"A server for SSE (Server-Sent Events) integration with Figma" matching MCP servers:

Enables AI agents to drive a headless browser to a Storybook story and capture every custom event a component dispatches with zero registration, while flagging shared, retargeted, undocumented, and not-composed events. It also lets agents dispatch synthetic events at the rendered component to verify it responds as documented.

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 compare a live web page against a Figma frame and receive a bounded JSON verdict of design deviations, without sending screenshots or mockups through the model context.

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.

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.

Compares Figma frames to live pages, checking colors, fonts, and border radii, and generates a shareable HTML report.

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.

A mock MCP server for testing MCP client implementations and development workflows. Supports tools, prompts, and resources across multiple transport protocols (stdio, HTTP, SSE).

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

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 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.

A powerful MCP server for automated JMeter test generation and execution with Docker integration and comprehensive performance analysis.

Exports Figma designs as ready-to-use HTML/CSS and validates pixel-perfect accuracy with image comparison and visual regression testing.

A lightweight MCP test server for verifying client connectivity, providing tools, resources, and prompts for integration.

A standardized MCP server designed for testing integration with the Des MCP Server Testing API. It allows AI agents to interact with testing endpoints using tools implemented via the Model Context Protocol.

Official MCP server for Qase Test Management Platform. Enables AI assistants to manage test cases, test runs, defects, and other Qase entities through natural language.

Translation quality evaluation MCP Server powered by xCOMET. Provides quality scoring (0-1), error detection with severity levels, and optimized batch processing for AI-assisted translation workflows.

Enables a language model to run four deterministic data checks it cannot argue with — column-contract validation with an explicit quarantine list, arithmetic reconciliation of opening/movements/closing, distinct entity counting against row counts, and duplicate detection returned for human review — each answering with structured findings and row/column locators. Failures come back as results with reasons, so the model reports exactly which rows and columns are broken rather than asserting the data is clean.

MCP server that exposes the JsonFabrica API as tools, so an AI agent can generate realistic synthetic JSON test data while it codes — single documents or full relational batches from reusable templates, reproducible with a seed. Runs locally over stdio; no network service.

Exposes Semgrep as deterministic, rule-matching analysis tools over MCP so a code-review agent can scan only the lines changed in a diff, scan whole files on demand, and check analyzer availability, version, ruleset, and limits. Results are returned as compact per-finding lines with source snippets suitable as comment anchors, along with counts of suppressed out-of-diff matches.