"The Movie Database" matching MCP servers:

Enables AI agents to submit npm, PyPI, Go, or Maven packages and manifests to the free OSV.dev database and receive per-package and per-advisory results with CVE mappings, CVSS scores, severities, and the versions that fix each issue. It also supports filtering by minimum severity, de-duplicating alias advisories, and machine-readable error/warning rows for CI gates and upgrade recommendations.

Connects AI agents to Minecraft servers via RCON to execute commands, monitor logs, and perform read-only SQLite database queries. It is specifically designed to facilitate AI-assisted plugin development, live debugging, and automated testing workflows.

Generate realistic relational test data with 156 field types, 22 locales, and foreign key integrity. One API call seeds your entire database.

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.

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.

Automatically scans project dependencies (npm, Composer) for security vulnerabilities using the OSV.dev database, providing real-time alerts and detailed remediation guidance directly in your IDE.

Enables AI assistants to perform QC Database tasks such as uploading records, managing project turnover packages, and signing off on inspections via natural language.

Enables AI agents to discover Robot Framework keywords, execute test steps live against web, mobile, API, database, or desktop targets, and generate clean .robot test suites from plain-English instructions.

Enables AI clients to drive a UI-testing toolbox with 35 tools, including a headless Playwright runner, live Chromium browser with screenshots, test management, and read-only database queries, all through the Model Context Protocol.

Enables interaction with Metasploit Framework for authorized security testing, including exploit searches, payload management, network scanning with nmap, and database operations for penetration testing workflows.

Enables local engineering workflow management by consolidating tickets, QA evidence, time tracking, root cause investigation, knowledge, and reporting into a single SQLite database, allowing generation of complete ticket packages for handoffs, dailies, or career evidence.

Generates realistic mock data using Faker.js for database seeding, API testing, and development environments. Supports person/company data, custom patterns, multi-locale generation, and structured datasets with referential integrity.

A simple server implementing the Model Context Protocol (MCP) that echoes messages back, designed for testing MCP clients.

BlueMouse is the "Prefrontal Cortex" for LLMs. It uses a 180k+ failure pattern database to validate code logic before execution, acting as a rigorous Quality Gate to prevent hallucinations and unsafe operations.

Enables mobile device management, app upload, automation session execution, and test result viewing through the Kobiton platform, integrated with AI coding assistants.

A lightweight Python-based microservice that provides simple echo functionality, receiving messages and returning them back to the client for diagnostic and testing purposes within the MCP framework.

Enables AI assistants to run inbox placement tests by handing over seed addresses from live mailboxes at Gmail, Outlook, Yahoo and 30+ other providers, then reporting which messages reached the inbox, which hit spam, and what to fix first.

MCP server for the BuildPulse Platform API. Lets AI agents surface flaky tests, CI run history, and coverage health.

Enables AI coding agents such as Cursor and Claude Code to browse KaDeep projects, suites, test cases, runs, jobs and defects, run end-to-end tests, and check localization quality directly as tools. It exposes 14 tools over stdio so agents can answer questions like which smoke tests fail and why, or trigger the checkout tests themselves.

Enables agents to read and create feature specs, track coverage and status, and generate pytest test skeletons from specs without leaving the conversation.