"JavaScript programming language resources" matching MCP servers:

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.

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.

Behavioral verification intelligence for AI coding agents. Reads a TypeScript or JavaScript repo, clusters functions into 25 semantic workflows (Authentication, Payments, Webhooks, Caching, Queue, and more), and emits concrete adversarial probes per workflow. 17 MCP tools, local SQLite state, zero cloud.

Enables LLM agents to programmatically inspect, debug, and test other MCP servers by wrapping the MCP Inspector CLI. Supports listing and calling tools, reading resources, and testing prompts on both local and remote MCP servers.

Enables real-time code analysis for JavaScript, TypeScript, and Python through Claude Desktop and other MCP clients, detecting bugs, code smells, and security vulnerabilities with automated quick fixes.

MCP server that lets AI editors execute JavaScript, read console output, and simulate clicks/input on static web pages. Supports multiple browser pages and can be deployed remotely via HTTP transport.

A high-performance, multi-protocol API mock server with 18 built-in MCP tools for managing HTTP, GraphQL, gRPC, WebSocket, MQTT, SSE, and SOAP mocks, chaos engineering, stateful CRUD resources, and request verification.

Connects AI coding assistants to TestCollab for managing test cases, plans, and suites directly through natural language. It enables users to create, update, and query testing resources within integrated development environments and AI chat clients.

A specialized testing harness that enables AI assistants to thoroughly test other MCP servers by connecting to them, discovering their tools/resources/prompts, executing test calls, and performing end-to-end validation with LLM integration.

MCP server that analyzes TypeScript/JavaScript codebases via AST parsing and dependency graph tracing to identify affected tests, detect dead code, circular dependencies, and trace import chains, enabling AI agents to run only relevant tests.

Enables AI assistants to debug JavaScript and TypeScript applications by connecting to Chrome DevTools Protocol-compatible debuggers, allowing them to set breakpoints, step through code, inspect variables, and evaluate expressions with full source map support.

MCP server that provides audit and safety-check tools for enterprise SDLC code integrity, enabling AI agents to scan workspaces for lifecycle gaps, mock-theater tests, DRY violations, and language-specific issues in shell, JavaScript/HTML, and Python.

Test coverage intelligence MCP server for TypeScript and JavaScript projects. Analyzes coverage reports to find untested functions, computes cyclomatic complexity, and suggests test cases locally.

Small diagnostic MCP server for checking what MCP clients actually support, including tools, resources, prompts, and transport behavior.

Enables automated migration of JavaScript/TypeScript packages from legacy test runners like Karma, Webpack, and Mocha to Vitest, including AST codemods, multi-project test scaffolding, and self-learning diagnostics for resolving runtime errors.

Provides Codex and other MCP clients a local web debugging server that coordinates a browser session, JavaScript debugger, bounded runtime evidence, and reproducible flow verification for vanilla HTML/JS projects.

Enables AI assistants to manage Apple App Store Connect resources like apps, builds, TestFlight, and reviews through natural language.

A minimal browser debugging MCP server that monitors Chrome Console logs and executes JavaScript. 97% lighter than full DevTools alternatives, providing just 4 essential tools for efficient debugging without consuming excessive context tokens.

Enables AI assistants to capture screenshots of web pages using automated browser sessions. Supports full-page and element-specific screenshots, device simulation, and JavaScript execution for comprehensive web testing and monitoring.

Enables LLMs to inspect and test other MCP servers by listing and calling their tools, reading resources, and getting prompts. Supports stdio, SSE, and HTTP transports for both local and remote MCP server inspection.