"A server for finding channels" matching MCP servers:

Enables passive security scanning of HAR files from QA test automation to detect missing security headers, insecure cookies, CORS misconfigurations, and leaked secrets, without making any live requests.

Enables AI assistants to summarize Playwright test runs, identify flaky tests, heuristically triage failures, generate Playwright test stubs, and retrieve recent GitHub CI status through MCP tool calls.

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.

A reusable MCP server for QA automation testing that enables running tests across web apps, APIs, CLI tools, and more directly from Claude Desktop.

Enables AI agents to perform comprehensive web application testing including visual, functional, performance, accessibility, and SEO analysis using browser automation without requiring API keys.

Provides prompt templates and tools for mobile QA automation, including converting manual tests to Appium scripts, analyzing failures, and standardizing bug reports.

Enables LLMs to inspect and test other MCP servers by listing and calling their tools, reading resources, and getting prompts. Supports stdio, SSE, and HTTP transports for both local and remote MCP server inspection.

MCP server for end-to-end QA automation: generates test scenarios, discovers Playwright locators, creates TypeScript test code, executes tests, and creates GitHub issues for failures.

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 zero-dependency mock MCP server for testing MCP clients and harnesses, with configurable tools and canned responses.

Professional Model Context Protocol implementation for Quality Assurance, integrating best practices of testing, reporting, and defect management.

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

Official MCP server for QA Touch, enabling AI assistants to manage test cases, defects, test runs, and more via natural language.

Enables AI to perform real-browser QA testing on websites via Playwright, finding bugs, accessibility, SEO, and performance issues through natural language conversations.

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 unified development tools including code analysis, debugging, refactoring, documentation, testing, and project automation through multiple LLM providers (KIMI, GLM, OpenRouter). Features agentic audit capabilities with multi-model consensus for finding issues and generating direct fixes.

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.

A fake MCP server that emulates the Pennylane MCP experience for local development, testing, demos, and CI pipelines, providing deterministic fixtures and authentication modes without needing a real Pennylane account.

Automate Google Play closed testing with AI - skip the hassle of finding testers and waiting 14+ days by telling your AI to handle it.

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