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Enables AI assistants to interact with and manage n8n workflows through natural language.
Enables Large Language Models (LLMs) to interact with external tools through the Model Context Protocol (MCP).
Provides a powerful, self-hostable AI Agent platform for maximum privacy and flexibility, acting as a complete drop-in replacement for OpenAI's Responses APIs with advanced agentic capabilities on consumer-grade hardware.
Install other MCP servers via Claude by specifying their npm or PyPi package names or local paths.
Provides a modular and extensible Python framework for building and managing Auto-GPT agents.
Enables interaction with iOS simulators for tasks like UI inspection, UI interaction, and screenshot capture.
Offers a comprehensive production toolkit for large language models, providing observability, prompt management, and evaluation capabilities to enhance LLM development.
Enables coding agents to communicate and coordinate asynchronously, providing a mail-like system with identities, inboxes, and shared context.
Provides a command-line interface for interacting with Model Context Protocol (MCP) servers using stdio and HTTP transport.
Enables creating, editing, and manipulating PowerPoint presentations through the Model Context Protocol.
Orchestrates components within a lightweight, high-performance rule engine framework for Go applications.
Provides a user interface for Nx and Lerna monorepos, enhancing developer workflow and AI integration within code editors.
Scans Model Context Protocol (MCP) servers for common security vulnerabilities like prompt injections and tool poisoning.
Enables AI assistants to interact with the Godot game engine by launching the editor, running projects, and capturing debug output.
Connects Language Servers to Model Context Protocol (MCP) clients, providing advanced code analysis and manipulation capabilities to LLMs.
Empowers AI coding tools to generate robust, performant, and modern PostgreSQL code by providing deep, versioned expertise.
Automates AI-powered workflows directly within your codebase.
Simplifies the development, running, evaluation, and orchestration of LLM-based agents using YAML and a CLI.
Enables AI assistants to access and search official Microsoft documentation in real-time.
Provides a secure sandbox environment to test payloads against detection mechanisms before deployment.
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