"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.

Runs SQL statements in memory against real PostgreSQL 18 and SQLite 3.49 engines after loading your schema and sample rows, returning each statement's own verdict: errors with line, column, and hints, constraint violations, or the resulting rows. It also compares both dialects to expose portability differences, all with no database server, network, or API key.

VAST validation MCP server that checks ad tags against IAB VAST specifications, returning structured JSON with rule IDs, XPath locations, and spec references.

Enables chat assistants to insert graded coding exercises (Python, JavaScript, TypeScript, SQL) with hidden tests, and returns failed attempts to the conversation so the tutor can explain the learner's specific mistake.

An MCP server that gives coding agents hands and eyes on an Android device, providing 19 tools for building, testing, installing, UI inspection, input, logs, and toolchain diagnosis. It returns concise, structured results to make the build-debug loop efficient.

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

MCP server that exposes Dira ProSuite quality verification to AI assistants, enabling data quality checks on geospatial datasets through natural language.

MCP server for managing test cases, cycles, and results in Zephyr Scale on self-hosted Jira. Enables AI agents to create, search, update, and delete test artifacts through natural language.

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.

Enables AI coding agents to perform real-browser accessibility scanning of localhost pages using Playwright and axe-core, returning WCAG 2.1 violations with structured fix plans.

Run the requests in a Postman collection folder and get structured, assertion-level results back straight from your AI assistant.

Umbra is the trust layer for AI-generated code. It scores any repo 0-100 with file:line evidence (security, slop, Docker-verified build/boot, and claim receipts that catch agents lying about tests), and guards agent file writes mid-stream blocking leaked keys, alg:none JWTs, and git-hook plants before they land. Tools: scan_repo, guard_content, get_score.

Audits Excel workbooks by tracing cell dependencies and detecting circular references, volatile functions, and other formula risks, enabling natural-language audit queries on local files.

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?'.

An MCP server that exposes Swarm's fact reconciliation to AI agents, allowing them to query scope, evidence gaps, and review requirements without being able to issue a final verdict.

Generates realistic, referentially-coherent test data (SQL INSERTs, JSON, or CSV) from your database schema, resolving foreign keys and respecting constraints. Paste CREATE TABLE DDL or a JSON schema and get ready-to-run seed data with valid relationships.

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.

Crawls and grades MCP servers deterministically, providing a registry, leaderboard, and API to query server grades and submit feedback.

Enables coding agents to independently verify web changes by scanning pages, inspecting UI structure, generating Playwright reproductions, and executing tests with structured QA evidence.

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