"A tool that can connect to MySQL database, understand table structure and query related data" matching MCP servers:

Enables AI assistants to deeply understand codebases via Knowledge Graphs, supporting fuzzy search, architecture layer queries, call chain tracing, impact analysis, and domain knowledge with multi-project support.

This MCP Server bridges Egonex-AI/Understand-Anything with Claude Desktop and other MCP clients, giving LLMs native access to full-codebase structural graphs, architecture analysis, and CI/CD validation.

Semantic React/TSX analysis MCP server that saves 70-90% tokens by using AST to retrieve precise component usages, prop flow, and state update information for AI coding assistants.

Enables secure read-only querying of multiple database types (MySQL, PostgreSQL, MSSQL, Oracle) through natural language. Automatically reads database configuration from project files and blocks any data modification operations for safety.

A tool discovery MCP server that integrates with Azure DevOps wikis and code-graph-rag to match natural language goals to tools, enabling tool composition and proxy testing.

Bridges codebase structural analysis, architectural rules, and CI/CD validation with MCP clients, enabling LLMs to check blast radius and prevent breaking changes.

Enables comprehensive MySQL database management including CRUD operations, schema queries, and natural language to SQL conversion support through complete database structure analysis.

Enables AI agents to format SQL, explain queries in plain English, analyze schemas, build queries from natural language, and generate migrations, all without requiring a database connection.

Offline PostgreSQL diagnostics: reviews SQL, risky migrations, candidate indexes and EXPLAIN JSON plans without database credentials or executing statements.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

A Model Context Protocol server that enables natural language interaction with the Coverity Connect static analysis platform, allowing users to manage projects, analyze snapshots, and generate security reports through AI-powered interfaces.

Reviews MySQL migrations, queries and application code before they run, flagging table locks, full table copies, data loss, missing indexes, integer overflow and SQL injection, with a safe rewrite for each finding. Runs locally; your SQL never leaves your machine.

Enables AI assistants to leverage Qwen's code analysis capabilities with large context windows, supporting file/directory analysis, sandbox execution, and multiple approval modes for safe code operations.

Enables AI agents to deterministically inspect, author, convert, validate, and diagnose Classical CAN and CAN FD databases and trace logs, including bit-layout validation, template generation, trace aggregation, ISO-TP/UDS reassembly, bus-health analysis, and reverse engineering.

Integrates the Atlassian Rovo Dev CLI with the Model Context Protocol, allowing AI assistants to perform deep code analysis using Rovo Dev's large context capabilities. It enables features like repository-wide queries, file-specific analysis, and specialized coding modes through a standard MCP interface.

A production-ready MCP server that provides comprehensive dbt project quality assessment for any GitHub repository, enabling AI agents to analyze dbt models, check metadata coverage, and map data lineage.

A runtime-free MCP server that converts source code into AST🌲, regardless of language.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Analyzes SQL queries for performance issues, provides optimization suggestions with automated rewriting, and recommends indexes across multiple database dialects (PostgreSQL, MySQL, Oracle, SQL Server).

Enables teams to structure metric definitions, compare semantic differences, detect JOIN fanout and drift, reconcile mismatched numbers layer by layer, and persist metric contracts as YAML.

Enables AI agents to run deterministic database intelligence tasks including natural-language-to-SQL synthesis, AST SQL auditing and optimization, schema migration diffing, SQL transpilation, index and normalization advice, PII scrubbing, fixture generation, connection-pool sizing, isolation-hazard auditing, and ORM model compilation over Streamable HTTP or stdio.

A Model Context Protocol server that extracts embedded data (such as i18n translations or key/value configurations) from TypeScript/JavaScript source code into structured JSON configuration files.

Analyzes source code across multiple languages to extract structural elements like classes, functions, and parameters using tree-sitter. It provides LLM-optimized markdown output that includes nesting levels, line numbers, and signatures to facilitate codebase navigation.

Provides comprehensive MySQL database operations including CRUD, performance optimization, health analysis, and anomaly detection. Supports multiple connection modes, OAuth2.0 authentication, and role-based permissions for database management through natural language.

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

CodeGuard MCP is a real-time AI code security scanning tool used to detect vulnerabilities, keys, and compliance issues in AI-generated code, and is suitable for code security reviews in development environments

Enables automated migration of Vue projects to React with intelligent analysis, task management, and learning from user modifications.

Enables comprehensive MySQL database operations including cross-database queries, performance analysis, health monitoring, and AI-assisted database management with role-based access control.

Enables binary comparison capabilities by leveraging IDA Pro and BinDiff to analyze similarities and differences between files. Users can perform automated function analysis to identify changed functions and compare original binaries against patched versions.

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