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Labs","email":"contact@ouranos-labs.dev"},"license":"MIT","homepage":"https://pseolint.dev","keywords":["mcp","model-context-protocol","seo","pseo","spambrain","lint","ai"],"repository":{"type":"git","url":"git+https://github.com/ouranos-labs/pseolint.git","directory":"packages/mcp"},"description":"MCP server for pseolint: audit programmatic SEO sites from AI coding assistants. v0.5 adds the AI-orchestrated audit tool that produces a fix manifest with concrete patches.","maintainers":[{"name":"tikkatenders","email":"philippe.kam27@gmail.com"}],"readme":"# @pseolint/mcp\r\n\r\n> MCP server for pseolint: audit pSEO sites by template from AI coding assistants.\r\n\r\nAn [MCP (Model Context Protocol)](https://modelcontextprotocol.io) server that exposes [pseolint](https://www.npmjs.com/package/pseolint) v0.7.5 auditing tools to AI coding assistants like Claude Code, Claude Desktop, Cursor, and Windsurf.\r\n\r\nAll tools are namespaced with a `pseolint_` prefix (`pseolint_audit_site`, `pseolint_explain_score`, `pseolint_check_page_technical`, `pseolint_orchestrate_audit`) so they don't collide with other MCP servers, and each returns both human-readable text and machine-readable `structuredContent`.\r\n\r\n### What's new in v0.6: per-template output in tool responses\r\n\r\n`audit_site` now returns a `templates` array alongside the existing `findings` list. AI clients get the per-template view automatically; no parameter changes needed.\r\n\r\n```json\r\n{\r\n  \"verdict\": \"concerning\",\r\n  \"risk\": 60,\r\n  \"templates\": [\r\n    {\r\n      \"signature\": \"/listing/:slug\",\r\n      \"totalUrls\": 8201,\r\n      \"auditedUrls\": [\"https://example.com/listing/foo\", \"...\"],\r\n      \"verdict\": \"concerning\",\r\n      \"risk\": 60,\r\n      \"variance\": {\r\n        \"uniformityScore\": 0.85,\r\n        \"topDriver\": { \"ruleId\": \"spam/thin-content\", \"fireRate\": 0.8 }\r\n      }\r\n    },\r\n    { \"signature\": \"/category/:slug\", \"verdict\": \"ready\", \"risk\": 12 }\r\n  ],\r\n  \"findings\": [...]\r\n}\r\n```\r\n\r\nWhen iterating `templates`, the `topDriver` rule + `fireRate` is the most actionable signal: \"8/10 samples fail `spam/thin-content`\" tells the LLM which template is broken and what to fix. The `findings` flat list remains available for per-URL drill-down.\r\n\r\nDesign rationale: [`docs/superpowers/specs/2026-05-04-pseolint-v0.6-audit-as-template-reframe.md`](../../docs/superpowers/specs/2026-05-04-pseolint-v0.6-audit-as-template-reframe.md)\r\n\r\n### What's new in v0.5.2: credibility layer\r\n\r\n- **4 new content-quality rules** in the underlying engine (consumed by `audit_site` and `orchestrate_audit`): `content/title-uniqueness`, `content/heading-structure`, `content/image-alt-text`, `tech/og-completeness`. Findings appear in tool output as standard rule findings.\r\n- **`audit_site.authorityScore`** parameter (0-100): bring-your-own-DA. `>= 80` shifts the verdict one tier lenient on established brands; `<= 30` shifts one tier stricter on newer/lower-authority operators. Raw `risk` number unchanged.\r\n- **`audit_site.sampleSeed`** parameter: deterministic sampler. Same seed = same audit = same verdict, run after run. AI assistants asking the user to confirm a finding can re-audit reproducibly.\r\n- **`spam/doorway-pattern` cluster collapse**: a 276-pair finding on a catalog directory now arrives as one cluster line per group, not 276 line items eating the LLM's context window.\r\n- **Findings stay actionable**: info-severity findings are capped per category bucket so they can't accumulate to tank a verdict on their own; the LLM gets the actual signal, not noise.\r\n- **Calibrated** against reputable in-production pSEO sites; trade-offs and limitations documented at [pseolint.dev/methodology](https://pseolint.dev/methodology).\r\n\r\n### What's new in v0.5\r\n\r\n**`orchestrate_audit` tool.** Drives an LLM through 25 deterministic audit tools and produces a fix manifest with concrete copy-paste patches (rewritten H1s, JSON-LD blocks, robots.txt diffs). Use when a user wants concrete fixes, not just a list of issues.