Software development, review and analysis.
Model Context Protocol (MCP) server that enables your MCP client (e.g., Claude Desktop, Cline, Roo Code, Cursor, Windsurf, etc.) to interact with GitHub repositories using your GitHub personal access token.
Ein Stryker Reporter Plugin, das Mutation Testing Ergebnisse nativ über das Model Context Protocol (MCP) bereitstellt.
Agent-first, provider-neutral multimodal OCR CLI for images, PDFs, URLs, JSON schemas, and agentic extraction with Gemini, Kimi, Muse, and OpenRouter.
A Model Context Protocol (MCP) server that provides systematic thinking, mental models, and debugging approaches for enhanced problem-solving capabilities
A lightweight, token-efficient local MCP server that exposes the full Buefy component documentation to any MCP‑compatible client (Cursor, Claude Desktop, Cline, Windsurf, etc.)
Structured CI failure summaries on PRs + compact test/build logs for AI agents. GitHub Action, CLI, MCP. ~80-95% fewer tokens on failures.
MCP server for code reviews - connects LLMs to GitHub and GitLab to analyze Merge/Pull Requests and provide expert feedback
An MCP server for testing MCP servers you are developing with AI assistants
MCP server wrapping the MCP Inspector CLI — lets AI agents test any MCP server without a browser.
MCP server for HTTP API testing with Playwright. Supports full CRUD operations, path/query parameters, and comprehensive error handling for API automation workflows.
MCP Server for visual test feedback in vibe coding — QA capability as a protocol
Shared, consistent permission-prompt and policy layer for AI coding agent tools
Install an issue-first Git workflow and an AI session protocol into any repo, for any coding agent.
MCP server exposing QA-lifecycle agents over a traceability spine: requirement -> findings -> tests -> results -> release verdict, with provenance for every AI-produced artifact.
MCP server that helps AI agents stay reliable by scoring tool descriptions, estimating token costs, simulating tool choice, and generating tests.
MCP server that reads Allure test results — failure stacktraces, step details, screenshots and DOM snapshots — from a local directory or a Jenkins build artifact.
An MCP server that guarantees an AI coding agent never hits a dead end — always returns concrete, ranked next-step suggestions as an interactive picker. Works with Claude Code, Cursor, opencode, and any MCP host.
SupaStory MCP server — bring AI-powered session replay insights directly into your editor
MiniMax MCP tools for pi - Web search and image understanding via MiniMax's Model Context Protocol
Mock IBM CSP Entitlement Service MCP Server for Watson Orchestrate