"Information about Azure (Microsoft Cloud Computing Service or General Search)" matching MCP servers:

This MCP server lets GitHub Copilot fetch Azure Boards work items by URL or ID and generate QA test cases from the ticket content.

Enables AI agents to test WCF/SOAP and REST services directly, with WSDL discovery, authenticated calls, and deterministic assertions. Supports YAML multi-step scenarios with variable extraction, JSONPath/JSON Schema checks, and CI runs without spawning PowerShell or curl.

It enables AI agents and CI to run profile-driven SOAP/REST service tests with automatic login/session handling, test-customer locking, masked transaction-log/HAR catalog import, and cross-environment scenario execution.

An MCP server that connects AI assistants to Xray Cloud for Jira test management, enabling natural language interaction with tests, test plans, executions, and CI result imports.

Enables a stateless, horizontally scaled MCP server using the 2026-07-28 specification, with tools for load testing and instance-aware operations.

MCP server for Xray Cloud test management that enables importing automation results and managing tests, test executions, and test sets in Jira.

MCP server for Jama Connect that brings requirements, traceability, tests, and baselines into MCP clients like Claude, Cursor, VS Code, or GitHub Copilot, with access control, audit trail, and rate limiting. It provides 53 tools across 8 individually enableable toolsets, with an admin dashboard for managing access and usage.

Enables automated WCAG 2.2 AA accessibility audits of Figma designs and webpages. Generates detailed markdown reports with severity-grouped violations, specific criterion references, and concrete fix recommendations.

A local MCP server that connects Claude Desktop, Claude Code, and Claude Chat to your Azure DevOps organization, enabling querying work items, reviewing pull requests, triggering pipelines, searching code, managing test plans, and updating wikis using plain language.

Enables automated access to LoadRunner Cloud APIs for retrieving performance test data, managing projects, and collecting test results. Supports integration with AI clients for building performance engineering workflows and dashboards.

Enables access to Xray Cloud test management on Jira Cloud through its REST v2 and GraphQL APIs, with configurable read/write toolsets, single-tool selection, and read-only or per-request credential modes.

Enables AI assistants to interact with Zephyr Scale Cloud for test management, including test cases, cycles, plans, folders, priorities, and statuses via the MCP protocol.

A paid remote MCP server for OpenAI Codex harness, offering structured JSON tools for coding task planning, safe command suggestions, test verdict recording, and run history.

Enables AI agents to debug code inside VS Code by setting breakpoints, stepping through execution, inspecting variables, and evaluating expressions across multiple languages.

Enables interaction with Gremlin's reliability management APIs to monitor service dependencies, run reliability experiments, generate reliability reports, and manage chaos engineering tests through natural language queries.

Enables controlled interception, review, and editing of web_search and fetch_page responses through a native desktop console, supporting live retrieval, synthetic or hybrid results, context sessions, and fault injection for AI agent robustness experiments.

Provides advanced Flutter development tools via Model Context Protocol with features including widget analysis, documentation search, performance optimization, and code generation.

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.

Provides echo tools for testing MCP protocol functionality with message echoing, delayed responses, and JSON data analysis capabilities.

Connects AI tools to BlazeMeter's Service Virtualization platform, enabling natural language management of virtual services, transactions, and configurations.

Enables MCP-compatible clients to list workspaces, inspect workspace-scoped findings and hosted runs, and prepare or—after explicit user confirmation—start or rerun hosted reviews. It does not access arbitrary local repositories or return raw diffs, full reports, artifacts, screenshots, credentials, or prompt text.

Enables MCP-compatible clients to inspect workspace-scoped findings and hosted runs, and, after explicit confirmation, prepare or start or rerun an existing hosted review.

Enables AI assistants to interact with Azure DevOps projects, including work items, test results, Git repositories, and dependency analysis via the Model Context Protocol.

Enables inspecting workspace-scoped review findings and hosted runs, and preparing or, after explicit user confirmation, starting or rerunning existing hosted reviews. It avoids exposing arbitrary local repositories, raw diffs, full reports, artifacts, screenshots, credentials, or prompt text.

Enables AI-powered document analysis and querying for project documentation using vector embeddings stored in Redis. Supports document upload, context-aware Q\&A, automatic test case generation, and requirements traceability through OpenAI integration.

A remote MCP server that exposes mock application security testing data (applications, scans, issues) for LLM clients to query security posture using natural language.

Enables Cursor AI to query SonarQube for pull request metrics, issues, file issues, and duplication reports directly, without manual data export.

Enables code agents to run risk-based Jev quality reviews on focused diffs through a read-only MCP tool, returning structured scores and weakness hints without modifying code.

Gives any agent eyes and ears by indexing video, audio, and screen activity into searchable, timestamped frames, transcripts, and OCR text that answers can cite. It also evaluates frozen verification contracts over file digests, JSON values, SQL results, HTTP responses, and DOM state to return a deterministic verdict from a separate process.

Enables agents to discover, search, compare, and inspect tested MCP tools by problem or keyword, with certification verdicts, scorecard summaries, certified scope, and explicit not-tested details.