"An overview or guide to GitHub Actions" matching MCP servers:

Enables agents to turn a plain-language description of a device into a complete, validated build package — parts list, 3D-printable parts, wiring, firmware code, picture assembly guide, and tests — that anyone can assemble without electronics experience.

Enables turning requirements documents into RFCs, functional test scenarios, and a traceability matrix, with tools to parse, diff, and verify coverage.

Automates the conversion of Figma designs into TypeScript React components and integrates with GitHub to create pull requests for the generated code. It includes visual regression testing with Playwright and accessibility validation to ensure implementations match the original designs.

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.

Provides a testable gateway path for running a local MCP-style server in hosted-like conditions, with tenant-isolated reads, approval-denied writes, deterministic failures, and smoke-test verification.

An MCP server for n8n that gives AI agents tools for generating workflows, linting, diagnosing failed executions, and driving live n8n instances.

A stdio MCP server that audits other MCP servers by linting their tool schemas and calling tools with malformed inputs to produce a 0–100 conformance score and Markdown report.

Free JSON Schema validation, JSON to TypeScript, CSV to JSON, JSON repair and JSON to CSV for AI agents. Hosted MCP plus local STDIO. Connect once with a scoped key; enforce tool allowlists and quotas, inspect request IDs. Runnable repair → validate → CSV workflow. Bounded OpenAPI and webhook checks. No LLM calls or payments. Setup: invokeport.com/agents.

Enables MCP-compatible editors to orchestrate test runs, debug failures, analyze visual regressions, run accessibility audits, and manage test cases through natural language.

Enables agents to grade other MCP servers for LLM usability, covering descriptions, schema design, naming, token cost, and consistency, while also explaining grading rules.

Enables natural-language testing of MCP servers—covering tools, resources, prompts, contracts, and transports—without writing test code, with deterministic validation and CI integration.

Runs as an MCP server that lets an agent grade other MCP servers for agent usability, explain grading rules, and list available rules. It enables automated assessment of tool descriptions, schemas, naming, token cost, consistency, and optional live evaluation.

Automates downloading mobile game performance data from PerfDog and converts it to Tableau-ready CSV format with device statistics, FPS metrics, and time-series data.

Enables migration of test automation projects from WebDriverIO to Playwright using AST-based transformations. Provides tools for analyzing tests, converting syntax, refactoring to Page Object Model, and generating migration reports.

Enables AI agents and developers to independently verify code and documentation claims against the repository, producing evidence-backed audit reports and pull-request checks.

Provides a read-only MCP bridge that lets Claude Web inspect workspace files, git state, and recorded test results while Codex remains the sole executor of changes.

Enables MCP clients such as Claude Desktop and Claude Code to read café rules, rota, and staff data, check proposed rota changes against the owner's rules, and evaluate customer chat replies before sending. Every tool is read-only, with code checks applied first and AI judging used only when needed.

Enables agents to discover, search, compare, and inspect tested MCP tools by problem or keyword, with certification verdicts, scorecard summaries, certified scope, and explicit not-tested details.

Enables agents to inspect web pages for Cloudflare Turnstile challenges without an API key, and clear Turnstile or WAF challenges using a SolveGate API key.

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.

Free church website audit: an MCP server that checks a church homepage for mobile, speed, SEO and first-time-visitor basics.

Enables AI agents to hire real human operators for tasks requiring physical presence, human perception, or judgment, such as verification, testing, data collection, and physical-world tasks.

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.

Provides an in-memory notebook interface with tools to create, retrieve, list, update, and delete notes, designed to test agent behavior through realistic MCP tool interactions.

Enables AI agents to hire verified human operators for tasks requiring physical presence, human perception, or judgment, such as real-world verification, product testing, and data collection.

Lets an AI assistant statically scan HTML and JavaScript landing-page code that turns Meta's fbclid URL parameter into the _fbc cookie (and hand-written _fbp cookies), flagging known ways the click ID is changed, truncated, or kept from an older ad, without executing the code or contacting Meta.

Scans any website to generate an Agent Readiness Report based on the ASO framework, evaluating agent discoverability, trust, interoperability, and commerce readiness.

Lets AI agents ask which tests a Playwright or Vitest project contains, which are skipped and why, by reading the test source files statically. Nothing is executed, written, or sent over the network, and answers come back as paged JSON with summaries, filters, and scan diagnostics.

Enables AI agents to drive the 1C:Enterprise test client directly, opening forms, reading and modifying data, working with tables, and recording or replaying action scenarios. Connects to local or remote test clients over their network protocol without a testing manager.