"A local tool for counting characters in text" matching MCP servers:

Enables MCP clients to open websites, capture screenshots at multiple breakpoints, and run automated design audits for issues like overflow, small tap targets, low contrast, missing alt text, tiny text, and clipped content.

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 AI agents and MCP clients to drive real Chrome, Edge, Brave, and Firefox browsers through native automation protocols. It exposes tools for navigation, page snapshots, form filling, clicks, screenshots, console/network inspection, and tab management.

Audits MCP tool descriptions for quality and reliability, scoring them 0-100, detecting smells, and providing rewritten versions for better agent accuracy.

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 AI agents to inspect UI screen recordings as token-efficient image sheets with changed regions boxed, single-frame flicker flagged, and speech aligned to frames. Exposes watch_video and zoom_video tools so agents can pull dense keyframes across any time range or one sharp full-resolution frame, all processed locally.

Protects AI agents from bad tool outputs, schema mismatches, and tool poisoning by validating, sanitizing, and scoring reliability of tool responses.

Guarded, profile-driven Charles Proxy automation for macOS and Android testing. Uses immutable TOML profiles and explicit plan/apply confirmation.

Enables verification of deployment-scoped model-visible DSH tool surface conformance by checking recorded tool identities and schemas against approved locks, reporting only drift categories and hashes.

Analyzes multi-step AI agent tool chains to compute success probability, identify bottlenecks, and suggest better execution orders, enabling more reliable agents via local pure-math computation.

An MCP Server that provides access to Google's Cloud Tool Results API, enabling applications to programmatically interact with test results from Firebase Test Lab and mobile app testing through natural language.

A lightweight multi-provider MCP testing fixture with two providers (eva_air and uk_railway), each exposing 5 tools using in-memory fake data, designed for verifying MCP client tool discovery, tool calls, and multi-provider routing.

This MCP server verifies that an agent’s claimed tool output matches the actual response returned by a tool to prevent invented or distorted results. It flags mismatches, omissions, and invented fields to ensure downstream logic only processes verified tool data.

A local MCP server that connects Claude Desktop, Claude Code, and Claude Chat to your Azure DevOps organization, enabling querying work items, reviewing pull requests, triggering pipelines, searching code, managing test plans, and updating wikis using plain language.

Enables measuring DOM elements and capturing screenshots in a real local Chrome browser over the DevTools Protocol, with in-page login so httpOnly cookies apply and overlay-masking before capture. It removes common Chrome automation traps such as sandbox kills, WebSocket origin rejection, and Retina pixel scaling, with no npm or Python dependencies beyond the MCP SDK.

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.

MITM proxy MCP server that intercepts and verifies AI agent tool calls, detecting fabrication, tracking costs, verifying outcomes, and inferring user satisfaction.

A multi-language testing automation server that enables AI assistants to discover, plan, and execute tests across six major programming languages. It provides comprehensive tools for repository scanning, automated test execution, and detailed coverage reporting.

Validates text accessibility (contrast, spacing, language) against WCAG 2.1 criteria via modular MCP tools.