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MCP 工具与服务目录

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87,637
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36,826
最近生成
2026-05-22

An MCP server that provides standardized tools for AI agents to interact with the Test MCP Feb4 API. It enables LLMs to access API endpoints through asynchronous operations and standardized Model Context Protocol tools.

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A simple learning-focused MCP server that demonstrates basic functionality with tools for mathematical operations, system information, and email validation, plus sample file resources. Perfect for understanding MCP protocol basics and testing integrations.

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A sample MCP server that fetches random inspirational quotes, programming jokes, and advice from public APIs. Provides three simple tools for testing and demonstration purposes.

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A dual-transport MCP server that exposes your API as tools to LLM clients, supporting both stdio transport for local clients like Claude Desktop and HTTP/SSE transport for remote clients like OpenAI's Responses API.

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An MCP server that enables AI agents and LLMs to interact with the Test MCP Server Feb6 USDT API through standardized tools. It provides features such as Docker support and async operations for efficient integration.

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Enables AI agents and LLMs to interact with the TEST MCP USDT API through standardized tools using the Model Context Protocol. It provides a containerized environment for executing USDT-related API operations and asynchronous tool handling.

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Connect Claude, Cursor, and other AI assistants to your Testmo test management instance to manage test cases, folders, runs, milestones, and CI/CD automation.

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MCP server for TestNeo quality workflows, enabling test generation, execution, and analysis through MCP-compatible IDE clients.

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Provides AI agents access to news aggregation from 80,000+ sources via the NewsAPI. Supports both authenticated access with API keys and pay-per-use via HTTP 402 protocol with blockchain payment verification.

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AI-native Model Context Protocol (MCP) server for TestRail. Lets Claude, Cursor, Windsurf, and other AI assistants browse projects, create and update test cases, kick off test runs, and record results through natural-language conversation — with strongly-typed tool schemas and per-project custom field validation that helps LLMs generate valid TestRail requests on the first try.

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Provides AI agents and LLMs access to the Tesy 56 API through standardized MCP tools for seamless integration and interaction with Tesy 56 endpoints.

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