pointing npx, uvx or an MCP client config at the local build; when a running server still shows old code, or dist is missing; when setting up a git worktree; or when adding an overrides pin.

MyBatis and MyBatis-Spring patterns for mapper design, XML and annotation SQL, result mapping, dynamic SQL safety, transactions, batching, pagination, and query performance. Use when building or reviewing Java persistence code with MyBatis, Spring Boot, MyBatis-Spring, or MyBatis-based legacy applications.

设置或检查 claude-mem 与 cmem.ai Pro 的云同步。当用户说「set up cloud sync」「sync my memories」「cmem pro」「cloud backup」「sync status」，或希望备份/同步记忆数据库到其 cmem.ai 账户时使用。

对当前分支功能做完整的 UI 调查。枚举每个视图与状态（空态、有数据、加载、错误、每个对话框/菜单/面板、响应式断点、浅色+暗色+RTL），用内置 Playwright 工装捕获，汇总为带全局明暗切换滑杆的单图 HTML 走查，随后跑两轮审查：视觉/一致性（对齐、间距、专业感、明暗一致、对比度、截断）与 UX/易用性（流程、可发现性、可供性、空态/错误态、预期）。当被要求做 UI 走查、截图审查、设计或 QA 巡检、「找出可以更易用/更好的地方」或前端工作合并前使用。加 --fix 自动应用安全的前端修复并重新捕获；--theme 限定主题；--no-rtl 跳过 RTL。

Run the Airbyte protocol sweep for airbyte/source-snowflake:<tag> against the shared Snowflake integration account inside a per-run PROVEFIX_<run_id> schema (B3 remote-backend mode of db-harness-lib); prove-fix comparisons, cursor canary, orphan sweep.

为标准与 Autopilot 集群规划、执行并验证 Google Kubernetes Engine（GKE）集群升级与维护操作。产出升级计划、升级前后检查清单、含 gcloud 命令的维护 Runbook、发布通道策略与故障排查指南。处理节点池升级策略（surge、蓝绿）、版本兼容、PDB 管理，以及有状态、GPU、operator 等工作负载的特定关注点。每当用户提及 GKE 升级、Kubernetes 版本升级、节点池维护、GKE 打补丁、集群版本管理、发布通道选择、维护窗口、surge 升级、卡住的升级，或任何 GKE 生命周期管理任务——即便是随意的「我们需要升级集群」或「规划下次 GKE 维护」或「我们的升级卡住了」——都使用本技能。不用于 GKE 集群创建、应用接入、一般网络/路由配置或安全策略配置（改用 gke-basics 或相关 GKE 技能）。

Laravel security best practices — authentication, authorization, Eloquent safety, CSRF, XSS prevention, API security, and secure deployment configurations. Use when reviewing Laravel auth, Eloquent safety, CSRF, XSS, API security, or deployment configuration.

在审计或修正读起来像泄漏推理记录的文案时使用——例如（决策 N）、审计条目编号等指向未提交草稿的陈旧设计会话引用；used to、no longer、this cut 之类的变更叙述；基于栈或评审视角的表述（本 stack 中后续的 PR、评审中被否决）；面向评审者的辩解；控制流叙述；以及注释、JSDoc、文档、Agent Notes 中残留的规划性试探语气。

使用 `@logseq/libs` SDK（TypeScript/JavaScript，iframe/shadow 沙箱）构建、调试或审查 Logseq 插件。适用于编写插件入口代码、注册 slash/命令/UI 项、provideUI/provideStyle/provideModel、设置 schema、macro renderer、DB 图的属性与标签、Datascript/DSL 查询、实验性 API、主题插件，或本包生成的 `logseq/*` CLJS facade。

在 PixiJS v8 中处理指针、鼠标、触摸或滚轮输入时使用。覆盖 eventMode（none、passive、auto、static、dynamic）、FederatedEvent 类型、冒泡与捕获阶段、hitArea、interactiveChildren、cursor 与 cursorStyles、用于拖拽的全局移动事件以及 eventFeatures 配置。触发词：eventMode、FederatedPointerEvent、pointerdown、click、tap、globalpointermove、drag、hitArea、cursor、stopPropagation。

Run, configure, and troubleshoot OpenAI Codex CLI in non-interactive headless environments. Use for Codex automation in Bash or PowerShell, native Windows or WSL2, shell scripts, CI/CD, Docker, Kubernetes, remote servers, agent harnesses, or batch jobs; for constructing `codex exec` commands; selecting sandbox and approval modes; consuming JSONL events or structured output; resuming sessions; passing prompts through stdin; and handling failures caused by unavailable interactive input such as `request_user_input`.

