developer tools向けの厳選されたMCPサーバーコレクションをご覧ください。20521個のサーバーを閲覧し、ニーズに最適なMCPを見つけましょう。
Performs mathematical calculations using natural language processing and OpenAI's GPT model.
Rolls dice using a server implementation.
Provides a search functionality for blog posts and generates content summaries in the style of Cybozu Frontend Weekly.
Provides local and remote servers to execute FlowMCP schemas for AI–API integration.
Manages Internet Information Services (IIS) web servers using the Model Context Protocol.
Enables natural language interaction with banking microservices using Spring AI and Model Context Protocol.
Accelerates the development of Model Context Protocol (MCP) servers with a production-ready Python template.
Fetches upcoming events directly from Google Calendar using its API.
Installs the HAPI CLI with a single command to swiftly integrate and test APIs.
Automatically introspects any GraphQL API to discover schemas and generate intelligent, production-ready GraphQL queries.
Integrates Z.AI's GLM-4.6 models with Claude Code, facilitating advanced code generation, deep analysis, and general AI queries.
Bridges the authentication gap for secure Model Context Protocol servers using Microsoft Entra ID with .NET.
Coordinates specialized agents to plan, build, test, and deploy applications with self-healing, authentication, and analytics, enabling autonomous software engineering workflows.
Connects local AI tools with the Workoflow orchestration platform, enabling AI assistants to discover and execute Workoflow tools.
Connect AI assistants to Tidio live chat for instant customer support with automated setup.
Empowers AI assistants with comprehensive access to the Databricks platform via the Model Context Protocol (MCP).
Leverage AI to generate complete frontend applications, UI components, interactive prototypes, and design mockups from natural language prompts.
Empowers AI models like Claude to execute Solana token trades, launches, and fee management through natural language commands.
Exposes Microsoft PyRIT's AI red-teaming capabilities as structured tools for real-time, LLM-orchestrated adversarial testing.
Detects visual layout bugs using deterministic DOM analysis, identifying issues like overflow, spacing, typography, and responsive regressions.
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