"Information about SQL (Structured Query Language)" matching MCP servers:

MCP server that integrates sql-sop SQL linter into LLM clients, enabling linting SQL queries and listing lint rules via chat tools.

A universal MCP server that dynamically generates and simulates actions for any query, maintaining state between sessions.

Static security linter for MCP servers. Scans tool definitions for vulnerabilities (path traversal, SQL injection, SSRF), scores description quality, and auto-rewrites descriptions for safer agent tool selection.

MCP server that lets Claude diagnose failed GitHub Actions runs by fetching and parsing CI logs into structured failure signals, enabling natural-language questions like 'Why did the last run fail?'.

Generates synthetic time-series test data with configurable trend, seasonality, noise, anomalies, and multiple correlated streams, outputting JSON, CSV, or SQL.

Turns natural-language API descriptions into runnable k6 load tests, executes them, and returns structured performance metrics for AI-assisted reporting.

Connects AI coding assistants to TestCollab for managing test cases, plans, and suites directly through natural language. It enables users to create, update, and query testing resources within integrated development environments and AI chat clients.

An MCP server that turns Zod schemas into mocks, violations, and contract tests, enabling AI agents to reason about API contracts without manually crafting payloads.

Automated Playwright E2E test repair powered by a self-improving, governed MCP server that runs failing tests, collects failure artifacts, reasons about root causes, validates and applies fixes, and re-runs to verify.

Enables AI agents to run reusable Playwright test fixtures against live deployments, providing structured test results, screenshots, and assertions.

MCP server that generates ISO/IEC/IEEE 29119-3 compliant test plan drafts from project information, providing a structured resource for the standard's test plan outline and a tool for draft creation.

Provides structured access to iOS Simulator management via xcrun simctl commands, enabling device, app, media, and testing operations through natural language.

Allows LLM agents to query Playwright JSON test results for run summaries and failure information.

Enables coding agents to run Playwright e2e tests, validate Supabase RLS policies with role-based SQL, typecheck TypeScript, execute npm scripts with parsed test output, and validate Next.js builds, all through a structured MCP interface.

Validates AI-generated artifacts (JSON, API responses, SQL) against a contract and returns a verdict.

Local MCP server for querying VCD waveform files via SQLite; enables AI agents to ask precise questions about signal values, transitions, and clock cycles without dumping raw VCD text.

Enables defect management on the SEPP platform, allowing users to query defects, retrieve user project information, and set up automated monitoring with alerts for new or unresolved defects via webhook or email.

Enables AI assistants to analyze and inspect RenderDoc capture files, providing tools to examine draw calls, textures, buffers, and shader information. It allows developers to perform graphics debugging and resource analysis through natural language interactions.

Enables RTL simulation and hardware verification with Verilator through automatic testbench generation, natural language queries about simulations, waveform analysis, and protocol-aware testing for Verilog/SystemVerilog designs.

Enables AI coding tools to query and validate analytics event specifications maintained as Wiki markdown tables, providing structured access to events, properties, and implementation details through MCP.