"Troubleshooting JavaScript Code" matching MCP servers:

Scaffolds new MCP servers for the OpenSIN-Code ecosystem with templates for Python, Node, Go; provides tools to add tools, test, validate, register, publish, and audit servers.

Enables Codex CLI to perform code reviews on uncommitted changes via an MCP tool, keeping review context separate from the main session.

A code review MCP server built on FastMCP, supporting security audit, style check, complexity analysis, and bug pattern detection for Python code.

Code Reviewer AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

MCP server providing code review, auto-fix, test running, linting, formatting, and refactor suggestions for Claude Code.

Provides comprehensive code analysis through three MCP servers: static analysis for code quality and security, dependency analysis for package management and vulnerabilities, and complexity analysis for maintainability assessment across multiple programming languages.

MCP server for automated code review using AI agents. It analyzes code diffs or file paths for bugs, security issues, and style violations.

Enables AI-assisted code review with bias mitigation strategies through cross-model evaluation and bias-aware prompting. Detects AI-generated code from commit authors and provides structured reviews with security, performance, and maintainability analysis.

Local MCP server for Cursor that analyzes code, finds bugs, generates tests and documentation via OpenRouter.

Enables AI agents to submit code snippets for review and receive structured quality reports covering correctness, security, performance, maintainability, and best practices.

Signalint is an MCP server that provides JavaScript and TypeScript diagnostics by running Oxlint, TypeScript, and optionally Biome, with caching, clustering of repeated issues, and detection of oscillating diagnostics.

Enables AI coding tools to run CheckMyLaunch scans on GitHub repos or live URLs and retrieve findings and repair prompts directly within the chat.

A Model Context Protocol (MCP) server for interacting with SonarQube code quality platform.

Audits a module against its test suite and reports the cases the tests are structurally unable to see, then proves each gap with a real failing test rather than a warning. Covers Python, TypeScript, JavaScript, Java, Rust and Go.

MCP server for Allure TestOps — lets an LLM agent (Claude Code, Cursor, Windsurf, etc.) inspect test quality without leaving the chat.

Connects AI coding assistants to Gaffer test history and coverage data to analyze project health, debug failures, and identify untested code areas. It enables tools to track test stability, cluster failures by root cause, and monitor code coverage trends across projects.

Enables chat assistants to insert graded coding exercises (Python, JavaScript, TypeScript, SQL) with hidden tests, and returns failed attempts to the conversation so the tutor can explain the learner's specific mistake.

Enables coding agents to gate code modifications behind an evidence check, preventing unnecessary edits by requiring reproduction of the problem before allowing changes.

Enables agents to verify completion by cold-running an acceptance command and reporting whether it exits with code 0, returning a pass/fail receipt with output and refusal reasons.

Enables coding agents to identify likely runtime failures in JavaScript and TypeScript by ranking risky files, tracing dependencies, analyzing logs, and obtaining independent model reviews with line-level reasons.