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.
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.
MCP server for the Ghost Inspector API that lets agents inspect and manage end-to-end browser tests, offering read-only tools for inventory, module usage, and stale test analysis, plus opt-in guarded write operations.
MCP server for AI security scanning. Detects prompt injections, jailbreaks, data exfiltration, and social engineering attacks in real-time using 42 regex patterns via the ClawGuard Shield API. Sub-10ms response times.
MCP bridge that lets any MCP client drive the Alethia runtime for agent-native E2E testing. It provides a per-step policy gate that blocks destructive actions with a cryptographic audit trail.
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.
Stops your AI from re-introducing bugs, leaking provider keys, or weakening tests. Bug fixes become permanent regression guards; blocked mistakes become AI lessons the agent reads and learns from before its next edit.
Runs SQL statements in memory against real PostgreSQL 18 and SQLite 3.49 engines after loading your schema and sample rows, returning each statement's own verdict: errors with line, column, and hints, constraint violations, or the resulting rows. It also compares both dialects to expose portability differences, all with no database server, network, or API key.
MCP server for Mockzilla. Lets coding agents like Claude Code, Claude Desktop, Cursor and Gemini CLI install the Mockzilla CLI and run API mocks from an OpenAPI spec or a single endpoint. Log in from the agent to deploy hosted mocks on mockzilla.org
MCP server that lets coding agents test AI agents. Create YAML test cases, snapshot golden baselines, check for regressions, and generate visual reports all from inside Claude Code or any MCP-compatible tool. Works with LangGraph, CrewAI, OpenAI, Claude, Mistral, and any HTTP API.
An MCP server that provides tools to interact with the JSONPlaceholder fake REST API for testing and prototyping, supporting CRUD operations on posts, comments, todos, and users.
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.
Analyzes Playwright test results to provide structured QA insights, including test metrics, failure analysis, bug report drafts, and release-quality recommendations.
A temporary MCP server that scrapes Bitrise Insights using Playwright to fetch flaky test data, providing tools to query workspace and app test insights until the official API is released.
Exposes the Polaris architectural fitness-function control plane's REST API as grouped MCP tools over stdio, letting agents manage tribes, squads, fitness targets and functions, measurement sources, submissions, evaluations, waivers, insights, and events. Handles Google OIDC login and silent token refresh automatically, and submits measurements with an ingest API key.
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.
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.
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.