mcp-deepwiki
Query public GitHub repos via DeepWiki MCP — AI-powered answers about architecture, internals, and design decisions without cloning. Use for: 'how does this repo work', 'explain the architecture of X', 'compare two frameworks'. No auth required.
What this skill does
<objective> Query public GitHub repositories through the DeepWiki MCP server. Get AI-powered answers about repo architecture, internals, design decisions, and usage patterns — without cloning the repo locally. No authentication required. **DeepWiki vs Context7 vs GitHub MCP**: - **DeepWiki**: Architecture, internals, design decisions — "How does X work under the hood?" - **Context7**: API docs, code examples, usage patterns — "How do I use X?" - **GitHub MCP**: Source code, PRs, issues, commits — "What does the code say?" </objective> <process> ## Investigation Workflow For understanding an unfamiliar repo, follow this order: ### 1. Browse Structure First See what documentation topics are available: ```bash mcporter call 'deepwiki.read_wiki_structure(repoName: "facebook/react")' --output json ``` Returns a table of contents for the repo's wiki. Use this to understand what's documented before asking questions. ### 2. Ask Targeted Questions Best for specific questions. Returns AI-powered, context-grounded answers: ```bash mcporter call 'deepwiki.ask_question(repoName: "facebook/react", question: "How does the fiber reconciler work?")' --output json ``` ### 3. Read Full Wiki (Use Sparingly) Gets the complete documentation for a repo. **Warning**: Can return 10K+ tokens. Only use when you need a comprehensive dump: ```bash mcporter call 'deepwiki.read_wiki_contents(repoName: "facebook/react")' --output json ``` **Prefer `ask_question` for targeted queries** — it's faster and returns only relevant content. ## Multi-Repo Comparison Compare approaches across repos (max 10): ```bash mcporter call 'deepwiki.ask_question(repoName: ["vercel/next.js", "remix-run/remix"], question: "How do these frameworks handle server-side rendering differently?")' --output json ``` ## Common Patterns ```bash # Understand a library's architecture mcporter call 'deepwiki.ask_question(repoName: "steipete/mcporter", question: "How does the config discovery and merging work?")' --output json # Investigate design decisions mcporter call 'deepwiki.ask_question(repoName: "anthropics/claude-code", question: "How does the permission system work?")' --output json # Compare competing libraries mcporter call 'deepwiki.ask_question(repoName: ["expressjs/express", "fastify/fastify"], question: "How do these handle middleware differently?")' --output json # Explore what docs exist before deep diving mcporter call 'deepwiki.read_wiki_structure(repoName: "langchain-ai/langchain")' --output json ``` </process> <tips> - **Start with `read_wiki_structure`** to see what's available, then use `ask_question` for specifics. - **`ask_question` is your primary tool** — it returns focused, relevant answers without the token cost of a full wiki dump. - **`read_wiki_contents` is expensive** — it returns the entire wiki (often 10K+ tokens). Only use it when you need comprehensive coverage. - The `repoName` format is always `owner/repo` (e.g., "facebook/react"). - For multiple repos, pass an array (max 10): `repoName: ["repo1", "repo2"]` - No authentication required — works out of the box. - Best for **public repos only** — private repos won't be accessible. - Use `--output json` for machine-readable results. </tips>
Related in Design
contribute
IncludedLocal-only OSS contribution command center. Auto-refreshes the user's in-flight PR and issue state on invoke so conversations start with full context — no need to brief Claude on what's in flight. Helps the user find issues to contribute to on GitHub, builds per-repo dossiers of what each upstream expects (CLA, DCO, branch convention, AI policy, draft-first, review bots, issue templates), runs deterministic gates before any external action so AI-assisted contributions don't reach maintainers as slop. State is markdown-only: candidate files at ~/.contribute-system/candidates/, repo dossiers at ~/.contribute-system/research/, append-only event log at ~/.contribute-system/log.jsonl. No database, no cloud calls. Use when the user asks about their PRs / issues / contributions, wants to find new work to take on, claim an issue, build/refresh a repo's dossier, or draft a Design Issue or PR. Trigger with "/contribute", "what's my PR status", "find a contribution", "claim issue X", "draft a Design Issue for Y", "refresh dossier for Z".
