"A guide to performing an SEO audit" matching MCP servers:

MCP server for technical SEO audits, powered by the detail.web engine. Run a site audit straight from your AI agent to get a health score, issues across 8 categories, and a GEO sub-score.

Get access to real-time SEO data, including: keyword insights, backlink data, traffic estimates and more. Allow AI tools and Large Language Models (LLMs) to tap into the real-time SEO Review Tools API with natural language commands.

Enables AI assistants to search Google SERPs, track rankings across locations, run Lighthouse SEO audits, find broken internal links, analyze backlinks, and get keyword volume data through a hosted service.

AutomateLab AI-SEO audits, scores, and rewrites web pages for AI citation eligibility, AEO and GEO. No API keys or registration. Works with Claude, Cursor, Codex, and other MCP clients. Product and documentation: https://automatelab.tech/products/mcp/ai-seo/

Enables users to cluster keyword lists, classify search intent, detect Google Search Console keyword cannibalization, score title tags and meta descriptions for CTR, and generate content briefs, all deterministically and locally from their own pasted data with no API key required. It also flags fixes such as canonical targets and merge actions for competing pages.

Connects Google Search Console and Google Analytics to AI assistants for SEO analysis, though the current public preview only exposes a service_info tool and does not yet enable Google account access.

Connects AI assistants to SEO data from Yandex Webmaster, Google Search Console, Yandex Metrica, and Topvisor, enabling natural language analysis of search performance, indexation, positions, and audits.

SEO MCP connects AI assistants to Search Console, technical SEO audits, crawl insights, Core Web Vitals, and uptime data.

Free MCP tools for context engineering audits of AI agents, offering on-demand analysis of system prompts, tool definitions, and context packing.

Enables AI assistants to query PostgreSQL, MySQL, SQL Server, Oracle, and MongoDB databases through MCP with read-only, audited access.

MCP server for Technical SEO DNS record auditing, SOA expiry health checks, SSL/TLS inspection, and HTTP security header analysis. Enables comprehensive security audits and scoring via 10 tools.

Forensic FX audit MCP. Detects hidden bank markups on cross-border payments and scores them 1-10. FINTRAC MSB registered (C10001283). Fully remote, no install required.

Provides IaC auditing across Docker Compose, Dockerfile, and GitHub Actions with 64 checks, plus HU postcode validation, via a single MCP endpoint with pay-per-event billing.

Lets any AI agent audit any website for SEO, GEO/AEO, and speed problems, reporting issues and recommendations without modifying the site.

This MCP server lets AI agents connect to Figma to read, analyze, create, and modify designs, including elements, styles, assets, and code generation. It works with free Figma accounts and supports parallel multi-agent use across MCP-compatible clients.

Enables agents to generate tamper-evident SHA-256 Merkle audit trails, produce logarithmic inclusion proofs, and verify integrity through a STDIO MCP interface.

Enables MCP clients to run local scans for known AI coding-assistant backdoor indicators and risky Claude Code/MCP configuration patterns, returning findings directly in chat.

Enables agents to hash execution logs into tamper-proof Merkle trees, compute cryptographic inclusion proofs, and verify audit integrity through MCP tools.

Automated SEO, AEO, ADA auditing for your website or project.

42 local SEO tools for AI assistants. SERP tracking, Google Business Profile data, review monitoring, keyword research, AI visibility scoring, geogrid rank scans, citation audits, and competitive analysis.

Universal HTTP 402 Micropayment Protocol & Autonomous Economic Settlement Engine for AI Agents on Base L2.

Enables auditing of extracted balance sheets, income statements, and cash flow reports by reconstructing complex document tables and verifying mathematical consistency and formula balancing. It also performs cross-reference resolution and sensitive PII redaction, returning structured matrices and validation telemetry over MCP to clients like Claude Desktop, Cursor, and Windsurf.

Answers why a specific number in a Chinese listed company moved — margins, cash flow, inventory, management commentary, policy impact — by reading filed reports and IR transcripts and returning figures with the document and announcement number attached. It deliberately refuses price, valuation, and recommendation queries, returning a "gone_by_design" error instead.

Enables agents to transform tabular Markdown content into structured, type-inferred records with normalized formatting through an MCP-compatible interface.

Enables searching and retrieving content, module information, and Twig template snippets from a-blog cms via its GET API.

What is PandaDoc MCP? PandaDoc MCP (Model Context Protocol) server connects AI agents directly to PandaDoc's document workflow — creating, sending, and tracking contracts and agreements without leaving your AI client. How to use PandaDoc MCP? To use PandaDoc MCP, connect your PandaDoc account, provide the required API credentials, and configure the appropriate MCP client.

Enables converting Markdown and HTML tables into structured JSON records with automatic column type inference and format normalization. It also offers supporting web-agent primitives such as DOM semantic pruning, form field auto-mapping, and execution trajectory evaluation, all via a zero-dependency MCP server.

Lets an AI assistant read call and message history, send texts and picture messages, reach Phone Book contacts by name, and — once switched on — place calls run by a voice agent, all limited to the phone numbers the user ticks. Hosted remotely with OAuth sign-in, so nothing needs to be installed locally.

Enables agents to break high-level business objectives into dependency-ordered sub-task graphs and then directly generate the finished deliverables, such as financial spreadsheets, executive presentations, and analytical reports. It runs as a zero-dependency Python MCP server over JSON-RPC stdio, adding deterministic authorization, role-boundary validation, and telemetry.

Audits extracted balance sheets, income statements, and cash flow reports for mathematical consistency and formula balancing, reconstructing complex financial tables and resolving cross-references from document or OCR payloads. Also performs spatial layout parsing and PII redaction, returning structured matrices and validation telemetry over MCP.