"API Labs MCP server" matching MCP servers:

API Tester AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Enables AI assistants to interact with Sauce Labs testing platform through natural language, providing access to device cloud management, test job analysis, build monitoring, and testing infrastructure insights. Supports both Virtual Device Cloud (VDC) and Real Device Cloud (RDC) with comprehensive test analytics and team collaboration features.

Accessibility AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Enables natural-language chat-driven API testing, letting users upload API specs, run deterministic pytest checks against live targets, inspect results, create defects, and view failure trends.

Starter scaffold for a workshop to build an MCP API testing server, intended to be extended through incremental steps.

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.

Enables MCP-compatible clients to discover API endpoints from OpenAPI/Swagger specs, send HTTP requests, validate responses, and analyze status codes for automated API testing.

Deterministic fluff detector for AI-generated prose. No model, no API key.

Enables testing how different MCP clients handle tool results containing both content and structuredContent, including outputSchema enforcement and mismatch scenarios.

Zero-Config, Fully AI-Managed End-to-End Testing for all code gen platforms.

Reads a small-business website like a customer would and shows where they get stuck. Every AI answer has to quote the page, and the server checks the quote before it counts.

Enables management of TestMu AI test projects, test cases, test runs, and integration with Jira, HyperExecute, and AI insights through natural language.

Enables reading, listing, searching, commenting on, and updating status of ZenTao bugs via its REST API, with write operations defaulting to dry-run.

Analyzes Playwright test results to provide structured QA insights, including test metrics, failure analysis, bug report drafts, and release-quality recommendations.

An MCP server that makes backend API requests and packages request+response pairs as evidence to prove an endpoint works.

Checks a site for AI crawlers: which of 11 AI crawlers its robots.txt lets in, whether its llms.txt follows llmstxt.org, and what its home page says without scripts. Findings with evidence; no scores, no model calls, no telemetry.

Enables prompt optimization loops and regression test suites for Claude Code, with a companion web UI for real-time visualization of scores and prompt revisions.

A research harness for measuring whether MCP clients preserve informed consent when tool definitions change after approval.

An MCP server that automatically discovers API endpoints from any codebase, generates and runs tests, and produces per-role QA audit reports in PDF and XLSX.

Enables engineering leaders to query their AI assistant for quality KPIs — MTTR, MTTA, DORA metrics, defect escape rate and SLA breaches — computed from Jira bug, incident and deployment CSV exports already on hand. It delivers trends, period comparisons, hotspot findings and ready-to-share executive summaries and HTML dashboards without a BI stack or data warehouse.

Evidence-driven quality testing for Model Context Protocol servers. It connects as a real client, captures the complete model-facing contract, identifies agent-usability risks, measures context cost, and executes only explicitly approved target calls.

Enables agents and users to validate Kubernetes manifests (YAML/JSON, multi-document) against the API of a chosen Kubernetes version without needing a cluster. It reports removed or deprecated APIs with replacements, unknown or misspelt fields, misconfigurations the API server would reject, Pod Security Standard violations, and common risks, each with file, line, and fix.

MCP server that generates ISO/IEC/IEEE 29119-3 compliant test plan drafts from project information, providing a structured resource for the standard's test plan outline and a tool for draft creation.

A licensed, locally run Playwright E2E testing MCP server for Claude Desktop and Cursor. It lets AI coding agents inspect semantic accessibility structure, validate role-based browser flows with explicit assertions, and generate reusable Playwright tests.

Enables AI coding assistants to distribute iOS and Android builds to BetaDrop testers, manage share links, track releases, and manage API tokens entirely through natural language prompts.

Contract-driven test enforcement and reporting for LLM-generated code via MCP, VS Code, Copilot CLI, Claude, Cursor, or Python SDK.

Exposes Specmatic's API contract testing, resiliency testing, and mocking capabilities to AI coding agents via natural language, enabling automated validation and simulation of API behaviors.

Turns an OpenAPI spec into a ready-to-run test harness with local LLM agents: WireMock stubs, contract tests, robustness probes, and chaos scenarios you can switch on and off in a running WireMock.

MCP server for self-hosted qTest Manager, enabling natural-language management of projects, modules, test cases, requirements, traceability, and test execution via the qTest REST API.

Connects Claude to Apple's App Store Connect API, letting you manage apps, builds, TestFlight beta groups and testers, customer reviews and replies, sales and finance reports, and team users through natural language. Write actions such as invites, beta review submissions, and review responses require confirmation before anything is sent.