"A tool for PostgreSQL database querying and schema inspection" matching MCP servers:

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.

Local MCP tool for understanding JSON Schema files while planning tests, summarizing types, required fields, constraints, and generating placeholder paths without copying data.

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.

Validates schema files against customizable lint rules using Claude or Gemini AI, supporting JSON and SQL schemas with rules for naming, structure, and migration safety.

A MCP server that exposes GraphQL schema information to LLMs like Claude. This server allows an LLM to explore and understand large GraphQL schemas through a set of specialized tools, without needing to load the whole schema into the context

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.

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.

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.

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

Scores MCP tool definitions and tool lists from 0-100, flagging vague descriptions, missing parameter docs, non-verb-first naming, oversized enums, and nested schemas with severity, rationale, and concrete fixes. It also validates marketplace listings against platform character caps such as MCPize's 500-character short-description limit before deploy.

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.

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

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.

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.

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

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.