Results for “mcp-server”

Design generation using V0 (v0.dev) via the official MCP server. Generates production React/Tailwind/Shadcn components with live preview URLs. Use for all design generation — original designs and clone workflows. Replaces Stitch for primary generation.

针对 Modular RAG MCP Server 项目的老师式复习 Agent。按章节带领用户系统复习项目知识点，每道题互动问答、给出参考答案，复习结束后记录掌握进度，每次开始时回顾上次进度并建议继续或复习。Use when user says '复习项目', '帮我复习', '带我复习', '开始复习', '项目复习', 'review project', 'study review', '学习复习', '复盘', or wants to systematically review and study the project.

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.

Query NFT and token data, browse drops, stream events, and search across Ethereum, Base, Arbitrum, Optimism, Polygon, and more using the official CLI, SDK, MCP server, or shell scripts.

针对 Modular RAG MCP Server 项目的老师式复习 Agent。按章节带领用户系统复习项目知识点，每道题互动问答、给出参考答案，复习结束后记录掌握进度，每次开始时回顾上次进度并建议继续或复习。Use when user says '复习项目', '帮我复习', '带我复习', '开始复习', '项目复习', 'review project', 'study review', '学习复习', '复盘', or wants to systematically review and study the project.

Integrate Xquik into apps, scripts, data pipelines, or AI agents for X API tasks like tweet search, user lookup, follower export, media actions, and webhook verification.

Query NFT and token data, trade NFTs on Seaport, swap ERC20 tokens via DEX aggregator, configure wallet signing providers, and build/register/gate AI agent tools on Base.

Access ATXP's paid API tools for web search, AI image generation, music creation, video generation, and X/Twitter search via CLI or programmatic client.

针对 Modular RAG MCP Server 项目的模拟技术面试 Agent。读取用户简历（可选），围绕三个方向进行最多 3 轮深度追问，结束后生成并持久化面试报告（含参考答案、包装识别点评、评分）。Use when user says '模拟面试', '面试练习', '帮我面试', 'mock interview', 'interview practice', '面试', '考我', '开始面试', or wants to practice interviewing about this project.

Analyzes the downstream impact (blast radius) when a BigQuery table or view is broken, stale, or modified, identifying all affected downstream tables, dashboards, and processes.

Provides authoritative, current guidance from OpenAI developer docs using the developers.openai.com MCP server, including model selection, API migration, and prompt-upgrade guidance.

Verify supply chain integrity for AI agent plugins, tools, and dependencies by generating SHA-256 manifests, detecting tampered files, auditing dependency pinning, and enforcing promotion gates.

针对 Modular RAG MCP Server 项目的模拟技术面试 Agent。读取用户简历（可选），围绕三个方向进行最多 3 轮深度追问，结束后生成并持久化面试报告（含参考答案、包装识别点评、评分）。Use when user says '模拟面试', '面试练习', '帮我面试', 'mock interview', 'interview practice', '面试', '考我', '开始面试', or wants to practice interviewing about this project.

Generates AI-ready context files for any codebase by auto-detecting the tech stack, scoring AI-readiness, and producing a portable .faf file that works across AI tools.

Aspire skill covering the Aspire CLI, AppHost orchestration, service discovery, integrations, MCP server, VS Code extension, Dev Containers, GitHub Codespaces, templates, dashboard, and deployment. Use when the user asks to create, run, debug, configure, deploy, or troubleshoot an Aspire distributed application.

SQLite-backed index over all entity files in the project. The read-side foundation for every other MCP server. Use whenever an agent needs to look up entities by ID, kind, state, or text — instead of grepping the filesystem.

Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, or chat applications. Covers Agent class, state management, callable RPC, Workflows integration, and React hooks.

Guides users through configuring a LaRuche node by reading its live API state and providing click paths for settings, including LLM providers, messaging channels, secrets vault, MCP server, and memory.

Publishes a local Markdown file to a user-specified Confluence location, creating a new page or updating an existing one through the Atlassian MCP server. Use when the user wants to post, publish, push, or sync a Markdown file to a Confluence space or page. Requires a configured Atlassian MCP server. Does not write or generate the Markdown itself — point it at an existing file, or use project-documentation-to-confluence for the document-then-publish flow, or plan-a-feature-to-confluence for the plan-then-publish flow. Does not publish to Jira — use work-items-to-jira.

Identify the right tool for a process step. Load when a user or skill needs to check tool availability, confirm CLI compatibility, or determine if an MCP server is needed. Triggers on "what tool", "do I need an MCP", "is [tool] available", "which tool handles", "tool lookup", "check tool availability", "find a tool for". Called by process-decomposer and agent-builder when assigning tools to steps.

Aspire skill covering the Aspire CLI (start, stop, describe, wait, logs, otel, mcp), AppHost orchestration, service discovery, integrations, MCP server, dashboard, and deployment. Use when the user asks to create, run, debug, configure, deploy, or troubleshoot an Aspire distributed application. USE FOR: aspire start, aspire stop, aspire describe, aspire wait, aspire logs, aspire otel, list aspire integrations, debug aspire issues, aspire dashboard, aspire add, aspire mcp tools, aspire docs. DO NOT USE FOR: non-Aspire .NET apps (use dotnet CLI), container-only deployments (use docker/podman).