architectural-analysis
IncludedUser-triggered deep architectural analysis of a codebase or scoped subtree across eight modes — information architecture, data flow, integration points, UI surfaces, interaction patterns, data model, control flow, and failure modes. This skill should be used when the user asks to "diagram this codebase," "map the architecture," "show the data flow," "give me an ERD," "trace control flow," "find the integration points," "verify the layout pattern," "audit the UX architecture," or any similar request whose primary deliverable is mermaid diagrams plus cited reports under docs/architecture/. Dispatches haiku/sonnet sub-agents in parallel for per-mode exploration, then verifies every citation mechanically before any node lands in a diagram. Not for one-off prose explanations of code (use code-explanation) or for high-level system design from scratch (use system-design).
mcp
IncludedModel Context Protocol (MCP) server development and tool management. Languages: Python, TypeScript. Capabilities: build MCP servers, integrate external APIs, discover/execute MCP tools, manage multi-server configs, design agent-centric tools. Actions: create, build, integrate, discover, execute, configure MCP servers/tools. Keywords: MCP, Model Context Protocol, MCP server, MCP tool, stdio transport, SSE transport, tool discovery, resource provider, prompt template, external API integration, Gemini CLI MCP, Claude MCP, agent tools, tool execution, server config. Use when: building MCP servers, integrating external APIs as MCP tools, discovering available MCP tools, executing MCP capabilities, configuring multi-server setups, designing tools for AI agents.
react-native-skia
IncludedDesign, build, debug, and optimise high-polish animated graphics in React Native or Expo using @shopify/react-native-skia, Reanimated, and Gesture Handler. Use when the user wants canvas-driven UI, shaders, paths, rich text, image filters, sprite fields, Skottie, video frames, snapshots, web CanvasKit setup, or performance tuning for custom motion-heavy elements such as loaders, hero art, cards, charts, progress indicators, particle systems, or gesture-driven surfaces. Also use when the user asks for fluid, glow, glass, blob, parallax, 60fps/120fps, or GPU-friendly animated effects in React Native, even if they do not explicitly say "Skia". Do not use for ordinary form/layout work with standard views.
plaid
IncludedProduct Led AI Development — guides founders from idea to launched product. Six capabilities: Idea (discover a product idea), Validate (pressure-test the idea against fatal flaws, problem reality, competition, and 2-week MVP feasibility), Plan (vision intake + document generation), Design (translate image references into a design.md spec), Launch (go-to-market strategy), and Build (roadmap execution). Use when someone says "PLAID", "plaid idea", "help me find an idea", "product idea", "idea from my business", "idea from my expertise", "plaid validate", "validate my idea", "pressure-test", "is this idea good", "find fatal flaws", "validate the problem", "plan a product", "define my vision", "generate a PRD", "product strategy", "plaid design", "design from image", "translate image to design", "create design.md", "extract design tokens", "plaid launch", "go-to-market", "launch plan", "GTM strategy", "launch playbook", "plaid build", "build the app", "start building", or "execute the roadmap".
nextjs-framer-motion-animations
IncludedAdds production-safe Motion for React or Framer Motion animations to Next.js apps, including reveal, hover and tap micro-interactions, whileInView, stagger, AnimatePresence, layout and layoutId transitions, reorder, scroll-linked UI, and lightweight route-content transitions. Use when the user asks to add, refactor, or debug Motion or Framer Motion in App Router or Pages Router codebases, especially around server/client boundaries, reduced motion, LazyMotion, bundle size, hydration, or route transitions. Avoid for GSAP-style timelines, WebGL or 3D scenes, heavy scroll storytelling, or CSS-only effects unless Motion is explicitly requested.