Run GPU workloads on Modal — training, fine-tuning, inference, batch processing. Zero-config serverless: no SSH, no Docker, auto scale-to-zero. Use when user says \"modal run\", \"modal training\", \"modal inference\", \"deploy to modal\", \"need a GPU\", \"run on modal\", \"serverless GPU\", or needs remote GPU compute.
Run a composable MCP test server by hand — pick the showcase config for a feature or bug, build it, and connect with the right protocol era. Use when a change, a PR or a smoke test needs a real server to exercise it; when reproducing a reported bug by hand; when choosing which fixture or protocol era to run; when a fixture keeps serving stale code after an edit; or when the config or preset you need does not exist yet.
Start, stop, and restart the OmniRoute server from the CLI. Manage daemon mode, port configuration, auto-recovery, system tray integration, and the dashboard open shortcut.
Decide when Zoom MCP is the right fit and produce a safe setup plan for Claude. Use when planning AI workflows over Zoom data, deciding between MCP and REST, or defining a hybrid MCP architecture.
Review the implementation source code of MCP (Model Context Protocol) servers, clients, and tool handlers against a security baseline — authentication, sessions, rate limiting, input-schema validation, official-SDK usage, RCE vectors, and the OWASP MCP Top 10 — producing a report with file/line evidence. Use this skill when: - Reviewing an MCP server implementation for security before release - Checking a server against the baseline controls (MCP-01 to MCP-05) and the OWASP MCP Top 10 - Auditing tools for RCE vectors (command/code injection, unsafe deserialization, path traversal, SSTI, dependency hijacking, SSRF) - Verifying auth, session, rate-limiting, and input-validation controls on a network-exposed server - Reviewing MCP client code that handles untrusted server responses and session IDs - Requests like "review this MCP server for security" or "is my MCP server implementation secure?"
Build Model Context Protocol (MCP) servers in C#/.NET against the current ModelContextProtocol 2.x NuGet packages. Helps with cases the model gets wrong without guidance — stale versions (0.x preview or 1.x-era defaults), the v2 stateless-by-default HTTP flip, the 2026-07-28 spec deprecations (roots/sampling/logging), MCP Apps and Tasks extension packages, elicitation URL mode, per-session HTTP wiring, OAuth and reverse-proxy deploy specifics, and debugging MapMcp / STDIO / Streamable-HTTP errors. Also covers STDIO and Streamable HTTP transports (SSE is deprecated), tools, prompts, resources, completions, and a basic .NET MCP client. Trigger when the user says or implies any .NET MCP server work: ModelContextProtocol, McpServerTool, MapMcp, WithStdioServerTransport, "MCP server in C#", "MCP tool in dotnet", "expose this as MCP", or names a primitive (prompt/resource/elicitation/MCP App) in a .NET context. Skip for MCP work in other languages.
This skill should be used when the user asks to "add MCP server", "integrate MCP", "configure MCP in plugin", "use .mcp.json", "set up Model Context Protocol", "connect external service", mentions "${CLAUDE_PLUGIN_ROOT} with MCP", or discusses MCP server types (SSE, stdio, HTTP, WebSocket). Provides comprehensive guidance for integrating Model Context Protocol servers into Claude Code plugins for external tool and service integration.
Stores, retrieves, and manages data as objects in Cloud Storage (Google Cloud Storage, or GCS) buckets. Use when you need to interact with Cloud Storage — set up a Storage MCP server (remote or local Toolbox), create or configure buckets, upload, download, stream, or transfer data, organize objects with folders, generate signed URLs, control access (IAM, ACLs, public access prevention), set storage classes (Standard, Nearline, Coldline, Archive), manage lifecycle and cost, protect data (versioning, CMEK, retention, Bucket Lock, holds, soft delete), host static websites, trigger Pub/Sub notifications, mount buckets (gcsfuse), or optimize performance. Covers gcloud storage / gsutil, JSON/XML APIs, client libraries, Terraform, and Cloud Storage MCP servers. Don't use for non-Storage MCP servers, block storage (Persistent Disk), BigQuery, or databases (Cloud SQL, Spanner, Bigtable, Firestore).
This skill should be used when the user asks to "add MCP server", "integrate MCP", "configure MCP in plugin", "use .mcp.json", "set up Model Context Protocol", "connect external service", mentions "${CLAUDE_PLUGIN_ROOT} with MCP", or discusses MCP server types (SSE, stdio, HTTP, WebSocket). Provides comprehensive guidance for integrating Model Context Protocol servers into Claude Code plugins for external tool and service integration.
