LLM Mart Basic

Apply MCAF non-functional-requirements guidance to capture or refine explicit quality attributes such as accessibility, reliability, scalability, maintainability, performance, and compliance. Use when a feature or architecture change needs explicit quality attributes and trade-of

Apply MCAF source-control guidance for repository structure, branch naming, merge strategy, commit hygiene, and secrets-in-git discipline. Use when bootstrapping a repo, tightening PR flow, or documenting branch and release policy.

Apply MCAF UI/UX guidance for design systems, accessibility, front-end technology selection, and design-to-development collaboration. Use when bootstrapping a UI project, choosing front-end stack, or tightening design and accessibility practices.

Build or consume Model Context Protocol (MCP) servers and clients in .NET using the official MCP C# SDK, including stdio, Streamable HTTP, tools, prompts, resources, and capability negotiation.

Use Metalint in .NET repositories that ship Node-based frontend assets and want one CLI entrypoint over several underlying linters. Use when a repo wants to orchestrate ESLint, Stylelint, HTMLHint, and related frontend checks from a single checked-in `.metalint/` configuration.

Use the open-source free `Meziantou.Analyzer` package for design, usage, security, performance, and style rules in .NET. Use when a repo wants broader analyzer coverage with a single NuGet package.

Build .NET AI agents and multi-agent workflows with Microsoft Agent Framework using the right agent type, threads, tools, workflows, hosting protocols, and enterprise guardrails.

Use the Microsoft.Extensions stack correctly across Generic Host, dependency injection, configuration, logging, options, HttpClientFactory, and other shared infrastructure patterns.

Build provider-agnostic .NET AI integrations with `Microsoft.Extensions.AI`, `IChatClient`, embeddings, middleware, structured output, vector search, and evaluation.

Design and implement Minimal APIs in ASP.NET Core using handler-first endpoints, route groups, filters, and lightweight composition suited to modern .NET services.

Work on C# and .NET-adjacent mixed-reality solutions around HoloLens, MRTK, OpenXR, Azure services, and integration boundaries where .NET participates in the stack.

Use ML.NET to train, evaluate, or integrate machine-learning models into .NET applications with realistic data preparation, inference, and deployment expectations.

Write modern, version-aware C# for .NET repositories. Use when choosing language features across C# versions, especially C# 13 and C# 14, while staying compatible with the repo's target framework and `LangVersion`.

Write, run, or repair .NET tests that use MSTest. Use when a repo uses `MSTest.Sdk`, `MSTest`, `[TestClass]`, `[TestMethod]`, `DataRow`, or Microsoft.Testing.Platform-based MSTest execution.

Implement the Model-View-ViewModel pattern in .NET applications with proper separation of concerns, data binding, commands, and testable ViewModels using MVVM Toolkit.

Use the open-source free `NetArchTest.Rules` library for architecture rules in .NET unit tests. Use when a repo wants lightweight, fluent architecture assertions for namespaces, dependencies, or layering.

Write, run, or repair .NET tests that use NUnit. Use when a repo uses `NUnit`, `[Test]`, `[TestCase]`, `[TestFixture]`, or NUnit3TestAdapter for VSTest or Microsoft.Testing.Platform execution.

Build or review distributed .NET applications with Orleans grains, silos, persistence, streaming, reminders, placement, transactions, serialization, event sourcing, testing, and cloud-native hosting.

Use the free official .NET diagnostics CLI tools for profiling and runtime investigation in .NET repositories. Use when a repo needs CPU tracing, live counters, GC and allocation investigation, exception or contention tracing, heap snapshots, or startup diagnostics without GUI-on

Create or reorganize .NET solutions with clean project boundaries, repeatable SDK settings, and a maintainable baseline for libraries, apps, tests, CI, and local development.

Fourteen posts of being wrong in production, compressed to checkboxes

Healthy nodes, a quiet network, 300 restarts in three days, and a latency budget measured in milliseconds

Discovery worked. Ping worked. Every TCP connection timed out, and later the tunnel only worked when someone had a terminal open.

Every VM came back. The cluster did not. Declarative systems converge on config, and the datapath isn't config.

A surprising share of AI-in-the-terminal failures aren't the AI. They're zsh, and a version of bash from 2006.

A Claude Code plugin turns standalone project configuration into a namespaced, installable extension that teams and communities can update as one unit.

None of the safety came from the model. It came from six boring habits.

Skills package instructions and references. Subagents run work in a separate context and return results. They solve different problems and can be composed deliberately.

Six hours in, one step left, everything green, and the incident that didn't happen

CLAUDE.md carries persistent project context. Skills load reusable procedures when relevant. Separating stable facts from task-specific workflows keeps both easier to maintain.