Build persistent agents on Azure AI Foundry using the Microsoft Agent Framework Python SDK, with support for function tools, hosted tools, MCP servers, conversation threads, and streaming responses.

Encode video to HLS/MP4, generate thumbnails, resize or watermark images, extract audio, concatenate clips, add subtitles, OCR documents, and build multi-step media processing pipelines using Transloadit's cloud infrastructure.

Use for designing, auditing, or refactoring a GitHub Copilot customization system in Visual Studio Code across instructions, prompt files, Agent Skills, custom agents, hooks, MCP servers, and plugins. Do not use merely to author one already-selected artifact or configure unrelated VS Code settings.

Use when aer-identification has fixed the design, after methodology choice and before aer-robustness or aer-tables-figures, to run an AER-track analysis with StatsPAI — the agent-native Python engine and MCP server for causal inference, robustness, sensitivity, and publication-ready table export.

Build, scaffold, refactor, and troubleshoot ChatGPT Apps SDK applications that combine an MCP server and widget UI. Use when Codex needs to design tools, register UI resources, wire the MCP Apps bridge or ChatGPT compatibility APIs, apply Apps SDK metadata or CSP or domain settings, or produce a docs-aligned project scaffold. Prefer a docs-first workflow through the openai-docs skill or an official OpenAI documentation connector before generating code.

Manages persistent coding sessions across multiple AI coding engines including Claude Code, Codex, Antigravity, Cursor, and OpenCode, with support for multi-agent councils, cross-session messaging, deep planning, parallel code review, and autonomous workspace iteration.

Generates high-fidelity UI screens, multi-page websites, DESIGN.md documentation, and React components from natural-language prompts using the Stitch MCP server, with support for prompt refinement and walkthrough video creation via Remotion.

Install, configure, and extend Pi, a terminal coding harness, with support for custom providers, models, extensions, skills, packages, themes, SDK integration, RPC mode, JSON event streams, and ecosystem packages for subagent delegation, MCP servers, interactive forms, and web access.

Provides nine skills for Nature-journal-family academic publishing, covering figure creation, prose polishing, manuscript writing, citation formatting, data availability statements, paper reading, reviewer responses, paper-to-PPT conversion, and academic search via an MCP server.

为 MODULAR-RAG-MCP-SERVER 添加 Agentic RAG 层并跑出真实评测数据。 作者背景：应届生 + 无实习，目标 Agent 方向求职。 使用场景： 1. 用户说"加 Agent 层" / "实现 ReAct Agent" / "Agentic RAG" / "多步推理" 2. 用户说"跑评测" / "出评测数字" / "Ragas 实测" / "对比指标" 3. 用户说"继续扩建项目" / "Stage J" / "Stage K" 4. 用户在新对话中提到这个 RAG 项目需要扩展 该 skill 记录了所有背景知识、架构决策和实现细节，使 Codex 无需重新探索即可直接执行。

Design, create, audit, and improve Claude Agent Skills with expert-level progressive disclosure. Use when building new skills, reviewing existing skills, debugging activation failures, encoding domain expertise, designing skills for subagent consumption, or understanding platform constraints and distribution surfaces. NOT for general Claude Code features, runtime debugging, non-skill coding, or MCP server implementation.

Process recipe tasks from the Flavor Atlas workspace on ax-gcp MCP server. Pick one recipe task, build it using the FlavorAtlas template, store locally in Artifacts, upload to GitHub AX-CommunityWorkspaces repo, and update tasks/messages. Use when asked to work on recipes, create new recipes, process Flavor Atlas tasks, or build recipe content.

Use to get access to Rulebase and connect an AI client to it — signing up, finding your data region, installing the Rulebase MCP server in Claude Code, Claude Desktop or Cursor, and creating an API key for the REST API. Trigger for "connect Claude to Rulebase", "install the Rulebase MCP", "set up the Rulebase connector", "create a Rulebase API key", "how do I sign up for Rulebase", "Rulebase returns 401", "no token provided", or when Rulebase tools are missing from a session.

Fast, accurate code search for AI agents using ~98% fewer tokens than grep+read. Indexes any local or remote repository in under a second (~250ms on CPU, no GPU or API key needed). Supports natural-language and symbol queries, semantic similar-code discovery, and MCP server integration for Claude Code, Codex, Cursor, and OpenCode. Python library available for programmatic use. Triggers on: semble, code search, semantic code search, semble search, token-efficient search, find code, code search mcp, agent code search, semble find-related, semble savings.

Routing guide for the built-in QwenWork Connector tools (mcp__qw-builtin__qw_query / mcp__qw-builtin__qw_action). Load ONLY right before calling them to view or manage QwenWork's OWN tasks/sessions or app configuration, or when a qw tool result explicitly asks. Before loading, always check whether another skill or tool can do the job — if so, use that instead. Unless the user explicitly asks, never use it to view skills, plugins, MCP servers, or third-party connectors. Never load in any non-essential scenario (content creation, PPT/docs, coding, research, web tasks), even when the topic is QwenWork itself. If in doubt, do not load.