A production-ready foundation for building secure, observable MCP servers with built-in authentication, rate limiting, and reference tools like database-query and semantic-search.
A production-ready, security-first starting point for building Model Context Protocol servers, enforcing safe defaults like dry-run and tenant isolation.
An enterprise MCP server scaffold that provides secure, governed access to internal tools through RBAC, audit logging, rate limiting, and prompt-injection boundaries, with a FastAPI control plane and OpenTelemetry observability.
A production-grade MCP server designed for multi-tenant, authenticated, and observable AI agent systems, enabling secure tool execution across heterogeneous data sources.
A production-grade, extensible Python template for building Model Context Protocol servers with support for Streamable HTTP and stdio transports. It provides a structured framework for implementing tools, resources, and prompts with built-in authentication, observability, and background task management.
Enables building agent-ready APIs that expose tools as both HTTP and MCP endpoints from a single server definition, with automatic OpenAPI, discovery docs, and interactive API reference.