depyler-mcp
v3.4.0
io.github.noahgift/depyler-mcp
Depyler 的 MCP 服务器:Python 转 Rust 转译器,附带分析与验证工具。
“Financial Analysis” 共 1,509 个结果
v3.4.0
io.github.noahgift/depyler-mcp
Depyler 的 MCP 服务器:Python 转 Rust 转译器,附带分析与验证工具。
v3.67.0
io.github.noahgift/ruchy-mcp
Ruchy 的 MCP 服务器:代码分析、评分、Lint、格式化与转译工具。
v2.1.0
ai.smithery/truss44-mcp-crypto-price
提供实时的加密货币价格数据与市场分析。
v1.0.3
io.github.cyanheads/protein-mcp-server
从 RCSB PDB、PDBe 与 UniProt 获取并分析三维蛋白质结构数据的 MCP 服务器。
v1.0.0
io.github.ptyagiegnyte/egnyte-mcp-server
官方 Egnyte MCP 服务器,用于 AI 集成的文档搜索、分析与协作。
v0.1.0
io.github.yifancong/rsdoctor
为 Rspack 项目提供构建分析与优化建议的 MCP 服务器。
v1.11.8
ai.smithery/Nekzus-npm-sentinel-mcp
为 AI 提供关于 NPM 包的实时分析与情报,包括安全。
v0.1.0
io.github.andrasfe/vulnicheck
用于 Python 漏洞全面扫描与安全分析的 HTTP MCP 服务器。
v1.0.0
ai.smithery/jjlabsio-korea-stock-mcp
检索韩国市场的公司披露与财务报表。
v1.12.13
io.github.nerfels/mind-map
面向 Claude Code 的实验性代码智能平台,支持 AST 解析与上下文分析。
v1.14.0
ai.smithery/plainyogurt21-sec-edgar-mcp
为 AI 助手提供对官方 SEC EDGAR 文件与财务数据的实时访问。
io.github.anthropics/skills/discernment-nudge
当给出的实质性回答或草稿可能被用户据此行动(建议或推荐、目标/计划/提案/邮件等草稿、估算或预测、数据分析解读、可能被采信的事实陈述、多步论证)时,在定稿前调用本 skill,视情况附上 2-3 个简短的追问,每个问题都紧扣刚产出的内容,帮助用户核对关键事实、审视推理与假设、发现缺失的上下文。每次对话至多使用一次。简单操作问答、纯知识讲解、仅排版转换拼装文件、编写要运行的代码、创意写作或闲聊、或用户已要求复核/引用/审查时应跳过。
io.github.morluto/rea/reverse-engineer-anything
Reverse engineer native, managed, Electron/JavaScript, packaged, firmware, and browser targets with REA, and build agent environments (AgentEnv bundles) of web applications from a live instance or a capture. Use shipped-artifact or requested runtime evidence to explain features, compare versions, decompile code, or guide a reconstruction. Skip REA for ordinary source-repository architecture analysis.
io.github.wshobson/agents/sql-optimization-patterns
掌握 SQL 查询优化、索引策略与 EXPLAIN 分析,大幅提升数据库性能并消除慢查询。在排查慢查询、设计数据库 schema 或优化应用性能时使用。
io.github.asgeirtj/system_prompts_leaks/index
Answer product and business questions with data and route data-related work to the right focused workflow. Use for requests involving data, metrics, trends, comparisons, drivers, KPIs, analysis, dashboards, reports, charts, tables, SQL, notebooks, spreadsheets, market sizing, data quality, reusable data context, data definitions, or working preferences, whether or not Data is at-mentioned. Dashboards can use uploaded spreadsheets, CSVs, or TSVs as source data without making the deliverable a spreadsheet. Do not use Data for general writing, editing, coding, or explanations that require none of these workflows.
