'mcp-server' 검색 결과

Guide for creating new MCP server integrations

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Manage OpenViking collections (OV libraries) from the command line with `ov-cp` — list / create / get / update / usage / get the data-plane API key / delete, plus managing the users and account data spaces of an enterprise-tier library (list / create / register / update / delete), account-scoped users / API keys / usage, and configuring how a library is billed (AgentPlan AFP deduction vs Volcano pay-as-you-go, `--pay-type` / `--seat-id`). Use when the user wants to provision or inspect an OpenViking library, fetch a library's data-plane API key, do the create→get-key cold-start, manage a library's users or accounts / 数据空间, set or switch a library's billing, or otherwise drive the OpenViking control plane (topapi). Authenticates with an Ark AgentPlan ApiKey.

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Use when exposing Spring Boot 4 application capabilities through Model Context Protocol tools, resources, or prompts. Covers Spring AI 2.0 MCP annotations, transport selection, schemas, errors, security, and the standalone MCP Java SDK 2.x.

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Use when exposing Spring Boot 3 application capabilities through Model Context Protocol tools, resources, or prompts. Covers Spring AI 1.x tool callback registration, transports, schemas, errors, security, and standalone MCP Java SDK compatibility.

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Build MCP (Model Context Protocol) servers on Cloudflare Workers with tools, resources, and prompts.

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Design, implement, harden, and verify Model Context Protocol (MCP) servers with precise tool contracts, least-privilege authorization, safe transports, structured errors, and interoperability tests. Use when creating a new MCP server, exposing an API or data source through MCP, reviewing an MCP server design, adding or revising MCP tools, or preparing an MCP server for production.

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Building production-ready Model Context Protocol servers that expose tools, resources, and prompts to AI assistantsUse when "mcp server, model context protocol, mcp tool, mcp resource, claude integration, ai tool integration, mcp, model-context-protocol, anthropic, claude, ai-integration, tools, resources, prompts" mentioned.

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Creates production-ready MCP servers using FastMCP v2. Use when building MCP servers, optimizing tool descriptions for context efficiency, implementing progressive disclosure for multiple capabilities, or packaging servers for distribution.

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Sub-skill de agent-ready-cloudflare: Implement MCP Server Card

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Ultimate guide for designing, building, and security-hardening modern AI Tools/Bots via Model Context Protocol (MCP v1.x) in TypeScript and Python / Panduan utama merancang, membangun, dan mengamankan AI Tools/Bots modern melalui Model Context Protocol (MCP) dalam TypeScript dan Python.

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Expert guide for DOKU Model Context Protocol (MCP) Server integration. Enables AI Agentic Commerce with tools for DOKU Checkout, payment links, Virtual Accounts, QRIS, and order status checks / Panduan ahli DOKU MCP Server untuk AI Agentic Commerce.

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Copilot Studio から利用する自前 MCP Server を Azure Functions 上に構築する。JSON-RPC 2.0 の最小実装、受信 Entra ID JWT 検証 / 送信 Managed Identity のキーレス認証、Private Endpoint 下でのデータ投入、Entra アプリ登録のスコープ公開と事前承認、デプロイの実測検証までを非対話スクリプトで完結させる。

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使用Node/TypeScript SDK构建MCP服务器——工具、资源、提示、Zod验证、stdio与可流式HTTP对比。使用Context7或官方MCP文档获取最新API信息。

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Use whenever the user wants to find, rank, or shortlist directories and listing sites where they can submit an AI product — an AI tool, AI app, AI agent, or agent skill / plugin — to get backlinks, referral traffic, and discovery. Triggers on "where can I list my AI tool", "directories to submit my AI agent", "agent-skills directories", "best AI tool directories for backlinks", "where do I get my GPT/Claude app discovered", or "pull submission details for these AI-directory domains", even when described indirectly (we built an AI agent, where do we get it in front of people). Drives the ServiceGraph API (api.servicegraph.co) — a catalog of 1,000+ product directories enriched with Domain Rating, backlinks, and organic traffic. Defer to find-mcp-directories for MCP-server listings specifically, and to find-product-directories for general SaaS/software/app launches with no AI angle. Skip finding an AI consultancy/agency to hire (use find-ai-consultancy), comparing AI products ("ChatGPT vs Claude"), building an AI tool (do-the-work), and AI link-building *services*.

