# ai-seo **Category:** 🎯 Marketing **Repository:** https://github.com/AutomateLab-tech/ai-seo **Views:** 0 **Installs:** 0 **Upvotes:** 0 **Directory Page:** https://allmcps.com/mcp/ai-seo ## Description MCP server for AI-SEO auditing: schema, robots.txt, llms.txt, citation scoring, and AEO/GEO rewrites ## Claude Desktop Quick Installation Heuristic fallback — verify the package name and runner against the repository README before running it. Uses `npx` (confidence: low): ```json "mcpServers": { "ai-seo": { "command": "npx", "args": ["-y","ai-seo"] } } ``` ## Documentation & README # @automatelab/ai-seo-mcp > AI Citation Toolkit for the Model Context Protocol [![npm version](https://img.shields.io/npm/v/@automatelab/ai-seo-mcp.svg)](https://www.npmjs.com/package/@automatelab/ai-seo-mcp) [![license](https://img.shields.io/npm/l/@automatelab/ai-seo-mcp.svg)](./LICENSE) [![node](https://img.shields.io/node/v/@automatelab/ai-seo-mcp.svg)](https://nodejs.org) **Audit why AI systems do or do not cite your pages.** MCP server. No API keys. Works inside Claude, Cursor, Windsurf, Codex, and any MCP client that speaks stdio. --- ## What it checks - **AI crawler access** - GPTBot, OAI-SearchBot, ClaudeBot, and PerplexityBot allowed or blocked in `robots.txt` - **`llms.txt`** - present, spec-compliant, links alive - **Structured answer extraction** - FAQ headings, BLUF paragraphs, answer-ready blocks - **[[schema]] completeness** - FAQPage, Article, Organization, Person; flags deprecated patterns - **Entity clarity** - named entity density and `sameAs` coverage that help AI systems identify the subject - **Citation formatting** - canonical URL hygiene, `og:url`, `hreflang`, noindex traps - **Sitemap freshness** - `lastmod` signals that tell crawlers the page is current --- ## Run an audit. Get a list of citation-blockers, ranked. > **You:** Run an AI-SEO audit on `https://automatelab.tech/launching-the-ai-seo-mcp/`. Result (truncated): ```json { "url": "https://automatelab.tech/launching-the-ai-seo-mcp/", "score": 61, "grade": "C", "dimension_scores": { "schema": 45, "technical": 80, "structure": 40, "robots": 90, "freshness": 85, "authority": 40, "entity_density": 21, "sitemap": 100 }, "findings": [ { "severity": "critical", "category": "structure", "message": "No FAQ structure found (no FAQPage schema or H3 question headings).", "fix": "Add FAQ H3 headings ending in '?' with answer paragraphs, and a FAQPage JSON-LD block.", "estimated_impact": "high" }, { "severity": "warning", "category": "authority", "message": "Low authority signals - missing Organization or author Person schema.", "fix": "Add Organization JSON-LD and Article.author as a Person node with sameAs links.", "estimated_impact": "high" } ] } ``` Each finding names the exact fix. No opaque scores, no guesswork. --- ## Install ```bash npx -y @automatelab/ai-seo-mcp ``` Requires Node 20 or later. ### Claude Desktop Add to `%APPDATA%\Claude\claude_desktop_config.json` (Windows) or `~/Library/Application Support/Claude/claude_desktop_config.json` (macOS): ```json { "mcpServers": { "ai-seo": { "command": "npx", "args": ["-y", "@automatelab/ai-seo-mcp"] } } } ``` Restart Claude Desktop. Any MCP client that supports stdio transport works - same `command` / `args` pattern. ### Optional: headless rendering for SPAs By default `audit_page` reads raw HTML — fast, but misses content on React/Vue/Angular SPAs. Pass `render: "headless"` to spin up Chromium and audit the rendered DOM (adds 3-10s per audit). One-time install: ```bash npm install playwright-core npx playwright install chromium ``` Then call `audit_page` with `render: "headless"`. Use static for everything else — most marketing sites and docs render fine without it. --- ## Run it in CI (GitHub Action) This repo doubles as a GitHub Action. Drop it in a workflow to fail a PR when any page regresses below an AI-citation score - the same audit engine, gated on every change. ```yaml - uses: actions/checkout@v4 - name: AI-SEO audit uses: