"A guide to creating SEO blogs and articles" matching MCP servers:

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.

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.

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

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

Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.

AI visibility and SEO data for AI agents. Check whether ChatGPT, Claude, Perplexity and Gemini mention your brand and which sources they cite, plus keyword volume and Google Trends.

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.

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.

This MCP wraps Bitrefill public API to allow agents to search for products and shop using cryptocurrencies like Bitcoin, Ethereum, Solana, and many more.

Credit and payments for AI agent developers — over MCP. No crypto required

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

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.

Enables MCP-compatible editors to orchestrate test runs, debug failures, analyze visual regressions, run accessibility audits, and manage test cases through natural language.

MCP-first A/B testing server that enables agents to manage experiments (create, update traffic splits, read results, apply winning variants) from tools like Claude Code, with self-hosted Cloudflare backend.

Provides Figma design context to AI agents, enabling code generation, design system integration, and canvas manipulation through MCP.

Connects AI coding assistants to Anima Playground, Figma designs, and design systems, enabling handoff of designs to production code.

Enables AI agents to check a list of websites by running an Apify Actor through one tool, returning per-site tech stack, on-page SEO issues and score, robots.txt rules for AI crawlers, sitemap, llms.txt presence, and an AI-readiness score. Supports local stdio operation with an Apify token for tool calls.