LLM Mart Basic

Atera service desk tickets: ticket fields, statuses, priorities, comments, work hours, and billing duration.

Auvik alerts: severity tiers, status lifecycle, dismissal semantics, and the common alertName patterns that show up in MSP NOC queues.

Auvik MCP fundamentals: the JSON:API envelope shape, basic-auth credential model, region routing, cursor-based pagination, rate-limit handling, and the v1 vs v2 device API distinction.

Auvik device records: device types, manageStatus and onlineStatus, lifecycle and warranty fields, and choosing between the v1 list endpoint and the detailed device endpoints.

Auvik network and interface entities: the network entity model, IP-range scoping, interface-to-device relationships, and adminStatus vs operStatus.

Autotask REST API fundamentals: header-based authentication, zone detection, the query/filter DSL (14 operators, logical grouping, includes), pagination, rate limits, and CRUD conventions across the 215+ entity PSA.

Autotask billing item retrieval, approval-level workflows, and invoice search — covering billing item types, approval status filtering, and reconciliation of billable work against invoices for MSP finance teams.

Autotask Configuration Item (CI) asset management: CI types and categories, lifecycle status codes, the CI field schema, related-item relationships, DNS records, notes, and contract/billing associations for MSP infrastructure tracking.

Autotask contract and service agreement management - contract types (recurring services, block hours, time & materials, fixed price, retainer), service/service bundle associations, SLAs, and how contracts drive billing for MSP account managers.

Autotask CRM entities - companies (accounts), contacts, and sites/locations - including field references, company type classifications, and how these records underpin tickets, contracts, and projects for MSP account management.

Autotask expense report and expense item structure - the report/item parent-child relationship, approval status workflow, expense categories, payment types, and the billable vs reimbursable distinction for MSP operational expenses.

Autotask picklist and reference-data lookups — queues, ticket statuses, ticket priorities, and project phases — the instance-specific configured values required before creating or filtering tickets and other entities.

Autotask product catalog structure - Products, Services, and Service Bundles - and how Price Lists override default unit pricing. Covers product/service fields, inventory tracking, and cost-vs-billing margin analysis for MSP quoting and procurement.

Autotask project structure - projects, phases, tasks, and milestones - including project and task fields, status values, resource assignment, and how project work links to contract billing for MSP project managers.

Autotask quote structure and line items - quote item types (product, service, service bundle, labor, expense, shipping), the mutually-exclusive catalog reference rules, and the three discount mechanisms (unit, line, percentage) used to build customer proposals.

Autotask Service Call data model - the ServiceCall / ServiceCallTicket / ServiceCallTicketResource three-layer structure - covering fields, status codes, and how tickets and technicians (resources) are linked to scheduled work.

Autotask ticket notes, attachments, and charges — the secondary entities attached to tickets: retrieving/searching notes and attachments, and creating, updating, or searching ticket charges for labor and expenses billed directly to a ticket.

Autotask ticket lifecycle: status/priority codes and transition rules, the ticket field schema, SLA calculation and clock behavior, escalation rules, ticket metrics, and the MCP tool surface (create, update, search, history, notes) for MSP service desk operations.

Autotask time entry structure: approval status codes and workflow, the time entry field schema, the billing rate hierarchy, budget and contract-limit validation, utilization analytics, and the MSP business rules for rounding and minimum billing increments.

The Autotask MCP lazy-loading pattern - four meta-tools (list_categories, list_category_tools, execute_tool, router) that expose the full 39+ tool catalog progressively instead of loading every tool schema upfront, plus the natural-language router for intent-based tool lookup.

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.

Generate API documentation from code

Update or generate YAML documentation for SQL models with proper descriptions and tests

Configure end-to-end testing suite

Generate accurate project time estimates

Analyze and explain code functionality

Explain how tasks in an issue were implemented with detailed breakdown

Search and locate tasks across all orchestrations using various criteria.

Apply the Five Whys root cause analysis technique to systematically investigate issues

Analyze and fix a GitHub issue with comprehensive testing and verification

Fix a specific issue or problem with the given identifier or description

Fetch unresolved comments for current branch's PR and fix them

Generate and analyze future scenarios with plausibility scoring, trend integration, and uncertainty quantification.

Auto-generate API reference documentation

You are tasked with generating a technical work log comment for a Linear issue based on recent git commits.

Generate comprehensive test cases automatically

Generate comprehensive test suite for $ARGUMENTS following project testing conventions and best practices.

Show detailed git repository status

Deploy critical hotfixes quickly

Verify repository is in working state by running CI checks and fixing issues

Design and implement caching solutions

Paper trading simulator for Polymarket — built for AI agents. MCP server, live order books, strategy backtesting. Install: npx clawhub install polymarket-paper-…

An SSH tool dedicated to addressing all pain points · (macOS/Windows/Linux/Android/iOS)

The first AI agent harness native to the browser. A browser extension that runs a full agent loop where you already work: it drives your tabs, spins up sandboxe…

SmartLabel AI 2026: Auto-Annotate Any Object via LLM-Powered Prompt Parsing

Local-first visual generation runtime and studio for people and coding agents, with reproducible image and video workflows across multiple providers.

Scholar All-In-One: A research infrastructure for AI agents

Give your AI agent a real browser — with a human in the loop. Open-source MCP-native browser agent.

同花顺免费开源AI插件FQGate-agent（原插件名 tonghuasun-agent）：为 Codex、Claude Code、DeepSeek 等 AI 工具提供本机 A 股实时行情、K 线、Level-2、资讯、账户查询与可选交易能力。

A non-linear AI agent workbench — session is a tree: branch anytime, and context follows the branch

Production-grade AutoCAD MCP server for AI agents — 122 tools, dual COM (live AutoCAD) + headless ezdxf engines, ISO GD&T and dimension-tolerance validation for…

A DeepSeek coding agent harness: persistent shell, Ultra subagents, auto approval, Chrome MCP and session telemetry

Waku Waku! Waku Agent is a local-first AI agent harness you actually own, including loop, memory, eval, all in code built to stay legible as it grows.

Remote control for Claude Code, Codex, Grok, and Cursor on Mac or PC. View sessions, send tasks, and drive them remotely from your phone, PIN, or Ring. OpenClaw…

Next-gen AI-native server ops panel with an in-workspace SRE agent. Crash self-healing, safe rollbacks, Docker/game servers, and local Ollama support.

Professional cloud architecture diagrams with official AWS, Azure and GCP icons, from Terraform code or a plain JSON graph. MCP server + agent skill.

A ready-to-use self-growing desktop AI assistant for long-running tasks, memory, agents, tool reviews, MCP, and high-concurrency workspace automation. / 开箱即用的自我…

Collection of templates using the Alchemyst AI Platform for your next big AI app.

Fast, exact LLM decoding on Apple Silicon (MLX) behind an OpenAI-compatible endpoint

The open source AI research agent.

Open-source agent-native visual production workspace where humans and coding agents edit the same live canvas — local-first, BYOK image/video models.