What problem does it solve?
Inconsistent and undocumented approaches to building Model Context Protocol (MCP) servers and clients cause integration friction, security gaps, and duplicated effort across AI‑augmented tools.
Core Features & Use Cases
- Tool Schema Patterns: Standardized JSON Schema definitions with annotations such as
readOnlyHint, idempotentHint, and openWorldHint.
- Transport Implementations: Ready‑to‑use examples for stdio, HTTP with Server‑Sent Events, and streamable HTTP endpoints.
- JSON‑RPC 2.0 Handling: Complete request, response, and error formats with batch support.
- Security & Best Practices: Input validation, origin checks, rate limiting, structured logging, and session management.
Use Case: A developer building an AI‑driven search service can adopt these patterns to expose a
search_kb tool over HTTP/SSE with proper validation, batching, and security safeguards.
Quick Start
Ask the assistant to generate an MCP server that exposes a search_kb tool using the shown TypeScript pattern.