"The dio-odi-mcp server" matching MCP servers:

Enables local validation, comparison, summarization, and explanation of HIPAA X12 834 benefit enrollment files with PII masked, plus Workday Cloud Connect for Benefits 834 V2 setup guidance.

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 stable, side-effect-free MCP tool contract that enables AI workflows to be prototyped, demoed, tested, or dry-run without connecting to databases, APIs, files, or other real data sources. It enables swapping in a real data server later without changing the AI-facing interface.

Enables to interact with Jira AIO Test Case Management System, allowing retrieval of test cases, projects, folders, and search functionality.

MCP server that enables AI agents to generate, verify, and set up Starship configurations for the Hyperweb platform.

Conformance test harness for Model Context Protocol servers, validating JSON-RPC, transport, capability, schema, and more across multiple spec versions.

A Model Context Protocol server for Hackle API providing tools and resources for querying A/B Test data.

A simple server implementing the Model Context Protocol (MCP) that echoes messages back, designed for testing MCP clients.

Enables AI coding agents to sniff a deployed app's homepage and receive a free Sniff Score out of 100, a verdict, structured findings, and a paste-ready fix prompt, plus retrieval of earlier results without spending a new sniff. It also reports what paid Smoke and Deep runs would add beyond the free homepage check.

Enables AI agents to run evidence-based technical SEO, AEO, LLMO and GEO checks on public pages, fix the issues found, and verify the fixes by re-running the same checks.

Enables mobile device management, app upload, automation session execution, and test result viewing through the Kobiton platform, integrated with AI coding assistants.

Lets an AI agent add websites, set up and tune uptime, user-flow, security, speed, SEO, domain and compliance monitors, run scans, and review results. It also explains what broke in a failed run and proposes fixes the agent can apply with the user.

A lightweight Python-based microservice that provides simple echo functionality, receiving messages and returning them back to the client for diagnostic and testing purposes within the MCP framework.

Enables AI assistants to run inbox placement tests by handing over seed addresses from live mailboxes at Gmail, Outlook, Yahoo and 30+ other providers, then reporting which messages reached the inbox, which hit spam, and what to fix first.

MCP server for the BuildPulse Platform API. Lets AI agents surface flaky tests, CI run history, and coverage health.

Enables AI coding agents such as Cursor and Claude Code to browse KaDeep projects, suites, test cases, runs, jobs and defects, run end-to-end tests, and check localization quality directly as tools. It exposes 14 tools over stdio so agents can answer questions like which smoke tests fail and why, or trigger the checkout tests themselves.

Connects MCP clients such as Claude Code, Cursor and VS Code to a hosted QA service so the assistant can start and monitor test runs on a web app, explore its pages and flows, and read the bugs those runs uncover. Access is scoped by API key permissions, letting read-only keys list projects and issues while write-enabled keys trigger or stop runs.

Enables searching, reading, creating, and updating AIO Tests test cases in Jira from any MCP client, supporting Jira Cloud and Server/Data Center with a read-only mode.

Enables agents to read and create feature specs, track coverage and status, and generate pytest test skeletons from specs without leaving the conversation.

Enables users to connect an AI agent to a deliberately hostile MCP server, run trigger prompts, and score whether the agent falls for tool poisoning, prompt injection, and rug-pull attacks, with canary-leak detection and CI-friendly reports.

Connects AI applications to Trunk Flaky Tests for root cause analysis of flaky tests and setup of test result uploads.

Enables AI agents to operate and view the Vega Virtual Device through MCP: press remote keys, take screenshots, record video with sound, wait for screen changes, and check the TV safe area.

An MCP server that runs a quality gate on generated code, executing it in a sandbox and scoring it before returning the code to the user.

Enables AI assistants to validate JSON-LD structured data against the Schema.org vocabulary through a remote MCP tool, without fetching URLs.

Enables AI agents to read sanitized test context, captured requests, rules, and logs from the InterceptPilot Chrome extension, and to propose or run actions such as enabling mocks, importing collections, or capturing tabs, all locally over a secure WebSocket.

Enables AI agents to run live mobile and desktop browser sessions side by side and measure real UI properties — contrast ratios, touch-target sizes, overflow, clipped content and light/dark theme drift — returning precise findings as text with the offending selector attached instead of leaving the model to guess from a screenshot. It also drives the page and shares one live panel with the human, who can pin notes and frames that the agent reads back.

Enables an AI agent and a human to share the same live, URL-synced mobile and desktop browser sessions, where the agent can navigate, tap, type and switch device/theme profiles while getting measured accessibility findings (contrast ratios, undersized touch targets, clipped or unreachable controls, dark-mode drift) returned as text tied to exact selectors. It also lets the human pin a note plus the matching frame in a shared panel for the agent to read back.

Enables AI agents to prove that previously working behavior still works after code changes by running the product through the same steps twice and surfacing only unintended differences as actionable findings.

Enables AI agents to drive live mobile and desktop browser sessions side by side and measure web/responsive UIs with a real engine, returning contrast ratios, touch-target sizes, overflow and theme-drift findings as precise text tied to selectors instead of screenshots. Humans and agents share the same live panel, where a human can pin a bug with a note and the agent reads that note plus the exact frame.

Enables Windows UI Automation through MCP, allowing agents to inspect, search, navigate, and interact with desktop UI elements via the UIAutomation framework. Supports actions such as focus, invoke, set-value, toggle, and event waiting, with CLI and VS Code extension variants.

Enables AI agents to autonomously interact with, test, click buttons on, and verify Telegram bots end-to-end via the MTProto protocol.

Provides a safe paper-trading twin of the Binance Agent OS MCP API so agents can be rehearsed, scored, gated for go-live, and shadow-compared against live calls without using real funds.

Automatically generates and maintains Bruno API test collections for CRUD JSON APIs. Developers describe endpoint changes and the server creates ready-to-run test suites with environment-driven configuration.

It enables AI agents to call real human reviewers for second opinions and judgment on design, wording, and artifacts. Reviewers return pinned comments and a verdict so the agent can iterate until approved.

Enables coding agents to control and inspect a live Chrome browser for reliable automation, in-depth debugging, and performance analysis via Chrome DevTools.

Enables AI agents to compare database tables using read-only tools, with credentials managed locally and never exposed to the model.

Magga lets coding agents prove their changes before claiming they’re done by building the code and verifying that newly added tests fail before the fix and pass after it. It returns evidence-backed verdicts through the verify_change tool and supports 16 languages, including Rust, Go, Python, Solidity, and C/C++.

MCP server to debug Telegram bots by controlling your Telegram user session over MTProto. It enables sending messages, reading chats, handling updates, and invoking raw Telegram API methods.

Enables an AI agent to drive live mobile and desktop browser sessions of a web or responsive UI and receive measured findings as text — contrast ratios, undersized touch targets, overflow, clipping and theme drift — instead of guessing from screenshots. It also gives the human and the agent one shared live panel, where pinned notes and frames are read back by the agent.

MCP Server for Adversarial Co-Generation Engine Generates code and adversarial attacks from the same specification, at the same time — before a commit exists.