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Provides a Model Context Protocol (MCP) server example that generates random US state and signature soup combinations.
Dynamically imports API specifications (OpenAPI, GraphQL, AsyncAPI), exposes them as tools for agents, and enhances functionality through self-learning and autonomous documentation.
Provides a Next.js project bootstrapped with create-next-app to assist in learning AI concepts.
Provides handy utilities for Advent of Code, such as fetching puzzle input, exposed via an MCP server.
Answers questions about the Peacock VS Code extension by fetching and querying its official documentation.
Demonstrates remote Model Context Protocol (MCP) calls using a Ping-Pong server implemented with FastAPI.
Provides documentation for the MIT decentralized AI, MCP hackathon.
Equips AI assistants with comprehensive resources for Vega-Lite and Deneb, including documentation, visualization examples, and specification validation.
Automatically generates visual architectural diagrams, including dependency graphs, class diagrams, and data flow diagrams, from codebase analysis.
Provides a customizable, secure AI assistant leveraging local LLMs for departments to manage data, automate workflows, and gain document-based insights.
Retrieves and cleans official documentation content for popular AI and Python ecosystem libraries, preparing it for LLM consumption.
Provides context-aware keyboard shortcuts for various operating systems, desktop environments, and applications through intelligent natural language queries.
Extracts clean markdown content from web pages using Playwright, intelligently filtering out non-content elements.
Automates the setup and management of a personal home lab environment using modern infrastructure tools.
Provides AI assistants with access to OOREP (Open Online Repertory), a comprehensive homeopathic repertory and materia medica database, via the Model Context Protocol.
Calculates comprehensive Jewish prayer and astronomical times (zmanim) for any global location with support for multiple halachic opinions.
Provides secure access to Kali Linux web penetration testing tools for AI assistants in a controlled Docker environment.
Integrates Kali Linux security tools with AI assistants for ethical penetration testing in a controlled Docker environment.
Implements a production-ready Model Context Protocol (MCP) server demonstrating the complete MCP specification including OAuth 2.1, sampling, elicitation, structured data validation, and real-time notifications.
Provides AI assistants with structured access to the CityJSON specification, allowing them to fetch specific chapters on demand.
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