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Enables AI assistants to interact directly with the microCMS content management system.
Connect Claude to your Substack and Medium writings for context-aware assistance.
Enables AI clients to interact with scientific protocols and methods on protocols.io.
Integrate GitBook's API with AI assistants and LLM applications via a Model Context Protocol server.
Enables AI assistants to manage Confluence spaces, pages, and content through a standardized interface.
Integrates a comprehensive Model Context Protocol (MCP) server with LightRAG API, offering 22 tools for document management, querying, knowledge graph operations, and system management.
Extracts subtitles, danmaku, and comments from Bilibili videos.
Integrates Day One Journal with Claude Desktop, enabling natural language control over journaling.
Enables Claude AI to download and parse Substack posts directly within conversations.
Manages org-mode and org-roam knowledge bases by providing search, content access, and note linking capabilities via the Model Context Protocol.
Serves as the official MCP server for NewsNow, providing access to over 40 news sources.
Exposes Discourse forum capabilities as callable tools for AI agents via a Model Context Protocol (MCP) stdio server.
Integrates Foundry VTT data with Claude Desktop, enabling AI-powered natural language interaction with game world information for enhanced campaign management.
Integrates Atlassian Cloud products like Confluence and Jira into the Model Context Protocol ecosystem, enabling AI models to access and interact with project and documentation data.
Enables interaction with Confluence through CQL queries and content retrieval.
Transforms any topic into an explainer video with AI narration and 3Blue1Brown-style animations.
Manages AI prompts by fetching them from GitHub, enabling intelligent discovery, composition, and real-time synchronization.
Facilitates AI interaction with WordPress forms, entries, and submissions through a Model Context Protocol server.
Provides intelligent question answering and analysis capabilities for multi-document PPT files powered by a Retrieval-Augmented Generation (RAG) engine.
Transforms static ZIM archives into dynamic knowledge engines for large language models, enabling offline access and search of ZIM format knowledge bases.
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