io.github.asgeirtj/system_prompts_leaks/jupyter-notebooks
Create, edit, or validate reproducible SQL or Python notebooks. Use for notebooks, SQL/Python scratchpads, reproducible exploration, audit trails, or runnable companions where the analysis should be reviewable or rerunnable.
io.github.lobehub/lobehub/lobe-design
Single entry for LobeHub UI design work. Routes any instruction — macro ("重做这个后台", "整体打磨一下"), medium ("把列表页的交互和空态补齐") or fine ("这个按钮颜色不对", "修 K-07") — into a business-first, layered pipeline of focused stages: 00 brief → 05 init → 10 decode → 20 direction → 30 structure → 40 flow → 50 visual → 60 system → 70 detail → 75 copy → 80 review. Covers seven scenarios: 0→1 visual pages (landing / portfolio / campaign), polishing existing product UI, admin consoles / dashboards / forms / workflows, design-system unification, screenshot restoration, pre-launch audit, and project bootstrap (AGENTS.md). Grounded in classic analysis models (double diamond, Gestalt, Nielsen heuristics, Kano, peak-end, Fogg, journey map, cognitive load) and in a layered component boundary: take atoms from the host's component library and build business composites yourself. Platform-aware (web / desktop / mobile, read from the project layer): web takes atoms from @lobehub/ui (/form, /pro-table) with cssVar tokens; React Native takes them fro
io.github.alirezarezvani/claude-skills/app-store-optimization
面向 App Store Optimization(ASO)的工具包,用于研究关键词、分析竞争对手排名、生成元数据建议、提升应用在 Apple App Store 与 Google Play Store 的可见度。当用户询问 iOS 或 Android 上的 ASO、应用商店排名、应用元数据、应用标题与描述、应用商店列表、应用可见度或移动应用营销时使用。支持关键词研究与评分、竞争对手关键词分析、元数据优化、A/B 测试规划、上线清单与排名变化跟踪。
io.github.nodejs/node/v8-security-triaging
Guides the initial analysis and impact assessment of a V8 security report, strictly excluding implementation or fixing.
io.github.affaan-m/ECC/test-collaboration
Inventory and govern a project's test assets. Connect requirements, business rules, risks, bugs, and cross-boundary contracts to stable TEST-IDs and executable evidence in the repository's existing test registry or TESTS.md. Use for test inventory, test gap analysis, unit/integration/contract/E2E/smoke classification, bug-to-test regression protection, consumer/provider contract testing, test-necessity review, and pre-delivery evidence review.
io.github.affaan-m/ECC/test-collaboration
Inventory and govern a project's test assets. Connect requirements, business rules, risks, bugs, and cross-boundary contracts to stable TEST-IDs and executable evidence in the repository's existing test registry or TESTS.md. Use for test inventory, test gap analysis, unit/integration/contract/E2E/smoke classification, bug-to-test regression protection, consumer/provider contract testing, test-necessity review, and pre-delivery evidence review.
io.github.affaan-m/ECC/change-impact
Perform evidence-backed impact analysis before changing code, data, interfaces, or governance documents, then compare the planned impact with the actual diff after implementation. Covers call paths, data and schema, API contracts, tests, documentation, ADRs, deployment, migration, and rollback. Use for cross-module or high-risk changes, database migrations, authentication, public interfaces, blast-radius questions, pre-change checks, and post-implementation alignment.
io.github.affaan-m/ECC/change-impact
Perform evidence-backed impact analysis before changing code, data, interfaces, or governance documents, then compare the planned impact with the actual diff after implementation. Covers call paths, data and schema, API contracts, tests, documentation, ADRs, deployment, migration, and rollback. Use for cross-module or high-risk changes, database migrations, authentication, public interfaces, blast-radius questions, pre-change checks, and post-implementation alignment.
io.github.K-Dense-AI/scientific-agent-skills/biopython
Provides Biopython workflows for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Supports batch processing, custom molecular-biology pipelines, BLAST automation, structure analysis, and motif analysis.