"An overview or resources about Node.js" matching MCP servers:

Enables developers and product owners to scan a codebase and extract a readable business overview—features, roles, access control, data model, and endpoints—along with findings on missing or inconsistent rules, and generate shareable HTML or Markdown reports and diagrams.

Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.

LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.

MCP server that demonstrates the Resources feature by exposing static and dynamic resources, including contact data and personalized greetings, through MCP.

Enables AI assistants to debug Node.js applications using Chrome DevTools Protocol. Provides comprehensive debugging capabilities including breakpoints, stepping, variable inspection, expression evaluation, and console monitoring.

Provides Node.js debugging capabilities with process management for AI agents, allowing them to start/stop Node.js processes, set breakpoints, step through code, and evaluate expressions.

Enables querying Node.js API documentation, including searching for modules and listing all available modules with their methods.

A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.

A basic MCP server that provides arithmetic calculation tools and system information retrieval capabilities, including platform, CPU, and memory details.

Exposes a Node.js REST API for user and product management through MCP tools, allowing AI assistants to directly interact with MongoDB to create, read, update, and delete users and products.

Serves as a practical starting point for AI agents, providing a stateless HTTP-based MCP endpoint with validated example tools for time queries, text formatting, and arithmetic calculations.

MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to: Submit and validate constraint models Set model parameters Solve constraint satisfaction and optimization problems Retrieve and analyze solution

Proxies MCP tools from Mingdao cloud, enabling Coze to use them securely without exposing Mingdao tokens.

Enables running arbitrary JavaScript code in isolated Docker containers with on-demand npm dependency installation, allowing for ephemeral script execution and long-running services with controlled resource limits.

Enables a bot to inspect, query, create, edit, and script Roblox Studio instances in token-cheap batches, plus run Luau, playtests, screenshots, and inputs through Roblox's official Studio MCP connection. It runs locally over stdio or an authenticated local HTTP endpoint, returning small structured answers instead of dumping whole games into context.

Enables AI coding agents to retain and recall project context across sessions through local Markdown storage and hybrid keyword/semantic retrieval, including reusable knowledge cards. It runs offline as a daemon and integrates with MCP-compatible IDEs to continue long-running work without re-explaining decisions or architecture.

A robust server implementing the Model Context Protocol with SSE and STDIO transport, enabling real-time communication and extensible tooling for AI models.

Gitbub mcp

A universal, architecture-agnostic blueprint for building Model Context Protocol servers, providing a modular structure with components for domain logic, storage, security, export, ingestion, forensics, and MCP protocol.

Provides GDB and clangd-based tools for debugging C++ programs, enabling step execution, variable inspection, diagnostics, and combined runtime-static analysis.