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Automates interaction with Cisco Modeling Labs (CML) for network simulation and learning.
Provides access to simplified `tldr` command-line documentation as an MCP server.
Demonstrates the Model Context Protocol's deprecated HTTP + Server-Sent Events (SSE) transport for educational purposes.
Integrates AI assistants like Claude and Cursor with SiYuan Note, enabling seamless interaction and management of personal knowledge bases.
Automates the generation of OpenAPI 3.0 API documentation by analyzing Django REST Framework ViewSets.
Provides readme and code samples for the Azure Java SDK to AI assistants via the Model Context Protocol.
Integrates WaniKani learning progress and data with AI assistants, enabling personalized study strategies and real-time updates through natural conversation.
Enables AI assistants to interact with the Canvas LMS platform.
Manage, organize, and search personal or professional notes in Markdown format through a Model Context Protocol (MCP) server.
Provides comprehensive OpenAPI specification linting and documentation rendering capabilities.
Generates detailed development plans, project roadmaps, and task breakdowns for Claude Code, transforming project ideas into actionable implementation steps.
Connects AI assistants to arXiv, enabling search, analysis, and download of research papers within AI workflows.
Provides centralized knowledge management for projects, enabling storage, search, and maintenance of project-specific information that persists across sessions.
Automate saving AI-generated content from Claude Code directly to Obsidian with customized formatting and project organization.
Provides comprehensive access to Kali Linux tool documentation directly within Claude Desktop.
Retrieves and cleans official documentation content for popular AI and Python ecosystem libraries, preparing it for LLM consumption.
Enables LLMs to automatically analyze project structures and generate comprehensive, well-formatted README files.
Answers questions about the Peacock VS Code extension by fetching and querying its official documentation.
Orchestrates comprehensive travel planning by leveraging an agentic workflow, integrating multi-LLM support and essential travel tools through the Model Context Protocol.
Demonstrates remote Model Context Protocol (MCP) calls using a Ping-Pong server implemented with FastAPI.
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