AutomateLab-tech/ai-seo-mcp@v0.5.0 with: urls: "https://example.com,https://example.com/pricing" min-score: "70" # fail if any URL scores below this respect-robots: "true" # set false for staging / sites you own report-path: "ai-seo-report.md" # optional Markdown report artifact fail-on-regression: "true" ``` The Action builds the auditor from the pinned ref, runs `audit_page` on each URL, writes a scorecard to the job summary, and exits non-zero if any URL falls below `min-score` (when `fail-on-regression` is true). Outputs: `min_score_observed`, `urls_audited`, `report_path`. Full example: [`examples/github-action-usage.yml`](./examples/github-action-usage.yml). --- ## Further reading - [automatelab.tech](https://automatelab.tech/products/mcp/ai-seo/) - teardowns and case studies ---
MCP tool surface (19 tools) | Tool | Purpose | |------|---------| | `audit_page` | Composite AI-SEO audit with 8-dimension scoring (schema, technical, structure, robots, freshness, authority, entity density, sitemap). | | `audit_schema` | Validate JSON-LD against Schema.org rules and AI-citation best practice. Flags deprecated patterns. | | `audit_canonical` | Canonical link integrity, trailing-slash hygiene, `og:url` consistency. | | `audit_site` | Single-call site sweep: `audit_page` + `check_robots` + `check_sitemap` + `audit_schema` with overall grade and top-5 fixes. | | `audit_sitemap` | Site-wide content audit: stride-sample N URLs from the sitemap, run `audit_page` on each, return distribution + worst pages + top findings. | | `check_robots` | Parse `robots.txt` and report per-crawler allow/disallow for all known AI crawlers. Surfaces the GPTBot-blocked-but-OAI-SearchBot-allowed trap. | | `check_sitemap` | Validate XML sitemaps: presence, URL count, `lastmod` freshness, image/video extensions. | | `check_technical` | HEAD tag audit: canonical, OpenGraph, Twitter Card, hreflang, HTTPS, noindex, title hygiene. | | `score_ai_overview_eligibility` | Score a page's probability of appearing in Google AI Overviews using current correlation factors. | | `score_citation_worthiness` | Score how citable a page or text block is for Perplexity, ChatGPT, Google AI Overviews, and Claude. Includes per-section `chunk_analysis` / `extractability_score`: how cleanly an LLM can lift a standalone answer from each heading. | | `score_agentic_browsing` | Score a page against the Lighthouse "Agentic Browsing" category (May 2026): llms.txt, WebMCP, accessibility-tree integrity, and layout stability. | | `score_test_citation` | Simulate "would an AI engine cite this for this query?" via MCP sampling, with deterministic heuristic fallback. | | `llms_txt_generate` | Generate `llms.txt` and optionally `llms-full.txt` from a domain's sitemap. | | `llms_txt_validate` | Lint an existing `llms.txt` for spec compliance and broken links. | | `rewrite_aeo` | Rewrite content for Answer Engine Optimization (BLUF structure, FAQ format, schema additions). | | `rewrite_geo` | Rewrite content for Generative Engine Optimization (entity definitions, comparison tables, synthesis-ready structure). | | `extract_entities` | Extract named entities, `sameAs` links, and citation-density score from a page's content and structured data. | | `diff_pages` | Compare two URLs for AI citation-worthiness: side-by-side dimension scores, gap analysis, and prioritized fix recommendations for url_a. | | `report_save` | Render an `audit_page` / `audit_site` result as a Markdown report and write it to disk under `MCP_WORKSPACE_ROOT`. | > **v0.4.0** renamed tools from flat `snake_case` to dot-notation (`audit_page`, `check_robots`, …) for a navigable hierarchy. Update any saved invocations. Environment variables: see [ENV.md](./ENV.md).
--- ## Contributing Bug reports, feature ideas, and PRs welcome. See [CONTRIBUTING.md](./CONTRIBUTING.md). ## Security To report a vulnerability, see [SECURITY.md](./SECURITY.md). ## License MIT - see [LICENSE](./LICENSE). Built by [automatelab.tech](https://automatelab.tech)