\r\n\r\n**Conservative MCP defaults**: $2 / 60 tool calls / 180 seconds wall (vs CLI's $5 / 100 / 300). Two output modes: `summary` (terse text for chat UI) and `json` (full manifest + validation + diff). Each invocation reports actual USD spend. Patches that fail deterministic validators are dropped from the manifest and surfaced separately.\r\n\r\n**Example prompt**: \"Use the pseolint_orchestrate_audit tool to run an AI-native audit of https://example.com with concrete fix proposals.\"\r\n\r\n### Safety defaults (v0.3.3+)\r\n\r\nAll three tools default to `safeMode: \"saas\"`; AI assistants running in end-user\r\nenvironments can't be tricked into scanning AWS/GCP metadata endpoints, localhost,\r\nor RFC1918 networks via a malicious URL argument. Specifically:\r\n\r\n- `guardSsrf: true`: DNS-validated private-range check on the source URL,\r\n  sitemap entries, redirect hops, and discovered links\r\n- `respectRobotsTxt: true`: sitemap URLs Disallow'd by the target's `robots.txt`\r\n  are skipped instead of crawled\r\n- Tighter `maxFetchBytes` (10 MB) and `maxCrawlDiscovered` (2000) caps\r\n\r\n## Tools\r\n\r\n### `pseolint_orchestrate_audit` (v0.5)\r\n\r\nDrive an LLM through 25 audit tools and produce a fix manifest with concrete patches. Use when a user wants paste-able fixes (not just a list of issues). Costs ~$1-3 per audit on managed Anthropic.\r\n\r\n**Parameters:**\r\n- `domain` (required): URL of the site to audit (e.g. https://example.com)\r\n- `maxCostUsd`: Hard USD cap (default 2)\r\n- `maxToolCalls`: Hard tool-call cap (default 60)\r\n- `maxWallSeconds`: Hard wall-clock cap (default 180)\r\n- `format`: `summary` (terse text) or `json` (full manifest + validation + diff)\r\n\r\n**Returns**: text summary with verdict + categories + top-3 patches per bucket (or full JSON when `format: \"json\"`). Validation failures listed separately so the LLM-host conversation stays grounded in what actually shipped.\r\n\r\n**Example prompt:** \"Use pseolint_orchestrate_audit on https://example.com with format=summary\"\r\n\r\n### `pseolint_audit_site`\r\n\r\nRun a full pseolint audit on a URL or directory path. Returns the site-level verdict + risk score, a `templates` array (per-template verdicts + variance metrics), and all per-URL findings with actionable fix suggestions.\r\n\r\n**Parameters:**\r\n- `source` (required): URL or directory path to audit\r\n- `threshold`: Score threshold for pass/fail (default: 40)\r\n- `sampleSize`: Audit a random subset of N pages (0 = all)\r\n- `format`: Output format: `console` or `json` (default: console)\r\n- `authorityScore`: 0-100 domain authority hint. ≥80 shifts verdict one tier lenient; ≤30 shifts one tier stricter. Raw `risk` number unchanged.\r\n- `contentEffort` (boolean, default false): enable the AI content-effort signal: an LLM judges a 0-100 originality/effort score from sampled page text that moderates the verdict ±1 tier. Requires `ANTHROPIC_API_KEY` in the MCP server's environment; no-ops safely without one. Adds a few cents of LLM cost per audit.\r\n- `sampleSeed`: Integer seed for deterministic stratified sampling. Same seed = same audit = same verdict.\r\n\r\n**Returns (v0.6 shape):** `verdict`, `risk`, `categories`, `templates: Template[]`, `findings: RuleResult[]`. AI clients should iterate `templates` first; `topDriver.ruleId + fireRate` is the most actionable per-template signal. Use `findings` for per-URL drill-down.\r\n\r\n**Example prompt:** \"Audit my site at http://localhost:3000; show me the per-template breakdown\"\r\n\r\n### `pseolint_explain_score`\r\n\r\nRun an audit and get a human-readable explanation of what's driving the SpamBrain Risk Score, including category breakdowns, top issues, and prioritized fix suggestions.\r\n\r\n**Parameters:**\r\n- `source` (required): URL or directory path to audit\r\n- `threshold`: Risk threshold for the pass/fail verdict (default: 40)\r\n- `authorityScore`: 0-100 domain authority hint. ≥80 shifts verdict one tier lenient; ≤30 shifts one tier stricter. Raw `risk` number unchanged.\r\n- `contentEffort` (boolean, default false): enable the AI content-effort signal: an LLM judges a 0-100 originality/effort score from sampled page text that moderates the verdict ±1 tier. Requires `ANTHROPIC_API_KEY` in the MCP server's environment; no-ops safely without one. Adds a few cents of LLM cost per audit.