"Five9: Cloud Contact Center Software" matching MCP servers:

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 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 run deterministic data-center engineering calculations and commissioning audits, including liquid-cooling hydraulics, pipe friction and flow checks, corrosion severity classification, protocol search, and defect-code lookup.

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

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 reproducible evaluation of AI coding agents by exposing repository inspection, code editing, test running, and deterministic verification through MCP tools.

Enables AI assistants to interact with iOS Simulators and Android Emulators, allowing autonomous app development, UI interaction, profiling, and debugging through natural language.

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 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.

Gives your AI the super power of traveling back in time to find what went wrong and fix the bug timeline.

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 AI coding assistants to scan an iOS, Android, Flutter, React Native or Expo project for App Store and Google Play rejection risks, returning deterministic findings that cite the guideline section, link to the official Apple or Google page and explain how to fix each problem. Nothing leaves the machine and no AI is used in the checks.

Lets any MCP client, such as Claude, browse attack suites and probes, run a full assurance assessment with all reports written out, send custom prompts or multi-turn histories and get leak, PII and refusal checks back for adaptive attacks, and read findings from an earlier assessment. This enables agent-driven red-teaming of a chatbot, RAG app or AI agent without leaving the chat client.

A read-only MCP server that exposes Zephyr Scale Cloud test data to review a Jira story's test coverage, answering whether tests are adequate and passing.

Provides an isolated workspace for testing candidate code, runs tests, and returns deterministic pass/fail verdicts. Enables automated grading of software engineering solutions by ensuring reproducible test runs.

Compacts noisy test, build, and cloud-log output before an AI agent reads it — dedupes repeats, collapses stack frames, folds Playwright retries, and renders CloudWatch/GCP JSON logs down to the signal. Typically 80–95% fewer tokens on failures. Tool: compact_output. Run: npx -y logslim logslim-mcp

Enables AI agents to perform software engineering tasks inside an isolated, deterministic sandbox—exploring repositories, reproducing failures, applying patches, running tests, and verifying solutions against hidden suites through MCP tools.

An intelligent MCP toolset for software testers that monitors code changes, analyzes test impact, recommends tests, and assesses risk, supporting multiple AI coding frameworks via dual transport modes.

Enables interaction with Xray Cloud and Data Center for test management, including authentication, GraphQL queries, test execution/plan management, and result import via MCP.

MCP server that analyzes TTS audio recordings, providing transcription, quality scoring, pacing analysis, and mispronunciation detection to debug voice call center audio.

Enables auditing any public website, returning a scored plain-English report that flags issues costing customers, covering speed, phone experience, search visibility, contact options, writing quality, and modernity.

Enables AI agents to enforce a software delivery standard by validating artifacts against declarative rules, providing templates, glossary terms, and pass/fail verdicts with actionable blockers.

Free, rules-based checks for e-commerce product pages: AI shopping readiness (structured data, reviews, return and shipping terms, GTINs, AI crawler access), Google Merchant Center compliance, store SEO audit and Shopify checkout deadlines. No AI calls, nothing stored.