"Methods to store and persist memories for AI systems" matching MCP servers:

Provides AI assistants with access to the Fake Store API for e-commerce prototyping and testing, enabling queries on products, carts, and users.

Connects Claude to Apple's App Store Connect API, letting you manage apps, builds, TestFlight beta groups and testers, customer reviews and replies, sales and finance reports, and team users through natural language. Write actions such as invites, beta review submissions, and review responses require confirmation before anything is sent.

Gives AI assistants complete, spec-driven access to Apple's App Store Connect API through 1300+ tools covering the full surface — apps and versions, TestFlight, Xcode Cloud, Game Center, App Clips, in-app purchases and subscriptions, pricing, review submissions, provisioning, analytics, sales and finance reports. It lets users automate submission workflows, manage multi-account credentials, and orchestrate builds and releases across any MCP client.

Enables AI coding assistants to scan an iOS, Android, Flutter, React Native or Expo project for App Store and Google Play rejection risks, returning deterministic findings that cite the guideline section, link to the official Apple or Google page and explain how to fix each problem. Nothing leaves the machine and no AI is used in the checks.

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 management of App Store Connect and TestFlight beta testers, including adding/removing testers by email and listing apps and beta groups using an individual API key.

Zero-Config, Fully AI-Managed End-to-End Testing for all code gen platforms.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

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

Lets Claude and other AI agents work with Apple's developer API to manage app metadata, versions, review submissions, builds, TestFlight, customer reviews, reports, Xcode Cloud, devices, and team members, with optional read-only safeguards.

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.

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

Checks a site for AI crawlers: which of 11 AI crawlers its robots.txt lets in, whether its llms.txt follows llmstxt.org, and what its home page says without scripts. Findings with evidence; no scores, no model calls, no telemetry.

A licensed, locally run Playwright E2E testing MCP server for Claude Desktop and Cursor. It lets AI coding agents inspect semantic accessibility structure, validate role-based browser flows with explicit assertions, and generate reusable Playwright tests.

MCP server for measuring, tracking, scoring, and improving AI agent reliability with tools for recording interactions, scoring reliability, analyzing failures, recommending improvements, generating audit reports, and checking MCP health.

Enables AI assistants to manage Apple App Store Connect resources like apps, builds, TestFlight, and reviews through natural language.

Enables agents to work with Robot Framework by discovering tests and resources, drafting tests from requirements, dry-running and executing suites, and parsing output.xml results.

Enables agents and teams to manage versioned delivery work items, role-tagged handoffs, revision- and source-bound evidence, QA gate evaluation, and release-owner attestations through MCP tools.

Enables scanning text for policy and safety issues, generating test suite outlines, and checking the configuration/health of the evaluation setup.

MCP server for AI-powered QA analysis. It enables analyzing test failures, identifying root causes, suggesting fixes, classifying defects, detecting flaky tests, and generating test cases and bug reports.

An MCP server for validating AI-generated code through automated browser testing, evidence collection, and intelligent diagnostics.

Enables AI assistants to write and run mobile UI tests on Android and iOS simulators via natural language, supporting native and WebView apps without Appium.

A multi-task MCP server for AI code optimization and testing that integrates with VSCode/Cursor, CLI tools, and autonomous agents. It provides tools for running tests, generating code improvements, and managing objectives across different environments.

Enables AI assistants to answer QA questions in a single call, covering run reports, failure grouping by root cause, flaky versus regressed test detection, and coverage gaps. Also exposes raw TestRail API access when a question needs it.

Accessibility AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

An MCP server that generates, runs, and triages tests by introspecting Python modules or web pages, using structured LLM outputs for scenario generation and failure analysis.

A lightweight MCP server for security reviews that injects security requirements before code generation, scans dependencies for CVEs, and verifies generated code without disrupting workflow.

An MCP server for validating JSON against schemas, checking email deliverability, verifying URLs, assessing data quality, and validating API responses using RFC-compliant checks and heuristic analysis.

Enables AI assistants to interact with the Scorecard REST API for exploring endpoints, making test requests, and integrating the SDK into applications.

Broccoli turns "the agent reads a stack trace and guesses" into "the agent drives the real debugger": it sets breakpoints, steps, inspects live variables over the Debug Adapter Protocol, and proposes a fix you approve in a diff — never applied silently.