Architecture and hard-won debugging lessons for customization enablement (plugins, MCP servers, agents, skills, instructions) in the agent host. Use when changing how customizations are discovered, published, enabled/disabled, or handed to a provider SDK; when a customization shows the wrong enabled state in the UI; or when a disabled MCP server or plugin is still reaching the model.
Verify an MCP server before release by exercising a real protocol session, comparing runtime capabilities with source and documentation, testing failure paths, and recording reproducible evidence. Use when shipping or reviewing an MCP server, tool, resource, prompt, catalog, or install path.
Use Hugging Face Hub via MCP server tools. Search models, datasets, Spaces, papers. Get repo details, fetch documentation, run compute jobs, and use Gradio Spaces as AI tools. Available when connected to the HF MCP server.
This skill should be used when the user wants to build an "MCP app", add "interactive UI" or "widgets" to an MCP server, "render components in chat", build "MCP UI resources", make a tool that shows a "form", "picker", "dashboard" or "confirmation dialog" inline in the conversation, or mentions "apps SDK" in the context of MCP. Use AFTER the build-mcp-server skill has settled the deployment model, or when the user already knows they want UI widgets.
Debug, support, and build PostHog MCP Analytics — product analytics for MCP servers (the `@posthog/mcp` and `posthog.mcp` SDKs plus the mcp_analytics product). Use when MCP analytics data looks wrong or missing ("events aren't showing", "intent clusters are empty", "sessions are missing", "per-tool numbers look wrong"), when writing queries over `$mcp_*` events by hand, or when doing feature work on the SDKs, the dashboard and its query runners, the self-instrumented MCP server, the `wizard mcp-analytics` install command, or the in-app onboarding. Covers the repo map, the `$mcp_*` vocabulary and where each property comes from, the rules that silently corrupt metrics when ignored, the end-to-end pipeline and where each stage breaks, and which repo to change. For reading the data rather than fixing it, prefer the `exploring-mcp-*` and `improving-mcp-tools` skills.
Interface for MCP (Model Context Protocol) servers via CLI. Use when you need to interact with external tools, APIs, or data sources through MCP servers, list available MCP servers/tools, or call MCP tools from command line.
Build and deploy an MCP server from an OpenAPI / Swagger spec using the mcp-use TypeScript SDK. Use this skill whenever the user wants to "turn this OpenAPI spec into an MCP server", "make this API usable from Claude/ChatGPT", "wrap this Swagger doc as MCP tools", "expose this REST API to an LLM", "generate MCP tools from a spec", or pastes/attaches an `openapi.yaml`, `openapi.json`, or `swagger.json` and asks for a Claude-compatible version. Trigger even if the user doesn't say "MCP" — if they describe an existing HTTP API (REST endpoints, an internal service, a third-party API they have a key for) and want an LLM to call it, this is the right skill. Covers spec ingestion (file path, URL, or pasted), operation-to-tool mapping, auth wiring (apiKey, bearer, basic, OAuth bearer), scaffolding with `create-mcp-use-app`, tool generation with proper zod schemas, live testing in the mcp-use inspector, and deploying to Manufact / mcp-use cloud.
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the privacy/cost/offline trade-offs. Based on Lesson 17 of AI Agents for Beginners. USE FOR: run an agent locally, offline agent, on-device agent, Foundry Local, Qwen function calling, local tool calling, local RAG, Chroma vector database, local MCP server, privacy-preserving agent, hybrid local and cloud agent, small language model agent, engineering assistant on my machine. DO NOT USE FOR: deploying agents to the cloud at scale (use deploying-scalable-agents / Lesson 16), building your first agent concept (Lesson 01), Foundry (cloud) hosted agents, GPU cluster / server-side inference provisioning.
Build, modify, debug, migrate, review, or verify TypeScript MCP servers and MCP Apps with mcp-use. Use for tools, resources, prompts, middleware, Views, authentication, Skills over MCP, scaffolding, and advanced features.
Plain text files in a repository that tell a coding agent how the project works: commands to run, conventions to follow and things to avoid. CLAUDE.md, AGENTS.md, cursor rules and skills are the common kinds.
CLAUDE.md or AGENTS.md?
CLAUDE.md is read by Claude Code. AGENTS.md is an open format that Codex, Cursor and other agents read. Many projects keep one and point the other at it.
What is a skill?
A folder with a SKILL.md that describes one capability, such as filling PDFs or reviewing code. The agent loads it only when the task calls for it.
Can I search my own team's files too?
Your agents already can, over MCP, limited to the files you're allowed to read. Searching them from this page is coming.