"A guide to conducting market research" 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.

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.

Enables capturing web evidence, freezing content-addressed snapshots, and comparing research agents on the same sources with traceable access and quotations.

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 deliverable conformance and evidence-chain checks by turning requirements into executable specs, validating numbers against a provenance ledger, and auditing PDF/OOXML metadata and archive manifests.

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.

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.

Run Semgrep static analysis from an AI agent. OWASP top 10, secrets detection, custom rule packs, baseline scanning. Curated by Archimedes Market with a verified Trust Report.

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.

Enables AI-powered document analysis and querying for project documentation using vector embeddings stored in Redis. Supports document upload, context-aware Q\&A, automatic test case generation, and requirements traceability through OpenAI integration.

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.

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.

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.

A shared, concurrency-safe ledger for LLM code audits. It enables multiple agents to collaboratively report, verify, and resolve bugs with deduplication and hallucination resistance.

Give AI agents 10 offline tools for market observations, repeated headlines, forecast evaluation, correlation risk and statistical checks. Preserve source clocks, missing data and stated assumptions. Python, CLI and MCP share the same zero-dependency core; no feed collection or trade execution.

A read-only MCP server that exposes Zephyr Scale Cloud test data to review a Jira story's test coverage, answering whether tests are adequate and passing.

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).

An MCP server that manages a pool of test accounts, leasing them out one at a time to prevent concurrent session collisions, with automatic reclamation of expired leases.

An MCP server that grades prompts against a validated rubric, tracks real outcomes, and provides guidance grounded in research on what predicts good results.

Enables LLMs to read existing PageSnap session packs and map locators to Playwright, Selenium, or Cypress without capturing or opening a browser.

A stdio MCP server providing AI agents with a stable tool interface to read and write TCM test cases through REST, including search, CRUD operations, and a dry-run-to-commit safety flow.

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.

Connects Claude to a live Chrome browser's accessibility tree to generate stable, framework-agnostic test selectors and perform accessibility audits. It enables users to read element roles and states exactly as a screen reader would to help write, debug, and migrate test suites using natural language.

Provides an LLM with a real Chromium browser to perform web tasks, recording every action into a structured trace for later verification of goal completion.