"A tool for inspecting SEO and validating schema markup in web pages" matching MCP servers:

An MCP server that provides targeted PostgreSQL schema access to AI agents, retrieving only relevant tables for a question and enforcing read-only access through multiple layers.

Enables automated schema management for Baserow, including creating, updating, and deleting tables and fields, with built-in 2FA TOTP authentication.

An MCP server that provides persistent memory for database schemas by storing table structures and metadata in a local SQLite file. It enables LLMs to save, retrieve, and manage database snapshots to maintain a structured understanding of database architectures.

A read-only MCP server for PostgreSQL schemas and their git history, enabling AI agents to inspect schema details, migrations, ERDs, missing indexes, circular foreign keys, and churn without write access.

Exposes tools that let AI coding agents browse a repo's schema snapshot of tables and columns and validate their SQL against it before running or writing it, so queries referencing invented or stale table and column names get caught and corrected up front. Provides list_tables, describe_table, search_columns, and check_sql over the same snapshot used by the CLI, hook, and CI check.

This server introspect database catalogs (PostgreSQL, MySQL, SQLite) and converts their structure into a compact, token-optimized notation. It enables AI coding assistants to efficiently analyze complex database architectures without exhausting their prompt context windows.

Provides an AI agent with read-only PostgreSQL access, enabling schema browsing, foreign-key exploration, column search across tables, capped SELECT queries, and offline data dictionary export while rejecting write operations.

Audits PostgreSQL/Supabase schemas for security issues like missing RLS, permissive policies, and sensitive data exposure during AI conversations.

Enables AI assistants to explore MySQL database schema — tables, columns, foreign keys, indexes, and relationships — through structured tools and resources, without any write access.

An MCP server that provides deep schema introspection for Supabase/Postgres, exposing tables, columns, views, enums, RLS policies, functions, and more.

A comprehensive website crawler and SEO analyzer that stores site data in a local SQLite database for AI-driven auditing. It enables users to detect technical SEO issues, broken links, and security vulnerabilities through natural language queries or terminal commands.

Database schema management MCP server for Claude Code, enabling natural language management from business requirements to complete databases.

Provides a unified MCP server to interact with multiple middleware (Loki, MySQL, Redis, RocketMQ, Elasticsearch, MongoDB) through a desktop application for connection management and configuration export.

Enables searching GitHub repositories, fetching readable web page text, and querying a local book database through MCP tool calls.

Enables AI tools to understand a database, inspect schema, and run safe SELECT queries with SQL guardrails, plus optional codebase reading.

This MCP server provides secure access to databases for AI agents, enforcing authentication, authorization, human approval, logging, and notifications to prevent dangerous actions.

Enables interaction with Plaid's financial data API to sync bank transactions and retrieve account balances with secure encrypted token storage.

Grounds a Fusion-SQL agent against Oracle Fusion schema catalog, enabling table/column search, validation, and relationship discovery.

Read-only MySQL MCP server that lets AI agents list tables, describe schemas, and run SELECT/SHOW/EXPLAIN queries with a row cap, bound to a single database for safety.

A modular monolith MCP server connecting multiple providers (Redash, PostgreSQL, GitHub) with unified permission, security, and auditing, enabling secure data access and tool execution.

A powerful Model Context Protocol (MCP) tool for exploring and managing different types of databases including PostgreSQL, MySQL, and Firestore.

A Model Context Protocol server that provides read-only access to PostgreSQL databases with enhanced multi-schema support, allowing LLMs to inspect database schemas across multiple namespaces and execute read-only queries while maintaining schema isolation.

Enables AI models to interact with MySQL databases through MCP protocol, supporting queries, table schema inspection, and data manipulation operations.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

Enables AI agents to index and search across SQLite databases and CSV files to discover table schemas and column metadata. It provides a unified MCP API for data source management and structural exploration through natural language.

Enables AI assistants to query relational databases like MySQL, PostgreSQL, and Oracle using natural-language questions, dynamically discovering schemas and generating validated read-only SQL through configurable AI providers such as Groq, Claude, and Gemini.

A read-only MCP server that provides AI coding tools with database schema structure (tables, columns, keys, relationships) without exposing row data.

Converts SQL queries between different database dialects using the sqlglot library to ensure cross-system compatibility. It allows users to list supported dialects and transpile SQL code from one syntax to another through the Model Context Protocol.

Search the fastest-growing US horse boarding directory: 6,000 facilities and 3,800 trainers across 48 states, plus boarding price data by state.

Enables LLM clients such as Cursor and Claude to discover and use generated REST services through MCP tools for create, update, and delete actions and MCP resources for list and get-by-id context. Services generated in one command are exposed simultaneously as REST endpoints and MCP tools and resources.