"Resources and Information about JavaScript Programming" matching MCP servers:

Provides 23 modular tools for competitive programming, including problem analysis, algorithm planning, code generation, verification, testing, code review, and learning assistance.

Enables AI-powered PLC programming with natural language to ladder logic conversion, L5X and .ACD project generation, and semantic search through L5X files and documentation.

Provides TypeScript and JavaScript code refactoring operations using ts-morph, allowing AST-based symbol renaming, file/folder renaming, reference searching, and path alias removal when integrated with editor extensions like Cursor.

An enhanced sequential thinking tool optimized for programming tasks that helps break down complex coding problems into structured, self-auditing thought steps with branching and revision capabilities.

Exposes 31 high-assurance agentic coding skills as MCP tools and resources, enabling AI agents to invoke structured workflows across DISCIPLINE, TECHNIQUE, KNOWLEDGE LAYER, and REFERENCE registers.

A Model Context Protocol server that provides integration with LeetCode APIs, enabling automated interaction with programming problems, contests, solutions, and user data across both leetcode.com and leetcode.cn platforms.

An MCP server that enables local AI models to receive guidance from remote 'senior' AI providers like OpenAI, Anthropic, and Gemini to solve programming problems. It features intelligent multi-turn dialogue management, context synchronization, and automated session history tracking.

Enables coding agents to search and retrieve persistent repository memory created by Cliper, providing context, gaps, architecture, and timeline information via MCP tools.

Enables AI agents to execute Python, TypeScript, and JavaScript code in persistent Jupyter kernels with stateful variables and imports across interactions.

An MCP server that integrates with mem0.ai to help users store, retrieve, and search coding preferences for more consistent programming practices.

MCP server for Python build123d to help AIs develop and reason about 3D models and CAD

ast-mcp-server gives coding agents compact, type-aware access to TypeScript and JavaScript projects, providing structural code tools based on the real compiler project model through ts-morph for declarations, references, renames, and diagnostics, with safe prepare → review → apply mutation semantics and immutable hash-bound plans.

Connects AI assistants to the Repovive competitive-programming platform, enabling them to browse problems and contests, judge and submit code for real verdicts, track ratings, communicate with users, and author verified problems and rounds.

MCP server for the AIMFP paradigm, enabling AI assistants to manage functional programming projects with persistent database state, directive compliance, and task tracking via JSON-RPC tools.

Turns AI assistants into full-stack software engineers with 36 tools for cognitive reasoning, code validation, project scaffolding, and AI/IDE configuration generation across 130+ programming languages, databases, and frameworks.

Enables MCP clients to interact with OpenCode 2.x/3.x servers through direct /api/... HTTP routing and ~85 tools spanning sessions, messages, files, config, providers, projects, input, TUI, and workflows. Runs as a zero-dependency, pure-JavaScript stdio bridge with no SDK or build step.

Architectural Gatekeeper for AI coding. Prevents "tunnel vision" bugs by forcing the AI to verify dependencies (via AST parsing) before editing files. Supports JavaScript & TypeScript. Blocks unsafe edits until the AI proves it understands the impact

Enables coding agents to navigate and query source code by providing context, symbols, and call graph information through a graph index.

A FastMCP integration with Hyperskill that allows AI agents to explain programming topics and search for programming resources using Hyperskill's learning materials.

Enables MCP clients such as OpenCode, Claude Code, and Codex to control a real VS Code editor by opening files, visibly typing code, running terminal commands, reading diagnostics, and fixing errors through the VS Code API. It makes AI programming observable by applying real progressive edits and actions that are visible on screen.