rush
Related Servers
Alternatives to rush
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityAmaintenanceAutonomous spec-to-product coding-agent CLI. Its MCP server exposes 34 tools over stdio: project state and task-queue ops, memory retrieve/store, code search, quality and verification reports, repo hotspots/co-changes, and structured findings/learnings.903 npm1,072Business Source 1.1
- AlicenseNot gradedqualityCmaintenanceAnalyzes codebases to produce structured quality health reports with risk-scored modules based on git churn, test coverage, and test-to-source mapping, acting as an MCP server for AI coding agents and a standalone CLI.14 PyPIMIT
- -licenseNot gradedqualityNot gradedmaintenanceProvides comprehensive code quality tools including linting, security scanning, TypeScript checking, and testing through a single MCP server. Integrates multiple quality analysis tools like Biome, ESLint, and Playwright for streamlined development workflows.-
- AlicenseNot gradedqualityDmaintenanceCode linting and style checking tools for AI agents, exposed as an MCP server. Supports style checks, naming conventions, complexity analysis, dead code detection, and import analysis.29 npmMIT
- AlicenseNot gradedqualityAmaintenanceProvides comprehensive code quality analysis and automated fixing, available as a CLI and MCP server (currently in early beta with MCP part untested).1MIT
- FlicenseNot gradedqualityBmaintenanceLocal MCP server for static Python/TypeScript code audits, Playwright test generation, and SDLC health checks with a 0-100 quality score.-
TDQS
Scored across 79 tools
Many tools fall into the same broad audit/scan bucket, such as rush_review, rush_lint, rush_slop, rush_dead, and rush_complexity, making selection genuinely ambiguous. Test-related tools like rush_test, rush_e2e, rush_snapshot, and rush_visual also blur together, and the deprecated rush_attest_generate alias adds extra confusion.
All tools share the rush_ prefix and snake_case, which keeps the naming readable. However, the operation part is inconsistent: some are nouns, some are verbs, and some are long descriptive phrases, so there is no predictable verb_noun or noun_verb convention.
With 79 tools, this is an extreme over-scoped MCP surface and far exceeds the threshold where a tool set remains navigable. Many related scanners could be consolidated into a single parameterized scan/audit tool, and the sheer count severely harms discoverability.
The inferred domain is a broad engineering-quality and release-readiness assistant, and the tool set covers static analysis, testing, security, release planning, AI evaluation, context management, and agent coordination. Some gaps remain—many findings can only be remediated by rush_fix and several tools depend on external engines—but agents can generally work around these.