# Knowledge Base > Plain-language guides to the protocols AI agents use — MCP, llms.txt, x402 payments, A2A, robots.txt and more — and how AgentGrade checks each one. ## About - [Getting Started — Make Your Site Agent-Ready](https://agentgrade.com/kb/getting-started): Quick checklist to make your site discoverable and usable by AI agents. - [Understanding Your Score](https://agentgrade.com/kb/understanding-your-score): How AgentGrade scores your site, what verified vs declared means, and how to improve. - [Cloudflare & Agent Access](https://agentgrade.com/kb/cloudflare-agent-access): Why Cloudflare blocks agent traffic and how to configure it for agent accessibility. - [About Scanning](https://agentgrade.com/kb/about-scanning): How AgentGrade scans sites, what data it collects, and how to opt out. ## Payments - [Comparing Payment Protocols](https://agentgrade.com/kb/comparing-payment-protocols): x402 vs MPP vs L402 — when to use each machine payment protocol. - [x402 — HTTP Payment Protocol](https://agentgrade.com/kb/x402): The HTTP 402 payment protocol that lets agents pay per-request with USDC on Base. Specification, comparison with traditional API monetization, ecosystem, and how to implement. - [MPP — Machine Payment Protocol](https://agentgrade.com/kb/mpp): Micropayment protocol using pathUSD on the Tempo network for sub-second agent payments. - [SPT — Stripe Shared Payment Tokens](https://agentgrade.com/kb/spt): Stripe card payments for AI agents via Shared Payment Tokens and the MPP 402 flow. - [L402 — Lightning Payments](https://agentgrade.com/kb/l402): Bitcoin Lightning Network payments for API access using macaroons and invoices. - [x-payment-info — OpenAPI Payment Discovery](https://agentgrade.com/kb/x-payment-info): Pre-request payment discovery via OpenAPI extensions so agents know pricing before triggering a 402. - [Bazaar — Service Discovery](https://agentgrade.com/kb/bazaar): The x402 service catalog that lets agents discover and browse paid API endpoints. ## Concepts - [What Is an AI Agent?](https://agentgrade.com/kb/what-is-an-agent): What an AI agent is, how it differs from a bot or a crawler, and what it needs from your website to actually work. - [How AI Agents Actually Browse the Web](https://agentgrade.com/kb/how-ai-agents-browse): How ChatGPT, Perplexity, and Gemini retrieve and process web content — and what it means for your site. - [Does llms.txt Actually Work?](https://agentgrade.com/kb/does-llms-txt-work): What llms.txt does and does not do in 2026 — the measured fetch rates, Google’s position, and why we still check it. - [Infrastructure — Cache, Errors, Redirects](https://agentgrade.com/kb/infrastructure): HTTP-level behaviors agents rely on: cache headers, structured errors, HTTPS redirect, sitemap. - [JavaScript-Rendered Sites and Agent Visibility](https://agentgrade.com/kb/javascript-rendering): Why client-rendered SPAs are invisible to AI crawlers, what it does and does not break, and how to fix it. ## Discovery - [MCP — Model Context Protocol](https://agentgrade.com/kb/mcp): The open standard for connecting AI assistants to external tools. Spec, transport options, ecosystem, authentication, debugging, and how to implement an MCP server. - [OpenAPI — API Specification](https://agentgrade.com/kb/openapi): Machine-readable API description that tells agents what endpoints exist and how to call them. - [llms.txt — LLM Context File](https://agentgrade.com/kb/llms-txt): Plain-text file that explains your service to large language models. - [llms-full.txt — Full Content for LLMs](https://agentgrade.com/kb/llms-full-txt): Companion to llms.txt: the entire site text concatenated into one file so non-browsing LLMs can ingest your content in a single fetch. - [agents.txt — Agent Access Policies](https://agentgrade.com/kb/agents-txt): Defines what AI agents are allowed to do on your service. - [Organization JSON-LD — Entity Graph for Agents](https://agentgrade.com/kb/organization-jsonld): Declare your site as a schema.org Organization with sameAs links to your other canonical surfaces. The linked-data signal LLMs use to consolidate scattered surfaces into one entity in their knowledge graph. - [AGENTS.md vs llms.txt](https://agentgrade.com/kb/agents-md-vs-llms-txt): Two root files for agents with different jobs: llms.txt is a content index; AGENTS.md is operating instructions. When to ship each — or both. - [robots.txt for Agents](https://agentgrade.com/kb/robots-txt): How robots.txt controls AI crawlers: the three-tier model (training, search, user-fetch), current tokens for OpenAI, Anthropic, Perplexity, Google, and Meta, and allow/block patterns. - [llms.txt for Shopify](https://agentgrade.com/kb/llms-txt-for-shopify): Shopify already serves llms.txt for your store — what the default contains, when to override it, and how to customize it with Liquid templates. - [llms.txt for WordPress](https://agentgrade.com/kb/llms-txt-for-wordpress): WordPress core doesn’t generate llms.txt — but your SEO plugin probably can. The current options (Yoast, Rank Math, AIOSEO, standalone plugins) and what to put in the file. - [llms.txt for Next.js](https://agentgrade.com/kb/llms-txt-for-nextjs): Next.js has no llms.txt file convention (yet) — the two patterns that work today: a static public file or an App Router route handler that stays in sync with your content. - [Skill file (SKILL.md)](https://agentgrade.com/kb/skills): A markdown file with YAML frontmatter that tells agents how to use your service. ## Identity - [Identity Protocols](https://agentgrade.com/kb/identity): Decentralized identity standards that let agents verify who owns a domain. ## Capabilities - [Content Negotiation for AI Agents](https://agentgrade.com/kb/content-negotiation): How to serve agent-optimized responses based on User-Agent and Accept headers. - [Web Bot Auth (RFC 9421)](https://agentgrade.com/kb/web-bot-auth): How AI agents prove their identity with cryptographic HTTP message signatures. - [A2A — Agent-to-Agent Protocol](https://agentgrade.com/kb/a2a): Google's protocol for AI agents to discover and communicate with other agents. - [WebMCP — Browser Agent Interaction](https://agentgrade.com/kb/webmcp): A W3C draft protocol that lets browser-based AI agents interact with websites through annotated forms.