Run PowerToys UITest.Next suites in persistent Hyper-V VMs over PowerShell Direct. Validate full default and constrained suites on Windows 10 and Windows 11, plus applicable ARM64 guests, then automatically hand implementation tasks to ui-tests-pipeline-ci for commit/push and CI validation. Local green is not end-to-end completion. Use for agentic UI-test iteration, reusable standard-user desktops, payload staging, evidence export, VM customization, clean baselines, or hosts without nested virtualization. Keywords: Hyper-V, local VM, virtual machine, PowerShell Direct, Copy-VMFile, VMBus, checkpoint, unattend, autounattend, ISO, Windows 10 LTSC, Windows 11, ARM64, Windows on ARM, UI tests, UITest.Next, winappcli, TRX, CI handoff.

面向 API、智能体与 LLM 端点的访问控制与授权模式。

End-to-end methodology for AI agents and software engineers to add machine learning algorithms to existing non-ML codebases. Covers problem framing, data readiness, architectural decoupling, and baseline model integration. Use when adding a machine learning capability to a codebase that has none, from problem framing through a baseline model.

Analyze an unfamiliar codebase and generate a structured onboarding guide with architecture map, key entry points, conventions, and a starter CLAUDE.md. Use when joining a new project or setting up Claude Code for the first time in a repo.

Create CodeTour `.tour` files — persona-targeted, step-by-step walkthroughs with real file and line anchors. Use for onboarding tours, architecture walkthroughs, PR tours, RCA tours, and structured "explain how this works" requests. Use when the user asks for a code tour, onboarding walkthrough, PR tour, or an explanation of how a subsystem works.

Idiomatic Kotlin patterns, best practices, and conventions for building robust, efficient, and maintainable Kotlin applications with coroutines, null safety, and DSL builders. Use when writing or reviewing Kotlin code and idiomatic structure or null safety is in question.

Idiomatic Rust patterns, ownership, error handling, traits, concurrency, and best practices for building safe, performant applications. Use when writing or reviewing Rust code and ownership, error handling, traits, or concurrency is in question.

Idiomatic C# and .NET patterns, conventions, dependency injection, async/await, and best practices for building robust, maintainable .NET applications. Use when writing or reviewing C# / .NET code — DI, async, or general conventions.

Test-driven development for Spring Boot using JUnit 5, Mockito, MockMvc, Testcontainers, and JaCoCo. Use when adding features, fixing bugs, or refactoring.

Trace every user-facing button/touchpoint through its full state change sequence to find bugs where functions individually work but cancel each other out, produce wrong final state, or leave the UI in an inconsistent state. Use when: systematic debugging found no bugs but users report broken buttons, or after any major refactor touching shared state stores.

Test-driven development workflow: write a failing test first, watch it fail, implement the smallest change to green, then refactor with 80%+ coverage across unit, integration, and E2E tests. Use when writing a new feature, fixing a bug, refactoring, or when told to write failing tests first.

PyTorch deep learning patterns and best practices for building robust, efficient, and reproducible training pipelines, model architectures, and data loading. Use when writing or reviewing PyTorch training loops, model architectures, or data loading, or when a run will not reproduce.

Nuxt 4 app patterns for hydration safety, performance, route rules, lazy loading, and SSR-safe data fetching with useFetch and useAsyncData. Use when building or reviewing a Nuxt 4 app, or debugging hydration mismatches and SSR-safe data fetching.

Modern Perl 5.36+ idioms, best practices, and conventions for building robust, maintainable Perl applications. Use when writing or reviewing modern Perl 5.36+ code.

Idiomatic Go patterns, best practices, and conventions for building robust, efficient, and maintainable Go applications. Use when writing or reviewing Go code and idiomatic structure or conventions are in question.

Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.

Local-evidence production readiness audit for shipped apps, pre-launch reviews, post-merge checks, and "what breaks in prod?" questions without sending repo data to an external audit service. Use when auditing production readiness before launch, after a merge, or when asked what breaks in prod.

C++ coding standards based on the C++ Core Guidelines (isocpp.github.io). Use when writing, reviewing, or refactoring C++ code to enforce modern, safe, and idiomatic practices.