「serve」の検索結果

Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.

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Creates and manages Cloud SQL instances for MySQL, PostgreSQL, and SQL Server. Handles backups, high availability, and secure connectivity for relational database workloads on Google Cloud.

日本語の概要は準備中です。原文の説明を表示しています。

Translate Figma nodes into production-ready code with 1:1 visual fidelity using the Figma MCP workflow (design context, screenshots, assets, and project-convention translation). Trigger when the user provides Figma URLs or node IDs, or asks to implement designs or components that must match Figma specs. Requires a working Figma MCP server connection.

日本語の概要は準備中です。原文の説明を表示しています。

WorkorAI talent marketplace skill: candidate job search and employer hiring with white-box match explanations via the WorkorAI MCP server (https://workorai.com/mcp). Use when the user asks to find a job, apply to jobs, respond to employer invitations, or when an employer wants to post jobs, search and evaluate candidates, invite them, and review applicants.

日本語の概要は準備中です。原文の説明を表示しています。

Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.

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Use when the user wants to integrate with the X (Twitter) API via Xquik to search tweets, look up user profiles, extract followers, run giveaway draws, monitor accounts, or access trending topics. Also use when the user mentions 'Xquik,' 'Twitter API,' 'X API,' 'tweet scraper,' 'follower extraction,' or 'Twitter monitoring.' Covers REST API, webhooks, and MCP server setup.

日本語の概要は準備中です。原文の説明を表示しています。

Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clusters for large-scale training.

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Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user wants to connect cognee to external services — switching LLM or embedding providers (OpenAI, Azure, Gemini, Anthropic, Ollama, OpenRouter), changing databases (Postgres, PGVector, Neo4j, Neptune, Turso), S3 storage, or the MCP server for IDE integration.

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user wants to run cognee with Docker or docker compose — trying it out from the prebuilt image, starting the API server in a container, or bringing up the full stack (UI, MCP, Postgres, Neo4j) with compose profiles.

日本語の概要は準備中です。原文の説明を表示しています。

Migrate Redux or React Context to the correct state option (React Query for server state, nuqs for URL/shareable state, Zustand for global client state). Use when refactoring away from Redux/Context, moving state to the right store, or when the user asks to migrate state management.

日本語の概要は準備中です。原文の説明を表示しています。

Customize your own agent — add capabilities, install packages, add MCP servers, edit code or CLAUDE.md. Use when the user asks you to add a feature, install a tool, or modify how you work. For non-trivial code changes, delegate to a builder agent via create_agent.

日本語の概要は準備中です。原文の説明を表示しています。

Use Iron Proxy for external accounts and APIs, including GitHub through gh. Connect credentials through the operator console and diagnose blocked requests without exposing tokens or adding unnecessary MCP servers.

日本語の概要は準備中です。原文の説明を表示しています。

Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.

日本語の概要は準備中です。原文の説明を表示しています。

Add DeltaChat channel integration via @deltachat/stdio-rpc-server. Native adapter — no Chat SDK bridge. Email-based messaging with end-to-end encryption.

日本語の概要は準備中です。原文の説明を表示しています。

Add Matrix channel integration via Chat SDK. Works with any Matrix homeserver.

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When you report a brain page to the user — created, edited, committed, or relayed from a subagent — a working link is part of the deliverable, in the SAME message. Derive the path mechanically (git ls-files --full-name), push BEFORE linking, verify the link resolves when a hosted remote exists, and degrade through a defined fallback chain when it doesn't. Inside brain pages the rule inverts: relative links preserve the link graph; absolute URLs are for chat deliverables only.

日本語の概要は準備中です。原文の説明を表示しています。

Configure, extend, debug, or contribute to PicoClaw itself. Use when the task is about PicoClaw CLI commands, config.json, gateway, auth, models, skills, MCP servers, cron, routing, sessions, self-evolution, built-in slash commands, or repository internals. Use PicoClaw-native workflows, terminology, paths, and configuration.

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Work inside cua Spaces through the cua MCP server. A Space is a remote or local computer the user can watch; you can run commands in it, move files in and out, show its desktop or a single window on the user's screen, start coding agents inside it, teleport a signed-in app session into it, and share the host's network with it. Use when the user mentions Spaces, asks you to do work "in a Space", or wants a task isolated but visible.

日本語の概要は準備中です。原文の説明を表示しています。

Drive a native GUI app (macOS, Windows, Linux) via the cua-driver CLI (default) or MCP server; snapshot its accessibility tree, act through snapshot-bound element tokens, native menu paths, exact window geometry, or pixel coordinates, and verify from fresh state. Use when the user asks you to operate, drive, automate, or perform a GUI task in a real application on the host, or to continue, resume, or recall recent Cua activity.

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Build or adapt a bounded computer-use loop where Cua Driver observes and acts, TypeSafe Jev selects only from application-owned candidate IDs, and the caller validates and verifies every action. Use for the jev-use recipe or similar Jev integrations; do not use it to add model logic or credentials to Cua Driver.

日本語の概要は準備中です。原文の説明を表示しています。

Reference skill for Zoom Rivet SDK. Use after routing to a Rivet-based server workflow when implementing auth handling, webhook consumers, API wrappers, multi-module composition, or Lambda receiver patterns.

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Guidance for the bundled Zoom MCP connectors. Use after routing to an MCP workflow when planning or troubleshooting tool-based access to meetings, recordings, meeting assets, or transcripts. Route Zoom Docs requests to the dedicated Docs MCP server and Whiteboard-specific requests to `zoom-mcp/whiteboard`.

日本語の概要は準備中です。原文の説明を表示しています。

Zoom Meeting SDK for Linux - C++ headless meeting bots with raw audio/video access, transcription, recording, and AI integration for server-side automation

日本語の概要は準備中です。原文の説明を表示しています。