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Use whenever the user wants to find, rank, or shortlist directories, listing sites, or launch platforms where they can submit a software product, SaaS, app, tool, or startup — to get backlinks, referral traffic, and launch-day reach. Triggers on "where can I submit my SaaS for launch", "list of Product Hunt alternatives", "directories to get backlinks for our app", "high-authority software listing sites", "where should I list my startup", or "pull submission details for these 8 directory domains", even when described indirectly (we're launching next week, where do we post; how do we get backlinks by listing in directories). Drives the ServiceGraph API (api.servicegraph.co) — a catalog of 1,000+ product directories enriched with Domain Rating, backlinks, and organic traffic. Defer to find-mcp-directories for MCP-server listings and find-ai-directories for AI-tool / AI-agent / agent-skill listings. Skip finding a firm/agency to hire (use the find-* agency skills), finding products *inside* a directory ("recommend the best CRM"), building a directory site (do-the-work), local/business directories for brick-and-mortar listings, and link-building *services*.

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Configure MCP (Model Context Protocol) servers for Claude Code and Claude Desktop. Covers mcptools setup, Hugging Face integration, WSL path handling, and multi-client configuration. Use when setting up Claude Code to connect to R via mcptools, configuring Claude Desktop with MCP servers, adding Hugging Face or other remote MCP servers, or troubleshooting MCP connectivity between clients and servers.

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Containerize an R-based MCP (Model Context Protocol) server using Docker. Covers mcptools integration, port exposure, stdio vs HTTP transport, and connecting Claude Code to the containerized server. Use when deploying an R MCP server without requiring a local R installation, creating a reproducible MCP server environment, running MCP servers alongside other containerized services, or distributing an MCP server to other developers.

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Analyze an arbitrary codebase to identify functions, APIs, and data sources suitable for exposure as MCP tools, producing a tool specification document. Use when planning an MCP server for an existing project, auditing a codebase before wrapping it as an AI-accessible tool surface, comparing what a codebase can do versus what is already exposed via MCP, or generating a tool spec to hand off to scaffold-mcp-server.

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Build a custom MCP (Model Context Protocol) server that exposes domain-specific tools to AI assistants. Covers server implementation in Node.js or R, tool definitions, the resources and prompts primitives, transport configuration, and testing with Claude Code. Use when you need to expose custom functionality beyond what mcptools provides, when building specialized domain-specific AI integrations, or when wrapping existing APIs or services as MCP tools.

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Search academic papers, build literature reviews, and synthesize research findings — combines Exa search (publication category, domain and date filters) with arxiv-mcp-server for paper discovery, download, and deep analysis. Triggers on academic paper, literature review, research synthesis, arxiv, find papers, scholarly search.

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Configure and manage MCP (Model Context Protocol) servers in Claude Code CLI. Use this skill when adding, removing, listing, or troubleshooting MCP servers, or when questions arise about MCP configuration, transport types, scopes, or authentication. Essential for connecting Claude Code to external tools, databases, and APIs.

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Write effective MCP server instructions for tool compaction support. Use when creating or updating the `instructions` parameter in MaaSProtectedFastMCP server initialization. Helps LLMs understand when to search for tools, workflow patterns, and cross-feature relationships.

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Comprehensive MCP server development guide covering FastMCP 2.14.3 features, Anthropic standards, ecosystem integration, and production deployment across all agentic IDEs

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Design, audit, harden, review, or upgrade MCP servers and MCP Apps with revision-aware protocol profiles, explicit HTTP/deployment boundaries, capability-centered validation, bilingual reporting, and reproducible evidence. Use for MCP server architecture, JSON-RPC or Streamable HTTP bugs, security hardening, protocol-version migration, MCP Apps widget boundaries, review reconciliation, test planning, and public engineering evidence.

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