Borrowing it
Nothing to install: this file belongs to g-battaglia/mcp-seo. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/g-battaglia/mcp-seo/main/AGENTS.mdgit clone --depth 1 https://github.com/g-battaglia/mcp-seoWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/g-battaglia/mcp-seo/agents-md)<a href="https://agentmods.dev/instructions/g-battaglia/mcp-seo/agents-md"><img src="https://agentmods.dev/badge/instructions/g-battaglia/mcp-seo/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/g-battaglia/mcp-seo/agents-md"><img src="https://agentmods.dev/badge/instructions/g-battaglia/mcp-seo/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.02085 | $0.02085 |
| Opus 5 | $0.01043 | $0.01043 |
| Sonnet 5 | $0.00417 | $0.00417 |
| Haiku 4.5 | $0.00209 | $0.00209 |
Grade A, and why
mcp-seo AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 209 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — MCP-SEO for Autonomous LLM Agents
Overview
This project provides a comprehensive set of SEO analysis tools designed to be used by an LLM agent autonomously. All tools are accessible via the mcp-seo CLI or the built-in MCP server, and produce structured, markdown-formatted output that is easy for an LLM to parse and reason about.
The tools use a headless browser (Playwright/Chromium) for rendering JavaScript-heavy pages, and httpx for lightweight HTTP fetching.
Setup
Before using any tools, the agent must run:
mcp-seo setup
This installs the Playwright Chromium browser (one-time only).
Available Tools
Via CLI
All tools follow the pattern: mcp-seo <command> <url>
Via MCP Server
Start with mcp-seo mcp — all tools are exposed as MCP tools that accept a url parameter and return Markdown reports.
Page Fetching
| CLI Command | MCP Tool | Description |
|---|---|---|
mcp-seo url-structure <url> |
analyze_url_structure |
URL length, depth, separators, tracking params |
mcp-seo accessibility <url> |
analyze_accessibility |
ARIA landmarks, skip-nav, forms, images, score |
mcp-seo crawl <url> |
crawl |
Render page with headless Chromium, return full HTML |
mcp-seo fetch <url> |
fetch_page |
Fetch raw HTTP response as JSON |
On-Page SEO
| CLI Command | MCP Tool | Description |
|---|---|---|
mcp-seo meta <url> |
analyze_meta_tags |
Title, description, OG, Twitter, canonical, viewport |
mcp-seo headings <url> |
analyze_headings |
Heading hierarchy (h1-h6), single H1, skip checks |
mcp-seo content <url> |
analyze_content |
Word count, readability, keywords, n-grams |
mcp-seo images <url> |
analyze_images |
Alt text, lazy loading, dimensions, modern formats |
mcp-seo links <url> |
analyze_links |
Internal/external, nofollow, anchor text analysis |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 209 lines · 2,085 tokens per session scan A 1e282b59e777
mcp-seo AGENTS.md is an instructions file published in the GitHub repository g-battaglia/mcp-seo (1 stars, last pushed 4mo ago), licensed MIT. It adds 2,085 tokens to every session, about $0.0104 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.