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Searches the barnsworthburning.net website via the Model Context Protocol.
Explores Retrieval-Augmented Generation (RAG) and Multi-Cloud Processing (MCP) server integration using free and open-source models.
Enables interaction with the Louvre museum's digital collection via a Model Context Protocol (MCP) server.
Quickly sets up a Model Context Protocol (MCP) server with documentation tools and extensible architecture.
Integrates Stack Overflow into LLM-based coding workflows by providing real-time access to solutions and encouraging knowledge contribution.
Connects TronClass to Claude AI, enabling direct interaction through the Model Context Protocol (MCP).
Streams up-to-date package documentation to AI coding assistants.
Empower AI agents with comprehensive access to Ilograph documentation, validation tools, and diagram creation guidance.
Provides AI assistants with access to sacred scriptures from major world religions via a Model Context Protocol server.
Integrates WaniKani learning progress and data with AI assistants, enabling personalized study strategies and real-time updates through natural conversation.
Facilitates searching, organizing, and summarizing academic papers from arXiv.
Provides handy utilities for Advent of Code, such as fetching puzzle input, exposed via an MCP server.
Automate the organization of Obsidian notes using the Zettelkasten method, integrating with Gemini CLI to manage vault structure and inter-note linking.
Extract clean, readable content including markdown text, links, and metadata from any URL for integration with AI assistants.
Connects AI assistants to the Zread.ai documentation platform, enabling them to read GitHub repository documents, search code, and engage in conversations with repository-specific AI.
Scores, compares, and shares human-AI collaboration patterns using the 4D framework and a community knowledge base.
Automatically captures project state on every git commit, detects context drift, and delivers structured, token-budgeted briefings to AI agents without developer action.
Enable AI clients to directly create, navigate, and edit local XMind mind map files on disk.
Provides intelligent, persistent memory capabilities for AI coding agents across various development platforms.
Generates AI context files from codebase conventions, providing non-discoverable project knowledge to coding agents.
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