"Step-by-step guide to breaking down a request into parts" matching MCP servers:

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

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.

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.

Provides AI agents with deep visibility into a running web page's UI by capturing DOM, styles, and screenshots through a lightweight bookmarklet. It facilitates design-to-code comparisons, accessibility audits, and automated CSS debugging directly within an IDE.

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.

MCP-first A/B testing server that enables agents to manage experiments (create, update traffic splits, read results, apply winning variants) from tools like Claude Code, with self-hosted Cloudflare backend.

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.

A Bun-based MCP server providing a persistent HTTP request toolset for testing and inspecting JSON APIs. It supports session-aware operations, including cookie persistence, automatic bearer token reuse, and configurable base URLs.

Enables AI coding assistants to validate HTML/CSS markup using W3C APIs, perform technical SEO audits, check broken links, and validate JSON-LD schemas directly in local workspaces.

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.

Generates a pytest suite from acceptance criteria withheld from the coding agent, so the tests can disagree with the code; qikly_run never returns the criteria. The CLI also scores an existing suite by planting faults, and ships as an agent Skill (qikly --install-skill). Runs locally (uvx --from "qikly[mcp]" qikly-mcp): your code and API key stay on your machine.

Turns AI coding agents into senior QA engineers by generating black-box test matrices, manual test plans, UI/UX checklists, Page Object Model automation, API contract tests, and STLC strategies, plus sandboxed local test execution and defect triage from raw logs. Eight tools cover exploratory charters, WCAG audits, and Jira-ready bug reports, all with injection-proof command handling.

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.

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).

Zero-dependency MCP server and CLI that proxies, inspects, and analyzes JSON-RPC message streams between MCP clients and servers.

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 MCP-capable clients to look up DDEX ERN 3.8.2 structure, element and attribute semantics, documented child sequences, AVS values, and step-by-step composition guides. It also performs offline XSD validation of ERN XML and package checks for delivery conventions such as BatchComplete, relative URLs, DeliveryType, and message MD5.

Guides users through creating professional Playwright test suites with a step-by-step wizard workflow, including analysis, planning, setup, and implementation.

Enables AI coding assistants to inspect GitHub Actions CI runs, diagnose failures with failed-step summaries and filtered job logs, read per-job coverage, and view pull request checks through read-only, allowlisted access.

Enables comprehensive test management in Zephyr Scale Cloud, including creating and managing test cases, executing tests with step-by-step results, organizing test cycles and plans, and performing advanced JQL searches.

An MCP server that guides QA and verification processes by breaking down tasks into manageable steps and providing LLM-driven, confidence-scored tool recommendations.

Exposes VS Code's Debug Adapter Protocol as MCP tools, enabling AI coding agents to set breakpoints, step through code, inspect variables, and read exceptions in a real debug session.

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 planning an ordered dependency upgrade path from caller-supplied release facts, returning the intermediate versions, the breaking changes each step introduces, and a verdict for the whole path. It also reports how many major boundaries are crossed and whether the chain actually reaches the target version.

Enables AI coding agents to snapshot workspace states, binary-search recorded trajectory steps, rewind to a prior good step, and retrieve per-step diffs for autonomous regression debugging. It supports self-healing debugging workflows through MCP tools.

Enables MCP clients to run autonomous game playtesting, evaluate the agent against seeded bugs, list bug flags, and interactively reset, step, and view game sessions.

Provides a central gateway to 170+ offline mock MCP servers with deterministic fixture-based responses and per-server SQLite state, enabling realistic credential-free agent trajectory testing and multi-step workflow rehearsal.

Lets a local AI agent scan a repository to map user flows against their Playwright end-to-end coverage, stand up and tear down a Docker-based local test environment, and write or run the missing specs. It also embeds video, trace, and step-list evidence into a local viewer synced to the flow graph.