Twenty minutes recovering secrets that never existed, and the one sentence from a human that ended it

An API request routing a model's tool call through an approval gate to a remote MCP server

31 config keys, two audits, and why the first one was wrong in both directions

The official MCP Registry stores standardized server metadata rather than package code. Publishers verify a namespace, describe installation or remote access, and submit immutable versions.

Everyone looks at the Dockerfile. The file that actually leaked the key was the project file.

Remote MCP authorization uses established OAuth standards, but secure integration still requires issuer validation, least-privilege scopes, protected token handling, and server-side enforcement.

"Copy it over and switch the reference" is two steps, and the outage lives in the one nobody checks

stdio fits local processes and prototypes. Streamable HTTP fits hosted services and shared integrations. The right choice follows where the capability runs and who must reach it.

The most important rule wasn't about what I could change. It was about what I was allowed to display.

Tools perform operations, resources expose readable context, and prompts provide reusable templates. Choosing the correct primitive makes an MCP server easier to understand and govern.

Search Clio contacts by name, company, or email

Search or list Clio matters by name/client and status

Capacity forecast for cloud resources, scoped to a resource type or covering everything connected

Cloud cost anomaly and reclaimable-spend report for a given window

Full network health sweep across all connected network-monitoring tools — devices down, degraded links, and topology changes

Report control and configuration drift since the last known-good baseline for a client or the whole portfolio

Build a source-cited compliance evidence package for a client against a named framework

Draft evidence-backed answers to the standard cyber-insurance questionnaire for a client

List computers in ConnectWise Automate with optional filters

Execute a script on an endpoint in ConnectWise Automate

Create a ConnectWise CPQ quote by copying a template or an existing quote

Get a ConnectWise CPQ quote with its tabs, line items, customers, and terms

List ConnectWise CPQ quote templates available to copy

Search ConnectWise CPQ quotes by account, status, or date range

Add an internal or external note to a ConnectWise PSA ticket

View agreement status and entitlements for a company in ConnectWise PSA

Close a ConnectWise PSA ticket with resolution notes

Create a new service ticket in ConnectWise PSA

Retrieve detailed ticket information from ConnectWise PSA

Log a time entry against a ConnectWise PSA ticket

Open-source MCP servers for Latin American commerce — Pix, NF-e, banking, fiscal, logistics, and messaging across Brazil, Mexico, Argentina, Colombia, Chile, an…

pi coding agent in a technicolor web trenchcoat

Open-source AI Search Intelligence Platform — track, analyze, and improve AI visibility, citations, prompts, competitors, and content opportunities across ChatG…

Open-source toolkit for the QVeris capability routing network: CLI, MCP server, Python SDK, skills, and REST API docs for agents to discover, inspect, call, and…

⚡ The Complete X/Twitter Automation Toolkit — Scrapers, MCP server for AI agents (Claude/GPT), CLI, browser scripts. No API fees. Open source. Unfollow people w…

The AI agent that interacts with you in the real world.

Offline Codex Desktop migration for Windows and macOS.

LLM 驱动的多市场股票智能分析系统：多源行情、实时新闻、决策看板与自动推送，支持零成本定时运行。 LLM-powered multi-market stock analysis system with multi-source market data, real-time news, decision dashbo…

Your smart, reliable, and friendly personal AI assistant.

The LLM Anti-Framework

A general-purpose AIGC video engine: script to finished film in one pipeline — dramas, ads, product videos, otome games, and more. | 通用 AIGC 视频引擎 —— 从剧本到成片一条流水线…

GTM agent for technical founders. Pay-per-result. Signed receipts. Two surfaces: terminal CLI + local web dashboard.

Desktop automation MCP server — computer use for any AI agent: control screen, windows, mouse/keyboard, and Chrome via Model Context Protocol (stdio)

DeepSeek Harness (dsh) Windows desktop client - bundled Node.js + dsh CLI, one-click launch

Open-source, real-time collaborative AI canvas - notes, mini-apps, and agents on one infinite board.

MCPSafari: Native Safari MCP Server for AI Agents

197 bioinformatics & life science skills for Claude Code and AI agents — BixBench 92.0% accuracy. RNA-seq, single-cell, drug discovery, proteomics, and more. Po…

The AI agent with a wallet — spends USDC autonomously to get real work done. Apache-2.0, TypeScript.

The fastest browser for AI agents to run browser automation, built for sharing your logged-in browser state with your AI agents, like Codex or Claude Code, with…

Ouroboros — self-creating AI agent. Born Feb 16, 2026.