\r\n- `sampleSeed`: Integer seed for deterministic stratified sampling.\r\n\r\n**Example prompt:** \"Explain why my site's SpamBrain score is high\"\r\n\r\n### `pseolint_check_page_technical`\r\n\r\nCheck a single page URL for per-page technical SEO issues (canonical, Open Graph, JSON-LD, robots, meta, thin content, author signals). Does not run cross-page rules; use `pseolint_audit_site` for those.\r\n\r\n**Parameters:**\r\n- `url` (required): Full URL of the page to check\r\n\r\n**Example prompt:** \"Check https://yoursite.com/templates/california-llc for technical SEO issues\"\r\n\r\n## Resources\r\n\r\nThe server also exposes pseolint's rule knowledge as read-only [MCP resources](https://modelcontextprotocol.io), so an assistant can explain a finding without guessing or fetching the web. The resources are keyed by `ruleId`, the same identifier that appears on every audit finding (e.g. `spam/thin-content`), so they line up 1:1 with tool output.\r\n\r\n- **`pseolint://rules`**: a JSON index of every documented rule (`ruleId`, `title`, and the per-rule resource URI). Read this first to discover what's available.\r\n- **`pseolint://rules/<ruleId>`**: one Markdown resource per rule, e.g. `pseolint://rules/spam/thin-content`. Each contains the rule's link, a **What it detects** section, and a **How to fix** checklist.\r\n\r\nTypical flow: run `pseolint_audit_site`, take a `ruleId` off a finding, then read `pseolint://rules/<ruleId>` to ground the explanation and fix advice in pseolint's own rule documentation.\r\n\r\n## Remote server (hosted, zero-install)\r\n\r\nPrefer not to install anything? Point your MCP client at the hosted endpoint:\r\n\r\n    https://pseolint.dev/mcp\r\n\r\nIt serves the three read-only audit tools (`pseolint_audit_site`, `pseolint_explain_score`,\r\n`pseolint_check_page_technical`) with no signup; anonymous use is rate-limited. Create an\r\nAPI key in your pseolint.dev dashboard and send it as `Authorization: Bearer <key>` to raise\r\nyour limits. The AI-orchestrated `pseolint_orchestrate_audit` tool is available only via the\r\nstdio package (below) or the CLI for now.\r\n\r\nExample client config:\r\n\r\n    { \"url\": \"https://pseolint.dev/mcp\", \"headers\": { \"Authorization\": \"Bearer <key>\" } }\r\n\r\n## Installation\r\n\r\n### Claude Code\r\n\r\n```bash\r\nclaude mcp add pseolint -- npx @pseolint/mcp\r\n```\r\n\r\n### Claude Desktop\r\n\r\nAdd to `claude_desktop_config.json`:\r\n\r\n```json\r\n{\r\n  \"mcpServers\": {\r\n    \"pseolint\": {\r\n      \"command\": \"npx\",\r\n      \"args\": [\"@pseolint/mcp\"]\r\n    }\r\n  }\r\n}\r\n```\r\n\r\n### Cursor\r\n\r\nAdd to `.cursor/mcp.json`:\r\n\r\n```json\r\n{\r\n  \"mcpServers\": {\r\n    \"pseolint\": {\r\n      \"command\": \"npx\",\r\n      \"args\": [\"@pseolint/mcp\"]\r\n    }\r\n  }\r\n}\r\n```\r\n\r\n### Windsurf\r\n\r\nAdd to `~/.codeium/windsurf/mcp_config.json`:\r\n\r\n```json\r\n{\r\n  \"mcpServers\": {\r\n    \"pseolint\": {\r\n      \"command\": \"npx\",\r\n      \"args\": [\"@pseolint/mcp\"]\r\n    }\r\n  }\r\n}\r\n```\r\n\r\n### VS Code (GitHub Copilot)\r\n\r\nAdd to `.vscode/mcp.json`:\r\n\r\n```json\r\n{\r\n  \"servers\": {\r\n    \"pseolint\": {\r\n      \"command\": \"npx\",\r\n      \"args\": [\"@pseolint/mcp\"]\r\n    }\r\n  }\r\n}\r\n```\r\n\r\n## What It Checks\r\n\r\n44 rules, grouped by theme (scored across 4 categories: integrity, discoverability, citation, data):\r\n\r\n- **SpamBrain Risk**: near-duplicate detection, entity-swap doorway pages, thin content, boilerplate ratio\r\n- **Content Quality**: unique value per page, heading/meta uniqueness, E-E-A-T signals\r\n- **Internal Linking**: orphan pages, dead ends, cluster connectivity, link depth\r\n- **Technical SEO**: canonical consistency, sitemap completeness, robots.txt conflicts\r\n- **Structured Data**: JSON-LD validation, required fields, schema consistency\r\n- **Cannibalization**: URL pattern conflicts (`title-overlap` and `keyword-collision` were dropped in v0.4 for high false-positive rates)\r\n\r\n## Links\r\n\r\n- [GitHub](https://github.com/ouranos-labs/pseolint)\r\n- [npm: pseolint](https://www.npmjs.com/package/pseolint)\r\n- [npm: @pseolint/core](https://www.npmjs.com/package/@pseolint/core)\r\n\r\n## License\r\n\r\nMIT\r\n","readmeFilename":"README.md"}