KP Agent Ready vs Markdown for Agents and Statistics

AI agents — tools like ChatGPT, Claude, Copilot, and the growing ecosystem of autonomous AI systems — are increasingly being pointed at websites to gather information, interact with APIs, and perform tasks on behalf of users. For a site to work well with these agents, it needs to speak the right language: publishing structured discovery files, declaring its capabilities, and responding to agent-specific requests in the right format. KP Agent Ready handles all of that for your WordPress site. It implements the current set of agent-readiness standards and the broader AI agent ecosystem — without requiring you to manually create files, edit server configs, or touch a line of code. Everything is managed from a dedicated settings page in the WordPress admin. What It Does RFC 8288 Link Response Headers Every response your site sends will include Link headers pointing agents to your API catalog, agent skills index, and MCP server card. This is how agents find your discovery documents without having to guess URLs. API Catalog — /.well-known/api-catalog Publishes a machine-readable catalog of your site’s APIs in the application/linkset+json format defined by RFC 9727. Each entry in the catalog can point to an OpenAPI specification, human-readable documentation, and a health/status endpoint. If you have not configured any entries yet, the plugin serves a sensible fallback automatically so the endpoint is always valid. Agent Skills Index — /.well-known/agent-skills/index.json Publishes a skills discovery index per the Agent Skills Discovery RFC v0.2.0. This tells agents what your site can do — search your blog, browse your portfolio, submit a contact form, and so on. Skills are built from three sources: Blog articles — a search skill and a browse skill, toggled with a single switch Custom post types — any public CPT registered on your site appears as a checkbox; tick it and it gets a browse skill pointing to its archive Manual entries — define any additional skill with a name, type, description, URL, and an optional sha256 digest MCP Server Card — /.well-known/mcp/server-card.json Publishes an MCP Server Card (SEP-1649) identifying your site to Model Context Protocol clients. Configurable name, version, description, transport endpoint, and a capability list. If you do not have an MCP server running yet, just leave the transport blank — the card is still valid and useful for discovery. OAuth / OIDC Discovery — /.well-known/openid-configuration or /.well-known/oauth-authorization-server If your site exposes protected APIs that require authentication, this feature publishes the discovery metadata agents need to authenticate. Supports both OpenID Connect Discovery 1.0 and RFC 8414. Disabled by default — only enable it if you have the infrastructure in place. OAuth Protected Resource Metadata — /.well-known/oauth-protected-resource Complements the OAuth/OIDC feature by publishing RFC 9728 Protected Resource Metadata. Disabled by default. robots.txt Content Signals Appends Content Signals directives to your robots.txt file, declaring your preferences for how AI systems may use your content: ai-train — whether AI companies may use your content to train models search — whether search engines may index your content ai-input — whether AI retrieval systems (RAG) may use your content as input Markdown Negotiation When an AI agent sends a request with the Accept: text/markdown header, the plugin intercepts the response for singular posts and pages and returns a clean Markdown version of the content. Regular browser requests are completely unaffected. WebMCP Injects a small JavaScript snippet into your page footer that calls navigator.modelContext.provideContext(), exposing your site’s key actions as tools to AI agents running in the browser. Built-in tools include blog search, portfolio navigation, and contact page navigation — each individually toggleable. llms.txt and llms-full.txt Generates physical /llms.txt and /llms-full.txt files in your WordPress web root per the llmstxt.org specification. These files give AI systems a structured, readable index of your site’s content — who you are, what pages exist, and what your posts are about. llms.txt contains your site header and a clean list of links by content type. `llms-full.txt` contains the same structure but expands each entry with an excerpt or truncated content block so AI systems can understand the content without fetching every URL. Files are regenerated automatically when posts are published, unpublished, or trashed, and whenever settings are saved. A manual Regenerate button is available in the llms.txt settings tab. If your host prevents direct file writes, the generated content is displayed in the admin as a copyable textarea so you can create the files manually. Configurable options include a custom intro block, toggling pages and posts independently, selecting additional custom post types, setting the excerpt word limit for llms-full.txt, and defining optional additional links that appear under an ## Optional section in both files. Developer Filters Two filters let themes and other plugins extend the plugin’s output without touching settings: kp_agent_skills — add entries to the agent skills index: add_filter( 'kp_agent_skills', function ( array $skills ): array { $skills[] = [ 'name' => 'my-skill', 'type' => 'api', 'description' => 'Does something useful.', 'url' => 'https://yoursite.com/api/endpoint', ]; return $skills; } ); kp_webmcp_tools — add tools to the WebMCP context: add_filter( 'kp_webmcp_tools', function ( array $tools ): array { // $tools is the PHP array that becomes the JS tools array return $tools; } );

Markdown for Agents and Statistics converts your WordPress content to Markdown and serves it to AI agents and language model tools that request it via HTTP content negotiation (Accept: text/markdown). The Chancery Lane Project is a charity that helps organisations reduce emissions using the power of legal documents and processes. We’ve published this plugin as we believe that making content more legible for AI Agents makes a meaningful difference to their energy usage – not only by reducing the amount of tokens required (by up to 90% over HTML) to consume the content, but also minimising the server resources required to render, process and display pages at source. How it works: Posts and taxonomy archive pages are converted to Markdown and saved as static files on disk inside wp-content/uploads/. When a visitor (or AI agent) requests a page with Accept: text/markdown in the HTTP headers, WordPress serves the pre-generated .md file directly — no page render required. A tag is added to each page’s so agents can discover Markdown versions automatically. Features: Content negotiation (Accept: text/markdown, ?output_format=md, or known AI User-Agents) Taxonomy archive support — category, tag, and custom taxonomy term pages served as Markdown post listings Automatic Markdown generation on post save; taxonomy archives auto-update when any post in the term changes Background bulk generation — runs as a WP-Cron job with live progress, so it survives closing the tab and never times out a page request Per-post-type field configuration — choose which meta/ACF fields go in frontmatter or body ACF support with dot notation for nested group fields (e.g. group.subfield) Content fields option — use ACF fields as the body content instead of post_content Manifest generation with content hashes and change tracking per post type Incremental export — only re-export changed documents (--incremental) Delta file (changes.json) for RAG system sync Access statistics — logs AI agent requests with a dedicated stats admin page Access grouping by class of agent Optional frontmatter fields — hierarchy (parent/ancestors/children IDs), author display name, root-relative featured image paths Topics section — appends a ## Topics section with linked taxonomy terms to the Markdown body Export preview — preview generated Markdown inline in the post editor without writing to disk OKF directory indexes — index.md listings at the export root and in every post-type and taxonomy directory (Open Knowledge Format), kept current automatically OKF-compliant frontmatter and links — timestamp and flat cross-taxonomy tags frontmatter keys, and internal links rewritten to point at the Markdown file versions, always on Downloadable OKF bundle — optional .zip archive of the export tree with relative internal links, manifest.json, and an ARD discovery catalog panel, kept fresh via bulk-generation rebuilds and a debounced WP-Cron schedule ARD catalog generation — ai-catalog.json document for manual deployment to /.well-known/, discoverable by AI agent directories, shown automatically whenever the bundle toggle is on WP-CLI commands: generate, generate-taxonomies, generate-indexes, prune-stats, status, delete, bundle Fully unit-tested