"Information about CookUnity meal delivery service" matching MCP servers:

Enables agents and teams to manage versioned delivery work items, role-tagged handoffs, revision- and source-bound evidence, QA gate evaluation, and release-owner attestations through MCP tools.

Enables turning requirements documents into RFCs, functional test scenarios, and a traceability matrix, with tools to parse, diff, and verify coverage.

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.

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.

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.

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

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

Enables AI assistants to author, debug, and run Snowfakery data generation recipes through the Model Context Protocol.

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 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.

Enables recurring website maintenance checks — domain registration, SSL certificates, uptime, technical SEO and accessibility — across a portfolio of client sites, using publicly available information. Results are returned as structured data and can be sorted by urgency into a client-ready report.

Enables AI assistants to inspect generated .docx and .pdf files before delivery, extracting structural, typographic, spacing, and language facts so formatting errors can be caught automatically.

Visual CVE audit dashboard for npm, Python, Go, and Rust projects. Scans your project manifests (package-lock.json, requirements.txt, go.sum, Cargo.lock) against OSV.dev live data, opens a browser dashboard for human review, then applies fixes only after explicit confirmation. Supports multi-service monorepos in one command.

Enables coding agents to compile supplied files, run optional focused tests, and get static findings across ten programming languages, providing a deterministic feedback loop on the code they are about to return.

Exposes six evidence-oriented tools over stdio so MCP clients can navigate unfamiliar code, ask typed questions about repository evidence, review completed changes, and select existing tests.

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.

Umbra is the trust layer for AI-generated code. It scores any repo 0-100 with file:line evidence (security, slop, Docker-verified build/boot, and claim receipts that catch agents lying about tests), and guards agent file writes mid-stream blocking leaked keys, alg:none JWTs, and git-hook plants before they land. Tools: scan_repo, guard_content, get_score.

Test management over MCP: author test cases, run manual executions with per-case results, cut releases, and link automated tests to the cases they cover. Works against the hosted M00N Report service or a self-hosted instance.

Enables coding agents to drive and inspect running Shiny apps (R and Python) by setting inputs, clicking, reading outputs, and getting detailed error information.

Automated Playwright E2E test repair powered by a self-improving, governed MCP server that runs failing tests, collects failure artifacts, reasons about root causes, validates and applies fixes, and re-runs to verify.

An MCP server that turns Zod schemas into mocks, violations, and contract tests, enabling AI agents to reason about API contracts without manually crafting payloads.

Enables AI assistants to access RenderDoc capture data and assist with graphics debugging by retrieving draw calls, shader information, buffers, textures, and pipeline state.

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.

Turns JUnit XML test reports from CI into queryable QA metrics, letting AI assistants answer plain-English questions about failures, flaky tests, regressions pinned to a commit, root-cause clusters, and performance drift. Also generates ready-to-share QA health reports and self-contained HTML dashboards without logging into separate tools.

Rarefaction is a Model Context Protocol (MCP) server that gives a coding agent the call graph and code context for one symbol straight from the project's language server (Language Server Protocol, LSP). Ask about a function, method or type and get, in one call: its signature and doc, its body, who calls it (tests marked), what it calls, who implements it, the tests that reach it and the short list

Enables AI agents to audit web surfaces for conformance and generate findability and delivery metadata, including meta tags, JSON-LD, sitemaps, robots.txt, image markup, and contrast-checked palettes, with provenance-stamped results.

Gives AI agents a real Chromium browser via Playwright to QA-test web apps, with pass/fail assertions, network mocking, recorded traces and reports, and safety guards that block live payment traffic. Test outcomes come back as explained verdicts suitable for review or email delivery.