Claude向けに構築された318個のMCPを発見。
Leverages AI to automatically generate Phaset manifest files by analyzing repository content.
Enables AI agents to execute TypeScript code with access to modular APIs defined in local skills directories.
Illustrates the practical implementation of OAuth and Dynamic Client Registration (DCR) for a Remote Model Context Protocol (MCP) server.
Provides a production-grade, self-hosted infrastructure platform with enterprise-level capabilities for scalable web applications.
Enables Claude to maintain persistent long-term memory across conversations.
Optimizes Claude Code's context window by intelligently managing Model Context Protocol (MCP) server tools, saving up to 90% of tokens.
Streamline AI integration in development workflows to reduce cognitive drift and enhance focus, ensuring accurate and secure coding practices.
Provides persistent memory and conversation continuity for Claude AI desktop and code environments.
Orchestrates complex workflows by integrating n8n with AI services, PostgreSQL, and Redis for robust automation and data management.
Manages MCP server environments, configurations, and local package installations.
Streamlines the management of AI tool configurations, including rules, commands, and MCP servers, for both global and project-specific environments.
Indexes local documents and runs Retrieval Augmented Generation (RAG) search to provide context for AI tools.
Facilitates seamless interaction with Claude Code models by routing requests and enabling customized AI development environments.
Provides a standardized template for building Model Context Protocol (MCP) servers with TypeScript/Node.js.
Parses over 36 document file formats, extracting text, metadata, and images with advanced chunking and token optimization for AI models like Claude.
Curates a collection of resources, guides, and tools for the Multi-Channel Platform (MCP) community.
Enables Retrieval Augmented Generation (RAG) systems by providing a Python server that leverages OpenAI's vector store capabilities using the Model Context Protocol (MCP).
Provides comprehensive resources, tools, and prompts for simulating and analyzing M/M/1 queuing systems, enabling large language models to assist with complex operations research tasks.
Automatically manages development and testing environments by monitoring coding tasks and switching containerized setups to match.
Augments Claude with Python code execution, shell command capabilities, and file manipulation.
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