# Data Protocol

This project implements a server based on the Model Context Protocol (MCP) standard to connect the ZenML platform with AI applications. It provides access to core ZenML functions through a standardized protocol, including querying information about users, pipelines, run records, etc., and supports triggering new pipeline runs.

Model Context Protocol (MCP) is an open - source protocol that provides a series of reference implementations and community - developed servers for providing large language models (LLMs) with secure and controlled access to tools and data sources. The project includes various functional servers, such as file system operations, Git integration, database access, etc., and supports rapid development of new services through TypeScript and Python SDKs.

Strapi MCP is an MCP server designed for Strapi CMS, providing the ability to access content types and entries through the Model Context Protocol, and supporting operations such as content management, media uploads, and relationship connections.

The Trino MCP Server is a protocol server that provides structured access to the Trino distributed SQL query engine for AI models, supporting multiple transmission methods and API integration.

This project compiles a list of popular Model Context Protocol (MCP) servers based on Smithery.ai usage data. MCP is an open-source standard developed by Anthropic for establishing secure two-way connections between data sources and AI tools.