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Demonstrates implementation of an MCP client using SwiftUI and the Anthropic API.
Exports 1C:Enterprise platform context from help files into multiple formats for LLMs and offers an MCP server for AI assistant integration.
Provides comprehensive access to academic paper data, author information, and citation networks via the Semantic Scholar API.
Connects AI systems to Atlassian Confluence knowledge bases by providing tools for accessing and searching Confluence spaces, pages, and content.
Guides users to set up a basic Model Context Protocol (MCP) server in .NET.
Provides project code and learning notes for collaborative study of the MCP Minimalist Development course.
Indexes and performs semantic searches across files in local directories using vector embeddings.
Enables programmatic interaction with Anki flashcards, decks, and review processes.
Enables Large Language Model (LLM) clients to interact with any MediaWiki wiki.
Transforms unreadable documentation into an intelligent, searchable knowledge base.
Manages todo items within Large Language Models through a comprehensive API.
Enables AI-powered interactions with Apple Books data, providing summaries, organization, and recommendations.
Provides access to LeetCode problems, user data, and contest information via a GraphQL interface.
Generates static sites for comprehensive documentation, leveraging Markdown and simple Wiki-link notation for a streamlined developer experience.
Transforms feature ideas into production-ready code using a systematic Spec-Driven Development approach.
Enables natural language interaction with the arXiv API for retrieving and utilizing scholarly articles.
Enables interaction with the Semantic Scholar API to search for papers, retrieve paper and author details, and fetch citations and references.
Enhances AI capabilities with Zig-specific functionality including code optimization, compute unit estimation, code generation, and best practices recommendations.
Provides access to Jewish texts from Sefaria.org's library for Large Language Models via the Model Context Protocol.
Searches and retrieves Go package documentation from pkg.go.dev for use as an MCP server.
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