Discover 141 MCPs built for Anthropic.
Facilitates interactive command-line chat with AI models, supporting document retrieval and extensible tool integrations.
Transforms Claude Code into a Rails-native development partner, simplifying efficient Ruby on Rails development.
Automates posting tweets to X (Twitter) using data sourced from a Google Sheet.
Serves as a demonstration MCP server built with Go.
Integrates AI tools and models through a server adhering to the Model Context Protocol (MCP).
Provides example code and learning materials for exploring the Model Context Protocol (MCP).
Provides a curated collection of Jupyter Notebooks, notes, and resources for learning and implementing the Model Customization Protocol (MCP) and Generative AI concepts.
Generates project specifications and files using an AI model.
Orchestrates AI models like Claude, Auggie, Codex, and Gemini to enhance collaboration, context retrieval, and code analysis for various tasks.
Orchestrates multiple specialized agents to draft articles and conduct web research using a custom communication protocol and an MCP-inspired architecture.
Facilitates the creation of Model Context Protocol (MCP) servers and clients using Python.
Intelligently compresses code to optimize LLM context windows, enhancing AI coding assistant capabilities.
Profile and optimize AI coding assistant sessions by tracking real-time token usage, analyzing MCP efficiency, and identifying cost-saving opportunities.
Automates diverse personal and professional tasks through an AI assistant interface, integrating specialized servers for a wide range of functionalities.
Automates the analysis of legal documents using Azure Blob Storage for content management and the Anthropic Claude API for AI-powered insights.
Offers a comprehensive collection of Jupyter notebooks guiding users through building rich-context AI applications with Anthropic models.
Establishes a robust security layer for AI agents and Claude Code, implementing input validation, output filtering, and policy enforcement.
Orchestrates specialized AI teammates (PM, Architect, Developer, QA, Security) through shared task lists, inter-agent messaging, and persistent learning for autonomous software development.
Equips autonomous AI agents with a metacognitive oversight layer, preventing reasoning lock-in and improving alignment.
Simplifies data analysis for everyone, offering AI-driven tools and simple commands for efficient insights into critical internet data.
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