"Running queries in Apache Superset" matching MCP servers:

Enables conversational analysis of n8n workflows and Make scenarios for silent-failure risks, with tools to explain findings, compare workflow versions, and list rules.

Enables AI agents and MCP clients to drive real Chrome, Edge, Brave, and Firefox browsers through native automation protocols. It exposes tools for navigation, page snapshots, form filling, clicks, screenshots, console/network inspection, and tab management.

Enables MCP clients to open websites, capture screenshots at multiple breakpoints, and run automated design audits for issues like overflow, small tap targets, low contrast, missing alt text, tiny text, and clipped content.

Enables AI agents to inspect UI screen recordings as token-efficient image sheets with changed regions boxed, single-frame flicker flagged, and speech aligned to frames. Exposes watch_video and zoom_video tools so agents can pull dense keyframes across any time range or one sharp full-resolution frame, all processed locally.

Lets an assistant read recorded production AI agent runs — steps, model and tool calls with arguments, and outcomes — along with the findings of comparison runs that checked a prompt or model change against those recordings, and verify a signed evidence bundle offline with no account or network. It is strictly read-only: no tool starts a replay or comparison, so nothing can spend money or act without a person deciding.

MCP server for generating, validating, running, and reporting Apache JMeter API performance tests from structured API sources.

MCP server for remote debugging of Apps in Toss mini-apps, providing CDP relay and test runner capabilities.

Enables read-only analysis of FST waveform files, including signal value queries, timing measurements, event search, latency analysis, and PNG plot generation using human-readable time addressing.

MCP server for the Ghost Inspector API that lets agents inspect and manage end-to-end browser tests, offering read-only tools for inventory, module usage, and stale test analysis, plus opt-in guarded write operations.

Measures what MCP servers cost in context tokens: probes a URL or a local command now, measures a whole config file, and looks up the daily results for every server in the official MCP registry on mcpcost.ulehla.dev.

Renders HTML in a headless browser and detects layout defects numerically, such as text overlaps, placeholder leftovers, and element overflow, without requiring baseline images.

Enables agents to verify completion by cold-running an acceptance command and reporting whether it exits with code 0, returning a pass/fail receipt with output and refusal reasons.

MCP server for Seedfast, which fills PostgreSQL databases with realistic, relationally valid test data generated from live schema, providing tools for planning, running, and inspecting seeding operations.

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.

On-demand micro-mutation sandbox for AI test verification that maps weaknesses in unit tests by running isolated mutation testing via the Model Context Protocol.

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

Evaluates MCP servers by running read-only checks and returning a graded report with an A-F letter grade.

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

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.

A local-first MCP server that scores your codebase's Build Readiness by reading code and running tests on your machine, outputting a diligence-grade score and risk register without uploading your source.

Enables AI coding agents to test and automate Android apps rendering UI in OpenGL/Vulkan/Metal surfaces via screenshot-based vision tools for tapping, swiping, long-pressing, and recording, without accessibility tree dependency.

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.

Enables building and running custom LLM benchmarks with multi-judge evaluation, supporting GUI, MCP client, and CLI usage for ranked, auditable results.

Detects tests that pass no matter what the code does, revealing vacuous tests that provide false confidence in coverage.

MCP server that lets AI agents rent a real UK phone number and receive SMS/OTP verification codes directly in agentic workflows.

Enables AI agents to perform software engineering tasks inside an isolated, deterministic sandbox—exploring repositories, reproducing failures, applying patches, running tests, and verifying solutions against hidden suites through MCP tools.

Enables AI agents to simulate network failures and test application resilience in Playwright browser sessions.

Enables Codex to inspect, test, and control Android emulators through adb with strict typed tools, returning screenshots as native MCP images and keeping physical devices and Gradle execution behind explicit opt-in policies.

Lets an MCP client query SQLite databases through validated, forced read-only, row-capped, time-limited and logged operations, so AI agents can explore data without risking writes or runaway queries. It also ships an eval harness that measures how accurately a model answers benchmark questions via text-to-SQL through the server.

Enables evaluation of patent feature-separation results by listing records, checking alignment with claims and original text, and running deterministic quality gates plus a Judge audit.