A basic starter project for building Model Context Protocol (MCP) servers that enables standardized interactions between AI systems and various data sources through secure, controlled tool implementations.
A bare-bones FastMCP server template designed to serve as a starting point for building custom Model Context Protocol servers. It provides a foundational structure for implementing tools over HTTP and includes a built-in health check utility.
MCP server scaffold that exposes stubbed tools for listing, searching, and summarizing sources, with built-in OAuth 2.1 authorization flow for Claude integration.
A corporate MCP server template in Python, built with FastMCP for stateless, scalable deployment behind a load balancer with health/readiness endpoints and JSON structured logging.