Awesome MCP Servers
@habitoai
关于 Awesome MCP Servers
A comprehensive collection of Model Context Protocol (MCP) servers categorized by functionality. This repository helps developers and AI enthusiasts discover and utilize the wide array of available MCP servers for various applications.
基本信息
配置
工具
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概览
What is Awesome MCP Servers?
A curated collection of Model Context Protocol (MCP) servers organized by functional categories, designed to help developers and AI enthusiasts discover and leverage MCP servers for various applications.
How to use Awesome MCP Servers?
Navigate through the categories listed in the table of contents or scroll through the sections to find relevant servers. Each entry provides a link to the server’s repository for installation, configuration, and usage details.
Key features of Awesome MCP Servers
- Categorized into over 25 functional areas
- Links to individual MCP server repositories
- Open-source and community-driven collection
- Covers AI, cloud, databases, browser automation, and more
Use cases of Awesome MCP Servers
- Discovering servers that extend AI models with real‑world APIs
- Finding tools for web scraping, email automation, or cloud management
- Identifying servers that integrate with Slack, Google Drive, or Kubernetes
- Locating solutions for data science, finance, or workflow automation
FAQ from Awesome MCP Servers
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文件与存储 分类下的更多 MCP 服务器
Claude Document MCP Server
alejandroBallesterosCA lightweight MCP server for processing, editing, and interacting with PDF, Word, Excel, and CSV documents.
box-mcp-server
hmkA Box model context protocol server to search, read and access files
Google Drive server
isaacphiModel Context Protocol (MCP) Server for reading from Google Drive and editing Google Sheets
mcp-rquest
xxxbrianA MCP server providing realistic browser-like HTTP request capabilities with accurate TLS/JA3/JA4 fingerprints for bypassing anti-bot measures. It also supports converting PDF and HTML documents to Markdown for easier processing by LLMs.
S3 MCP Server
samuraikunMCP server to integrate AWS S3 and LLM
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