"Wikimedia Foundation" matching MCP servers:

A foundation for building interactive applications using the Model Context Protocol that integrates AI capabilities with Magic UI components.

MCP server that inspects older repos, identifies stale guidance, and installs a managed foundation for better Copilot work including instructions, objectives, specialist agents, and insights.

A basic TypeScript implementation of the Model Context Protocol (MCP) server designed as a starting point for MCP development. Provides a minimal foundation for building custom MCP servers with stdio configuration for local integration with VS Code and GitHub Copilot.

A foundation for creating custom Model Context Protocol servers that can integrate with AI systems, providing a simple BMI calculator tool as an example implementation.

An MCP server that enables automated dataset creation and custom object detection model training through natural language interactions. It integrates foundation models like GroundedSAM for auto-labeling and supports training specialized YOLOv8 models using local or Unsplash images.

An LLM-native decision tracking system that captures unexpected engineering outcomes as 'pressure events' to build a persistent learning foundation. It enables AI assistants to manage cases, log surprises, and promote recurring insights into global or project-specific knowledge bases.

Enables agents to inspect repositories, manage Golden Packs, plan golden flows, and run asynchronous validation tasks over MCP, providing a deterministic foundation for project-specific workflows.

Enables Claude to delegate tasks to IBM watsonx.ai foundation models (Granite, Llama, Mistral) for text generation, chat, embeddings, and document analysis. Supports two-agent architectures where Claude can leverage IBM's enterprise AI capabilities for specialized workloads.

A Model Context Protocol server implementation built with FastAPI that enables AI agent interactions. Provides a structured foundation for building AI-powered applications with proper data validation and modern Python tooling.

A Python starter template for building MCP servers with client connection management and Jupyter notebook integration. Provides a structured foundation for adding custom tools, prompts, and workflows to create AI-powered applications.

MCP server for the FLOX trading framework. About 30 tools to run backtests, scaffold strategies, validate for lookahead bias, compute indicators, place orders, and query PnL from Claude/Cursor.