"Natural language interface for PostgreSQL database querying" matching MCP servers:

Lets developers and MCP agents run deterministic local HTML audits, turning inline HTML into structured findings for missing labels, unnamed buttons, skipped headings, ambiguous links, duplicate IDs, and missing landmarks. It also exposes a rule list and returns stable, actionable reports without external API keys.

This server automatically validates consistency between AI-generated frontend and backend code by enforcing OpenAPI 3.0 specifications. It injects smart constraints into AI prompts to ensure that generated data structures and API calls remain synchronized across the entire stack.

Runs a language server and provides tools for communicating with it. Language servers excel at tasks that LLMs often struggle with, such as precisely understanding types, understanding relationships, and providing accurate symbol references.

Enables AI coding agents to interact with TypeScript projects through compiler-level code intelligence, providing tools for navigation, type information, diagnostics, refactoring, and semantic search.

TypeScript-based MCP server designed to enhance code editing experiences by providing features such as hover information, code completion, and diagnostics.

Enables Codex to read, write, and design windows for E-language (易语言) programs using official IDE APIs, allowing natural language control of development workflows.

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.

Exposes VSCode's Language Server Protocol features through MCP, enabling AI assistants to perform language-aware operations like symbol navigation, reference tracking, safe renaming, type information retrieval, and hover documentation across codebases.

Enables LLM-powered agents to generate, execute, and analyze Alloy modeling language code for software modeling and formal verification. Provides tools to run Alloy models, access documentation and examples, and generate models from system descriptions.

A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

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.

Enables intelligent image analysis using GLM-4.5V model, specializing in extracting and analyzing code from screenshots with support for file paths and clipboard input.

Provides AI agents with ground-truth knowledge of Strapi projects by reading real schema files, enabling accurate queries and safe refactoring operations.

Enables semantic code search across multi-language codebases using natural language queries, integrated with Qdrant vector database for fast, cached retrieval.

Enables MCP-compatible AI clients to inspect Godot project and editor state, observe opted-in running scenes, manage processes, and apply permission-scoped guarded edits. It starts read-only and exposes additional capabilities only through explicit command-line flags.

Uses Claude as an independent second-model reviewer inside Codex, performing reviews on disposable Git snapshots with structured findings.

Enables Claude Code to leverage OpenAI models for expert code review, deep architecture analysis, and security audits, with automatic markdown report generation.

Provides LLMs with comprehensive knowledge about the V programming language, including documentation access, code examples, standard library reference, and syntax explanations to help users learn and work with V.