"SEO" 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 Claude Desktop or Code to analyze, optimize, and automate internal linking for static Hugo sites by auditing link graphs, finding semantic link opportunities, and updating Markdown source files.

Enables integration with Ahrefs SEO tools and services through MCP protocol. Provides automated exception handling, comprehensive logging, and parallel processing capabilities for SEO data analysis and operations.

Enables AI-driven brand visibility monitoring and SEO project management via the SEOforGPT API. Users can execute brand visibility checks, list projects, and retrieve detailed visibility reports through natural language interactions.

Transforms YouTube videos into LLM-ready knowledge bases through transcription, semantic chunking, and vector embedding services. It provides 12 specialized MCP tools for video processing, semantic search, and SEO intelligence analysis.

A Model Context Protocol server that provides access to the Keywords Everywhere API, enabling AI assistants to perform SEO research including keyword analysis, domain traffic metrics, and backlink data.

Search Google and major search engines through Talordata SERP API for AI agents and RAG workflows.

Enables AI agents to audit URLs or raw HTML for SEO, AEO, and GEO performance, generate llms.txt manifests, and check the tool version via MCP tools.

MCP server for the Get Canopy WordPress site, giving AI agents context over ACF blocks, content, Yoast SEO, menus, HubSpot tooling, and the running change journal.

Read-only MCP server connecting Codex to Neo4j for querying projects, clients, tasks, and SEO audit results.

Enables querying and analysis of SEC filing documents through natural language. Uses Pinecone vector search with document summarization to help users retrieve and understand financial filings for various companies.

Enables AI agents to answer SEO, local SEO, blogging, and Etsy questions strictly from a governed knowledge base of cited course material, declining anything outside its scope.

Enables to precheck landing pages and Figma frames for readiness to be cited in AI Overviews, providing audit scores, grades, and improvement actions.

SEC EDGAR filing MCP for equity research agents: search 10-K/10-Q/8-K with CompanyFacts metrics, preview a free sample, and purchase full structured JSON via x402 USDC on Polygon. Public endpoint on xpay.tools.

A hosted multimodal RAG MCP server that enables natural language queries over text and visual content (PDFs, images, etc.) with verifiable citations, easily run via npx with a Calypso API key.

MCP server that gives AI agents persistent, tenant-scoped memory with semantic search and consolidation, using CockroachDB vector indexes and Amazon Bedrock embeddings.

MCP server for SEC EDGAR filing intelligence, providing tools for fetching, chunking/embedding, retrieval, and evaluation of filings.

SearchAtlas MCP Server connects AI assistants to the SearchAtlas platform, providing 16 specialised tools for SEO automation, content generation, PPC management, keyword research, site auditing, authority building, Google Business Profile management, and LLM brand visibility monitoring. It works with Claude Code, Cursor, Claude Desktop, VS Code, Windsurf, and Zed via stdio transport.

GraphRAG MCP server for querying SNOM CT medical terminology via Neo4j, offering graph_search_concept and graph_get_related tools to search and traverse concepts and relationships.

Enables MCP clients to list, search, and read SEC 10-K filings, returning relevant passages with company, fiscal year, section path, and SEC URL citations so answers can be grounded in source documents.

A modular RAG framework exposing knowledge retrieval tools via MCP, enabling AI assistants to perform hybrid search, reranking, and multimodal document queries with full observability and evaluation.

Enables offline archiving, deduplication, and quality-controlled indexing of Medium articles, exposing MCP tools for retrieving, managing, and exporting knowledge for AI agents and local pipelines.

Provides persistent, graph-based memory for AI agents using Neo4j and vector embeddings, enabling semantic recall across sessions via MCP.

Turns any URL into structured web intelligence in one call: SEO/OpenGraph metadata, public contacts, tech-stack fingerprinting, Schema.org data, a security-headers audit, and clean AI-ready Markdown. Anti-SSRF hardened by design.

Enables auditing webpages for GEO metrics, calculating MAVI score, and generating llms.txt templates for RAG readiness.

Integrates EdgeOne Pages Functions with large language models to retrieve and utilize user geolocation information through the Model Context Protocol (MCP).

Korean writing-style checker that flags rule violations sentence by sentence.

Provides a coherent memory layer for LLM agents that models beliefs as nodes in a constraint network to detect and surface semantic contradictions. It uses local embeddings and a hybrid geometric-logical energy model to identify conflicting information that requires review.

Enables AI coding agents to search, route, and read code across multiple repositories through a central semantic index, without needing to clone repositories locally.