Skill UI

This guide details the process of building Model Context Protocol (MCP) servers. These servers are crucial for enabling Large Language Models (LLMs) to interact with external APIs and services, facilitating complex, real-world task completion. It provides comprehensive coverage on architectural planning, choosing appropriate languages (Python, TypeScript, C#), and selecting transport mechanisms (HTTP, stdio) for robust integration within enterprise ecosystems like Azure and Foundry.

Used for building, debugging, and extending MCP servers and clients. This skill implements robust connections between AI systems and external tools/data sources using structured protocols like JSON-RPC 2.0. Expertise includes defining tool schemas (Zod/Pydantic), configuring transport layers (HTTP/SSE/stdio), and scaffolding full-stack projects in TypeScript or Python.

Defines MCP server tooling with file search, query execution, resource endpoints, prompt templates, and transport configurations alongside a client setup example for streamlined project automation.

Codified best practices for senior transportation managers to negotiate freight components, keep scorecards, steward carrier portfolios, and balance cost, service, and compliance when running RFPs and managing mixed contract/spot freight programs.

Comprehensive Python toolkit for building, analyzing, and visualizing complex networks; supports algorithms, I/O, generation, and community detection across social, biological, transportation, and citation data.

A comprehensive technical reference for implementing advanced Lightning Network channel factories. It covers complex topics such as multi-party channels, Layer 2 scaling on Bitcoin, and advanced protocols including Decker-Wattenhofer invalidation trees, MuSig2 key aggregation, and encrypted Noise NK transport. Essential for developers building highly scalable and secure Bitcoin infrastructure.

A comprehensive skill set for senior transportation managers overseeing a large, multi-modal carrier portfolio. It covers the full lifecycle of carrier engagement, including sourcing, compliance checks (FMCSA SAFER), executing complex RFPs, negotiating granular rate components (linehaul, FSC, accessorials), and establishing performance scorecards. Use this skill to optimize logistics costs, mitigate supply chain risks, and ensure consistent service quality across varied freight types.

A comprehensive guide to implementing and validating Transport Layer Security (TLS) 1.3. This skill covers configuring modern cipher suites, key exchange groups, and enforcing perfect forward secrecy (PFS). Use this when deploying secure communication protocols, hardening network services, meeting compliance standards, or performing deep security assessments on web servers and applications.

Provides a comprehensive guide to auditing the security posture of the etcd cluster, the critical key-value store backing Kubernetes. This assessment covers encryption at rest for secrets, TLS transport security, access control policies, secure backup procedures, and network isolation best practices. Essential for hardening control planes and ensuring regulatory compliance.

This tool scaffolds a complete, production-ready Model Context Protocol (MCP) server project written in Rust. It utilizes the official `rmcp` SDK to ensure full compatibility. The generated structure includes modules for handling logic, defining tools, managing prompts, and providing resources. Users can configure different transports (stdio, SSE, HTTP) and immediately run the server for integration testing or production use.

This comprehensive guide details how to construct a complete, robust Model Context Protocol (MCP) server using TypeScript and the specialized v2 SDK. It covers all aspects of Node.js project setup, selecting appropriate transport layers (HTTP or stdio), implementing complex, schema-validated tools, and integrating resources, resulting in a highly type-safe AI backend service.

This skill guides the creation of production-grade Model Context Protocol (MCP) servers and basic clients using C# and the .NET framework. It ensures adherence to the stable 2.x specification, addressing common pitfalls like stateful/stateless HTTP defaults, handling deprecations (roots, sampling), and utilizing appropriate transports (STDIO, Streamable HTTP). Essential for developers integrating structured AI APIs into enterprise applications.