"The number 555" matching MCP servers:

Virtual phone number platform for AI agents — rent numbers across 200+ countries, receive SMS, and manage the full activation lifecycle.

MCP server that lets AI agents rent a real UK phone number and receive SMS/OTP verification codes directly in agentic workflows.

Checks that every computed number in a Markdown document still matches the formula that produced it, and repairs it under an explicit write gate — so an agent's correct formula can't ship with a wrong total. Exposes every VisiMark command as a tool (check, explain, eval, infer, format), the authoring discipline as resources, and the orderings an agent gets wrong unsupplied as prompts. Read-only by

MCP server that gives an AI agent a throwaway test identity — a real disposable email address and a real UK phone number — so it can sign up for something it's testing and read back the verification email/SMS itself, without a human in the loop.

Enables any MCP client to plan and run verifiable analysis of engine hot-fire and bench test data through tools that open runs, segment phases, check sensor health, redlines, valve response and oscillations, compare simulations, verify every reported number against an evidence ledger, and write HTML reports. All findings stay traceable and reproducible from deterministic tool calls rather than raw samples.

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

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

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.

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

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 agents to convert Figma frames into self-contained HTML and then iteratively verify the rendered code in Chromium against the design using pixel diffs and element bounding-box checks until it converges.

Enables AI agents to drive live mobile and desktop browser sessions and measure web/responsive UIs directly from the DOM — computing contrast ratios, touch-target sizes, overflow, clipping, and theme drift as precise text findings tied to CSS selectors instead of screenshot guesswork. A human and the agent share the same live session, so pinned notes, navigation, taps, and device or theme switches are visible to both.

Enables AI coding agents to read point-and-talk review notes with marked screenshots, fix them by number, and report each fix back with proof so nothing is considered done until verified.

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 control a real browser through intent-based tools—reading pages, filling forms, clicking, and replaying self-healing recipes—while returning only concise answers instead of the DOM.