What problem does it solve?
Implement robust MCP servers and clients that connect AI systems to external tools, resources, and prompts while enforcing protocol compliance, validation, and secure transports to avoid fragile or insecure integrations.
Core Features & Use Cases
- Protocol Compliance: JSON-RPC 2.0 message formatting, initialize/handshake lifecycle, and defined core methods for tools, resources, and prompts.
- SDK Guidance & Transports: Implementation patterns and examples for TypeScript (Zod) and Python (Pydantic) using stdio, HTTP, and SSE transports.
- Security & Reliability: Input validation, structured error handling, authentication, rate limiting, logging, and resource URI templates for safe resource access.
- Use Case: Build a production MCP server that exposes tool execution, dynamic resource providers, and prompt templates to Claude Desktop or remote LLM clients with observability and rate controls.
Quick Start
Start by implementing an initialize handler that advertises capabilities, lists tools/resources/prompts, and validates inputs using Zod or Pydantic before executing any tool.