"How to execute tests on a frontend page and debug browser console issues" matching MCP servers:

An MCP server that adds a safety layer with eight independent checks and audit logging between a language model and a broker order, supporting both on-disk simulation and live MetaTrader 5 terminals.

A minimal MCP server with get_weather and create_ticket tools, used for testing MCP servers across protocol, unit, eval, transport, and auth layers.

Enables frontend navigation and browser automation through a deterministic MCP server, integrating Browser Use and optional code graph hints for coding agents.

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

Enables triage of GitHub issues by fetching and filtering issues, checking claim status, and listing new open issues across a watch-list.

Enables AI assistants to list, search, and inspect issues on any public GitHub repository via natural language.

Exposes GitHub issue operations as tools for LLM agents, enabling listing, creating, commenting on, closing, and searching issues via natural language.

Lets agents read a GitHub repository's live issues through read-only tools for listing, filtering, fetching details with comments and cross-references, searching, and exploring labels and milestones, with transparent pagination and provenance notes.

Enables AI assistants to perform interactive Python debugging with breakpoints, step execution, and variable inspection using the Debug Adapter Protocol (DAP) through an MCP server interface.

Provides an MCP server that tracks open loops (pending decisions or replies) across email, agent sessions, and other channels, enabling agents to query what is waiting on whom.

A smart debugging agent that remembers errors, automatically diagnoses issues, and accumulates solutions for faster resolution.

Enables searching, reading, creating, and updating AIO Tests test cases in Jira from any MCP client, supporting Jira Cloud and Server/Data Center with a read-only mode.

Enables coding agents to use a real debugger (Python via debugpy) for launching, attaching, setting breakpoints, stepping through code, inspecting stack frames, and evaluating expressions through MCP tools.

Enables AI assistants to discover, filter, and triage GitHub issues across repositories, with tools for fetching issue details, listing issues by state/labels, and finding related pull requests.

A local stdio MCP server that lets AI assistants run audits of generic HTML and Shopify product pages, gathering reproducible evidence on identity, structured data, images, links, specifications, and optional browser or link checks. It returns JSON and Markdown reports that the client can interpret, while keeping automated findings separate from checks requiring human judgment.

Enables systematic investigation of VMware errors and events by correlating event timelines, ranking root-cause hypotheses, and suggesting next diagnostic steps.

Enables MCP clients to search, describe, and call roughly 180 undocumented UniFi OS/Network console API operations from a bundled OpenAPI spec, plus curated reads and typed configuration changes. Writes are off by default, require per-entity enablement, and use previews, verification, and rollback safeguards.

An MCP server that lets AI agents drive real Android apps on emulators/devices, returning screen state, logs, and screenshots after every action, and learns a navigation map of the app for efficient route-based interaction.

Enables AI agents to monitor and debug browser runtime errors, console logs, and page diagnostics in real time via a Chrome extension and local MCP server.

A read-only MCP server for Google Search Console that lets you query search performance data, sitemaps, and URL index status from any MCP client.

An MCP server that deterministically scores landing pages on conversion-critical signals and blocks ad spend on low-quality pages to prevent wasted budget.

Enables AI tools to perform full-featured embedded microcontroller debugging via pyOCD and CMSIS-DAP probes, including probe management, flashing, breakpoints, register/memory access, fault analysis, and RTT communication.

Multi-account Google Search Console MCP server enabling AI assistants to query multiple GSC accounts by name in a single session, with support for OAuth and service accounts.

Provides 8 MCP tools for frontend design: load design system, generate components, scaffold pages, review consistency, extract tokens, check WCAG 2.2 AA, test responsiveness, and export to Figma.

Enables MCP clients like Claude to query Chinese A-share market data, including K-line charts with forward/backward adjustment, limit-up and limit-down pools, per-stock fund flows, index quotes, and stock news, with automatic symbol normalization and retry handling for throttled data sources.

Enables AI agents to directly inspect and debug embedded hardware: reading/writing serial ports and bus devices, auto-detecting baud rates, parsing Modbus/NMEA/custom binary frames, plus diagnosing failures through a 45-rule fault-pattern library, error-code tables, and compile/flash error translation. Also provides pin-conflict checking, register and Cortex-M fault decoding, pre-validated driver and component selection libraries, board knowledge, and guarded flashing with post-flash byte-level verification.

Provides A-share (Chinese stock market) quantitative analysis through tools for stock screening, northbound capital flow tracking, dragon-tiger list analysis, margin trading, sector analysis, technical indicators, IPO info, and limit-up/down statistics using akshare data.

Enables policy-gated control of Hyper-V virtual machines on Windows through a single local stdio server, covering VM inventory, power, checkpointing, PowerShell Direct guest diagnostics and file transfer, synthetic keyboard/mouse console input, serial consoles, ISO media mounting, and serial WinDbg preparation. Every mutation requires an explicit VM allowlist and per-capability flag, with read-only operation as the default.

Frontend Design Loop MCP enables coding agents to improve web page designs through screenshot-grounded iteration and proof artifacts, making pages materially better.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.