ZBS Index What actually exists in applied AI, with the source next to it

mcp server

OrangePro

Find test gaps, generate grounded tests, and dynamically prove behavior with mutation testing.

Description as published by the maintainer. Source

  • version 0.2.21
  • active

active — Most recent push to the repository was 2026-08-05.

Signals

These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.

Signal Value What it measures Window Observed Source
GitHub stars 15 Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. cumulative, all time GitHub
Last commit 2026-08-05 Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. point in time GitHub
Open issues 0 Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. as of fetch GitHub
Package downloads 1,273 downloads Package downloads from the npm registry in this window. Includes continuous integration runs, mirrors and automated installs, so it overstates the number of human users. 2026-07-30 to 2026-08-05 npm
Latest published version 0.2.21 Latest version string the maintainer published to the registry. as of fetch Model Context Protocol
Registry record last updated 2026-08-05 When the registry record was last updated by its maintainer. point in time Model Context Protocol
License MIT Licence GitHub detected in the repository. Detection can be wrong; the LICENSE file is authoritative. as of fetch GitHub
First listed in the MCP Registry 2026-08-05 Date this server was first published to the official MCP Registry. Not a usage or quality measure. point in time Model Context Protocol
repository status active The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. as of fetch GitHub

Where to get it

Related, by what their authors tagged them

  • Vibe Test — Browser Testing Agent — last commit 2026-06-08, shares ai-testing, test-automation, testing
    Code-aware browser testing agent — 13 Playwright tools for AI code editors via MCP
  • Drengr — last commit 2026-08-01, shares ai-testing, test-automation
    Eyes and hands for AI agents on Android and iOS devices.
  • io.github.ai-dashboad/flutter-skill — last commit 2026-07-23, shares ai-testing, test-automation
    AI-powered E2E testing for 10 platforms. 253 MCP tools. Zero test code needed.
  • Workflow Generator — last commit 2026-07-27, shares developer-tool, static-analysis
    Architecture diagram with concurrency capacity and bottleneck estimates from any codebase.
  • Open Investment Model — last commit 2026-07-22, shares knowledge-graph, ontology
    Read-only OpenIM search for institutional buy-side investment models and architecture.
  • io.github.cruxible-ai/cruxible-core — last commit 2026-08-05, shares ontology
    Deterministic decision engine with receipts. Define rules in YAML, query a graph, get proof.
  • KSail — last commit 2026-08-07, shares developer-tool
    SDK for creating, managing, and operating Kubernetes clusters and workloads with ease.
  • ai.testiv/mcp — last commit 2026-08-04, shares test-automation
    Local-first visual regression for AI agents: verdicts, diff images, explain_snapshot. No API key.
  • arvindrk-extract-design-system-extract-design-system — last commit 2026-08-01, shares developer-experience
    Extract design primitives from a public website and generate starter token files for your project.
  • adrkit decision memory — last commit 2026-08-06, shares developer-experience
    Deterministic, offline, read-only ADR decision memory for coding agents. No model or network calls.

These share tags the maintainers applied themselves, such as ai-testing, test-automation, testing, developer-tool. Common tags like "mcp" or "ai" are ignored for this: agreeing with six hundred other projects is not a similarity.

This is not a recommendation and not a test result. It is a map of what the authors said their work is about.

Also from orangeproai

  • OrangePro
    Find test gaps, generate grounded tests, and dynamically prove behavior with mutation testing.

How the author describes it

Topics the maintainer set on GitHub: ai-test-generator, ai-testing, behavioral-coverage, claude-code, code-coverage, developer-experience, developer-tool, end-to-end-testing, graph-based-testing, integration-testing, knowledge-graph, mcp, model-context-protocol, mutation-testing, ontology, semantic-analysis, static-analysis, test-automation, test-generation, testing.

Bring your own setup

We take apart real AI setups every week and show what broke, what cost too much, and what the trace actually said. If you run agents on real work, that is where the useful conversation is.

Join ZBS AI Practice Lab

Sources

  1. OrangeproAI/orangepro-mcp on GitHub — GitHub, observed , trust tier 3.
  2. @orangepro/mcp-server download counts — npm, observed , trust tier 3.
  3. Official MCP Registry — Model Context Protocol, observed , trust tier 1.