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    This MCP server enables intelligent API testing automation by combining RAG knowledge retrieval with tool execution capabilities. It allows QA engineers to perform natural language-driven API testing with contextual knowledge support.
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    Provides AI assistants with real-time access to 1000+ AI models including their latest pricing, context windows, capabilities, and specifications. Supports model search, comparison, recommendations, and live testing.
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    MIT
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    A fake web search server that generates LLM-powered search results and full articles based on a configurable background story for AI alignment testing. It enables users to simulate a controlled web environment where AI agents interact with fabricated content tailored to a specific narrative.
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    MIT
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    Enables interaction with Azure AI Foundry services through a unified interface for model exploration and deployment, knowledge indexing and search, AI evaluation, and fine-tuning operations. Supports both GitHub token-based model testing and full Azure deployment workflows.
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    MIT
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    Enables intelligent Kubernetes deployments, automated documentation testing, organizational pattern management, and shared prompt libraries. Provides AI-powered recommendations based on cluster capabilities and automates DevOps workflows through conversational interfaces.
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    MIT
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    Integrates the OpenViking context database with Cloudwise SA Workflow Skills to enable semantic search and access to product catalogs or solution templates. It supports hierarchical context loading for optimized token usage and includes a mock mode for testing without a live backend.
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    A Model Context Protocol server that provides tools for fetching xkcd comics and resources for dynamic data retrieval, WebSocket echo functionality, and static JSON data testing.
    5