"Awesome Lists" matching MCP servers:

Search and explore a catalog of 2,000+ MCP servers — full-text search, trending, hot, categories, and side-by-side comparison — from any MCP client. A zero-dependency stdio bridge over the hosted awesome-mcp.tools endpoint.

Enables AI agents to query China's GB/T 47746—2026 customer-service compliance standard, providing clause-referenced answers, self-check lists, and standard metadata via MCP tools.

Enables AI assistants to query accurate, up-to-date documentation for a React component library, including component lists, search, props, allowed values, defaults, and validated JSX usage examples over stdio.

Enables an MCP client to query a token-driven SCSS design system out of the box, with no manual SDK or zod install step, exposing 30 tools covering themes, mixins, functions, tokens, animations, components, recipes, doc readers, size resolution, and prompt assembly. It resolves that data directly from the installed css-is-awesome package, so answers always match the version the user actually has.

A beginner-friendly Model Context Protocol (MCP) server that helps users understand MCP concepts, provides interactive examples, and lists available MCP servers. This server is designed to be a helpful companion for developers working with MCP. Also comes with a huge list of servers you can install.

🚀 Token-efficient MCP server for Confluence. Reduces LLM costs by 76% via Markdown conversion. Supports listing, searching, and fetching pages.

MCP server for SecretiveShell/Awesome-llms-txt. Add documentation directly into your conversation via MCP resources.

A local, read-only MCP server that lets coding agents search the complete AAS skill catalog, compose and validate agent-chosen skill stacks, and generate reproducible, reviewable plans without uploading project code.

Fetches and renders tldr pages for commands, lists commands and platforms, and searches across page titles.

An MCP server that converts Cursor agent plans into structured markdown task lists and organizes them in your repository, helping you track AI-generated plans and recommendations as actionable specifications.

Enables agents to fetch specifications from the public ProveSpec catalog, search and retrieve specs, and grade their own implementations against capability checklists, returning parity scores and gap lists.

Enables AI assistants to search and retrieve content from the Chinese Minecraft Wiki, including article introductions, full content, and category lists.

Enables searching and exploring CERN Open Data records, files, analysis environments, CMS validated-run (good-run) lists, and HLT trigger paths through MCP tools. Supports exact-vocabulary filtering with live facet counts, license and citation retrieval, and runs over stdio or Streamable HTTP.

Enables converting Markdown text into clean HTML for headings, lists, code blocks, tables, links, and images, with optional full-document wrapping via x402 micropayments.

MCP server for exploring a software developer's portfolio: lists projects, semantically searches code, explains architecture, summarizes READMEs, and answers questions through a natural-language agent, with a built-in web playground.

MCP server for 1C:Enterprise that provides precise syntax reference cards (call signatures, parameters, return types, examples) by element name and lists object members. It helps AI agents answer 1C development questions using the official Russian help book.

Enables reading and searching API documentation from YApi instances, allowing AI models to access interface definitions, project API lists, and search through API endpoints using YApi URLs or project IDs.

Provides access to research paper topics and lists via a remote SSE server, enabling users to explore folders, topics, and execute prompts.

Enables local analysis of OpenAPI 3 and Swagger 2 JSON/YAML spec files on disk, with no remote fetching of specs or credentials. It groups endpoints by tag, flags operations that appear to lack security, lists deprecated operations, and produces short markdown cheat sheets for agents.

Enables AI models to search and read technical discussions, customizations, and error resolutions from the Sankhya Community forum. It provides tools to retrieve topic lists and extract clean content from specific posts to help resolve system-related issues.