"Top 20 most starred MCP servers on GitHub" matching MCP servers:

An MCP server exposing every documented Email on Acid API v5 request as a tool — 24 tools across authentication, email client lists, email rendering testing, and spam testing.

Enables GitHub Copilot Agent Mode to act as a QA assistant by providing MCP tools to query and modify Bugzilla bugs, Jira issues, and Confluence pages through natural language.

Enables AI agents to start, control, and verify local open.mp/SA-MP game servers via MCP stdio, using a headless RakClient to send allowed slash commands and assert round-trip responses.

MCP server for self-hosted qTest Manager, enabling natural-language management of projects, modules, test cases, requirements, traceability, and test execution via the qTest REST API.

Enables a stateless, horizontally scaled MCP server using the 2026-07-28 specification, with tools for load testing and instance-aware operations.

Enables coding agents to verify whether a GitHub pull request is genuinely ready by checking draft state, conflicts, check results on the head commit, review requirements, merge queue status, and expected commit, returning a verdict with reasons and owners pinned to a commit and timestamp. It reports merged or closed PRs without judging them and never authorizes a merge.

Enables AI coding tools to run CheckMyLaunch scans on GitHub repos or live URLs and retrieve findings and repair prompts directly within the chat.

Local-first bug reports for coding agents: annotated screenshots, recordings and notes stored on your machine, served over MCP with the images included. Sync reports to GitHub issues when you choose.

Screen-reader navigation cost analyzer. Measures how hard it is for assistive-technology users to discover, reach, and operate interactive targets on the web.

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

Verify AI agent communication with session types and formal proofs. 4 tools: parse protocols, verify messages, check safety properties, browse 20 stdlib templates.

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.

Enables AI assistants to generate realistic, synthetic test data on demand, including valid PESELs, NIPs, addresses, and more across 27 EU countries, through two tools: list_generators and generate.

Translates a lockfile diff into a human-readable upgrade plan. For every dependency bump (npm or PyPI) returns semver class, breaking changes from GitHub release notes, CVEs fixed in the range, migration guide links, and a clear per-package recommendation. Bulk tool ranks up to 50 package changes in parallel by risk (security > caution > review > likely-safe > safe).

Enables AI assistants to summarize Playwright test runs, identify flaky tests, heuristically triage failures, generate Playwright test stubs, and retrieve recent GitHub CI status through MCP tool calls.

AI 規格大師 — MCP server bridging specs (Linear / JIRA / GitHub Issues / Notion / Markdown / Figma) to tests, with bidirectional traceability and a spec-quality coach. Sibling to mk-qa-master.

Enables automated evaluation of one or many domains in a real browser for accessibility conformance, returning one row per domain with the issues automated checks find by severity, top failing rules, sample elements, a 0–100 score, and European Accessibility Act exposure signals.

Enables LLM agents to programmatically inspect, debug, and test other MCP servers by wrapping the MCP Inspector CLI. Supports listing and calling tools, reading resources, and testing prompts on both local and remote MCP servers.

Automates the evaluation of GitHub hackathon submissions by providing tools to collect issue data, apply scoring rubrics, and generate ranking reports. It enables a multi-agent system to manage scoring consistency, statistical outlier detection, and feedback generation through the GitHub CLI.

Provides AI coding assistants with on-demand access to component specs, test scenarios, accessibility requirements, and build guides from the Web UI Component Specification.

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?'.

Prediction stability engine for AI agents. Evaluate model stability, detect ghosts, probe any LLM for instability, monitor fleet drift. 20 tools + 1 resource. Works with Claude, Cursor, VS Code.

Crash-test AI agents on real professional decisions. Agents take real tariff classification and patent examination cases, search reference libraries and rulebooks, submit a decision, and get an exact score with a receipt against what the professional actually decided. Most cases were decided after current models were trained.

Scans any website and produces an Agent Readiness Report scored on the open ASO framework.

Browser control for Claude Code, on Firefox.

An intelligent debugging assistant that automates the debugging process by analyzing bugs, injecting HTTP-based debug logs into code across multiple environments (browser, Node.js, mobile, etc.), and iteratively fixing issues based on real-time feedback.

Scores npm packages, PyPI packages and GitHub repositories 0-100 with an A-F grade and plain-language risks. Scans package.json, requirements.txt and lock files; no API key needed.

AI-powered website feedback and visual bug reporting MCP server that lets AI coding assistants access Vynix projects, annotations, and create GitHub issues with rich debugging context.

MCP server that lets AI editors execute JavaScript, read console output, and simulate clicks/input on static web pages. Supports multiple browser pages and can be deployed remotely via HTTP transport.