"API for Claude AI" matching MCP servers:

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

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

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

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

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

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 agents to call real API endpoints and verify responses against OpenAPI specs, supporting contract testing, auth presets, spec diffing, and health checks.

Generates comprehensive API test plans (positive, negative, and boundary/edge cases) from endpoint metadata using LLMs, and exports them as Excel files.

MCP server for measuring, tracking, scoring, and improving AI agent reliability with tools for recording interactions, scoring reliability, analyzing failures, recommending improvements, generating audit reports, and checking MCP health.

Enables AI agents to manage Autotest AI projects, screens, test cases, and test runs through natural language commands.

Enables agents to work with Robot Framework by discovering tests and resources, drafting tests from requirements, dry-running and executing suites, and parsing output.xml results.

Enables AI clients to analyze software test results and defect records, producing explainable GO, CONDITIONAL_GO, or NO_GO release-readiness recommendations with deterministic risk scoring, failed-test retrieval, defect hotspot ranking, and regression test planning.

Enables scanning text for policy and safety issues, generating test suite outlines, and checking the configuration/health of the evaluation setup.

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.

Enables input/output policy validation via MCP, including scanning text for policy and safety issues, generating test suite outlines, and checking configuration health.

MCP server for AI-powered QA analysis. It enables analyzing test failures, identifying root causes, suggesting fixes, classifying defects, detecting flaky tests, and generating test cases and bug reports.

An MCP server for validating AI-generated code through automated browser testing, evidence collection, and intelligent diagnostics.

Enables AI assistants to write and run mobile UI tests on Android and iOS simulators via natural language, supporting native and WebView apps without Appium.

Enables running, listing, inspecting, and comparing standardized model benchmarks through MCP.