A Model Context Protocol server that enables AI assistants to interact with Jenkins CI/CD servers, providing tools to check build statuses, trigger builds, and retrieve build logs.
Implements the Model Context Protocol (MCP) to provide AI models with a standardized interface for connecting to external data sources and tools like file systems, databases, or APIs.
A secure, container-based implementation of the Model Context Protocol (MCP) that provides sandboxed environments for AI systems to safely execute code, run commands, access files, and perform web operations.
A streamlined foundation for building Model Context Protocol servers in Python, designed to make AI-assisted development of MCP tools easier and more efficient.
A foundation for building custom local Model Context Protocol (MCP) servers that provide tools accessible to AI assistants like Cursor or Claude Desktop.