"Information about PostgreSQL Database" matching MCP servers:

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.

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

Enables querying any GitHub, GitLab, or Bitbucket repository and getting AI-generated answers about the codebase, powered by Gemini.

Enables asking natural-language questions about any GitHub repository and receiving answers grounded in the actual code, with read-only enforcement and automatic repository fetching.

truth is a deterministic fact-checker for the claims an AI coding agent makes about its own work.

Semantic git queries via MCP. Beyond git log — answer who/what/why about any line, file, or branch with blame, co-change, PR linkage.

MCP server that provides npm package information for AI agents during TypeScript development.

Extracts deterministic architecture maps from codebases for AI agents, enabling queries about blast radius, routes, security findings, and production readiness without sending code anywhere.

Blocks unsafe PostgreSQL migrations before an AI agent writes or runs them. check_before_apply returns a pass/fail gate; reads the real Postgres parser, classifies the lock each statement takes, checks 112 safety rules. Runs offline, no database required.

Enables AI agents to search and retrieve details about Odoo code elements (models, fields, views, etc.) with exact file locations using MCP tools.

An MCP server that catches dangerous SQL migrations by analyzing PostgreSQL statements for locking risks and providing safe rewrites.

Provides coding agents with a compact map of a TypeScript/TSX codebase, enabling direct answers about symbol locations, imports, dependencies, and references while reducing token usage.

A mcp server to allow LLMS gain context about shadcn ui component structure,usage and installation

Enables storing and querying structured information about software code entities (classes, functions, files) and their relationships (calls, imports) along with qualitative observations like design decisions and change rationale.

Exposes Lachesis's code navigation tools over MCP, letting LLM agents ask precise compiler-level questions about dataflow, taint, callers, and guards in source code.

Enables AI coding agents to perform deterministic database architecture audits and performance engineering for PostgreSQL and MySQL, covering migration analysis with schema health scoring, ESR-based composite index recommendations, N+1 query detection, EXPLAIN plan diagnosis, transaction and deadlock analysis, partitioning and archival design, and capacity or configuration tuning. It also generates phased Expand & Contract runbooks that turn blocking DDL into zero-downtime production migrations.

Enables interaction with PostgreSQL databases through comprehensive database management tools including index tuning, query execution plans, health checks, schema intelligence, and safe SQL execution with configurable read-only mode for production use.