"An overview or resources for jQuery, a JavaScript library" 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.

Deterministic MCP server for semantic analysis of JavaScript/TypeScript codebases, including frameworks like Vue, Angular, React, and Node. It provides tools for type checking, code metrics, framework-specific analysis, and quality heuristics via static parsing.

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

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.

Enables coding agents to establish exact-release library identity, search provenance-tracked API, docs, example, source, and release evidence, compare releases, and test proposed invocations in isolated capsules for Rust and Python dependency environments.

An MCP server that scans React and Vue projects, extracts component metadata (props, slots, events, imports, usage), and exposes it to AI coding agents via structured tools.

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.

Enables AI-assisted development by providing a library of 110+ curated prompts, workflows, and coding standards, with MCP tools for prompt retrieval, composition, and multi-step workflow chains.

An unofficial JavaScript SDK to create customized servers for the Model Context Protocol, allowing definition of prompts, resources, and tools for tailored interactions.

Enables automatically generating standalone MCP servers from any Python library, exposing its functions as deterministic callable tools.

An MCP server that enables users to manage, search, and apply specialized AI personas within Claude Desktop and Claude Code CLI. It features a local-first architecture with YAML-based storage for organizing curated prompts and role collections.

Enables executing submitted code snippets in a fresh isolated V8 isolate, capturing stdout, stderr, return values, and failures under enforced resource limits.

Serves Markdown skill and rule files from a local directory to AI agents on demand, letting them list and fetch specific instructions without context bloat.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Enables OpenAI-compatible clients to access external tools, APIs, repositories, and data sources through MCP with allowlisting, approval, and argument validation, deployable as a FastAPI service or Python library.

Provides AI assistants with access to design documentation across multiple code libraries, enabling discovery of existing utilities and patterns to avoid reimplementation.

A comprehensive prompt library for frontend developers covering React, frontend best practices, and coding guidelines, accessible via MCP tools.