Model Context Protocol (MCP) Servers
Comprehensive collection of Model Context Protocol servers that help AI models securely interact with local and remote resources through standardized implementations.
Table of Contents
Top Starred Repositories
- Type: Cloud browser automation
- Features: Web navigation, data extraction, form filling
- Platform: Cloud-based browser automation
- Best for: Production web scraping and automation
- Type: Official Microsoft browser automation
- Features: Web page interaction via accessibility snapshots
- Platform: Cross-platform browser control
- Best for: Enterprise web automation
- Type: Database and backend integration
- Features: Table management, data querying, project management
- Platform: Supabase cloud platform
- Best for: Full-stack application development
- Type: API integration platform
- Features: 2,500+ APIs, 8,000+ prebuilt tools
- Platform: Cloud and local deployment
- Best for: Rapid API integrations
- Type: In-memory database integration
- Features: Data management, search capabilities
- Platform: Redis Cloud and local instances
- Best for: Caching and real-time data
Browser Automation
- Type: Cloud browser automation
- Features: Web navigation, data extraction, form filling
- Platform: Cloud-based
- Best for: Production web scraping
- Type: Official browser automation
- Features: Accessibility snapshots, web interaction
- Platform: Cross-platform
- Best for: Enterprise automation
- Type: AI-powered browser automation
- Features: Natural language web control
- Platform: Docker + VNC
- Best for: AI-driven web tasks
- Type: Chrome/Chromium automation
- Features: Web scraping, interaction
- Platform: Node.js
- Best for: JavaScript-based automation
Database Integration
- Type: Full-stack platform integration
- Features: Database, auth, storage management
- Platform: Supabase Cloud
- Best for: Modern web applications
- Type: PostgreSQL database integration
- Features: Schema inspection, query execution
- Platform: Local and cloud PostgreSQL
- Best for: Relational database operations
- Type: SQLite database operations
- Features: Built-in analysis, query capabilities
- Platform: Local file-based database
- Best for: Lightweight data storage
- Type: NoSQL database integration
- Features: Document operations, collection management
- Platform: MongoDB instances
- Best for: Document-based applications
- Type: In-memory database
- Features: Data management, search, caching
- Platform: Redis Cloud and local
- Best for: Real-time applications
- Type: AWS services integration
- Features: EC2, S3, Lambda management
- Platform: Amazon Web Services
- Best for: Cloud infrastructure management
- Type: Cloudflare services integration
- Features: Workers, KV, R2, D1 management
- Platform: Cloudflare platform
- Best for: Edge computing and CDN
- Type: Infrastructure as Code
- Features: Resource management, deployment
- Platform: Multi-cloud
- Best for: Infrastructure automation
- Type: Container orchestration
- Features: Cluster management, resource operations
- Platform: Kubernetes clusters
- Best for: Containerized applications
- Type: Slack workspace integration
- Features: Message management, channel operations
- Platform: Slack workspaces
- Best for: Team communication automation
- Type: Discord bot integration
- Features: Message handling, server management
- Platform: Discord servers
- Best for: Community management
- Type: Telegram API integration
- Features: Message management, bot operations
- Platform: Telegram
- Best for: Personal and group messaging
- Type: Teams integration
- Features: Messaging, member management
- Platform: Microsoft Teams
- Best for: Enterprise communication
- Type: Git and GitHub integration
- Features: Repository management, PR operations
- Platform: GitHub platform
- Best for: Code collaboration
- Type: Container management
- Features: Image management, container operations
- Platform: Docker Hub and local
- Best for: Containerized development
- Type: CI/CD integration
- Features: Build management, failure analysis
- Platform: CircleCI platform
- Best for: Automated testing and deployment
- Type: API testing and management
- Features: Collection management, API testing
- Platform: Postman platform
- Best for: API development and testing
- Type: 3D modeling and animation
- Features: 3D scene manipulation, rendering
- Platform: Blender software
- Best for: 3D content creation
- Type: Pixel art creation
- Features: Sprite editing, animation
- Platform: Aseprite software
- Best for: Game development and pixel art
- Type: Video editing and post-production
- Features: Video editing, color grading
- Platform: DaVinci Resolve
- Best for: Professional video production
- Type: 3D animation and modeling
- Features: 3D scene management, animation
- Platform: Autodesk Maya
- Best for: Professional 3D animation
Aggregators and Frameworks
- Type: Unified MCP server aggregator
- Features: Multiple server integration
- Platform: Cross-platform
- Best for: Managing multiple MCP servers
- Type: MCP server management platform
- Features: GUI-based server management
- Platform: Cross-platform
- Best for: Visual MCP server management
- Type: MCP server discovery hub
- Features: Server discovery and installation
- Platform: Web-based
- Best for: Finding and learning about MCP servers
- Type: MCP server proxy and load balancer
- Features: Request distribution, load balancing
- Platform: Cross-platform
- Best for: Scaling MCP server deployments
Selection Guide
| Use Case |
Recommended MCP Server |
Why |
| Web Automation |
Browserbase MCP |
Cloud-based, production-ready |
| Database Operations |
Supabase MCP |
Full-stack integration |
| Cloud Management |
AWS MCP |
Comprehensive AWS services |
| Team Communication |
Slack MCP |
Rich workspace integration |
| Development Workflow |
GitHub MCP |
Complete Git/GitHub operations |
| API Testing |
Postman MCP |
Comprehensive API management |
| 3D Content Creation |
Blender MCP |
Professional 3D modeling |
| Server Management |
1MCP Agent |
Unified server aggregation |
Quick Start Examples
Python - Basic MCP Server
from mcp import Server, StdioServerTransport
from mcp.server.models import InitializationOptions
import asyncio
# Create MCP server
server = Server("my-server")
@server.list_tools()
async def list_tools() -> list:
return [
{
"name": "hello_world",
"description": "Say hello to the world",
"inputSchema": {
"type": "object",
"properties": {
"name": {"type": "string", "description": "Name to greet"}
}
}
}
]
@server.call_tool()
async def call_tool(name: str, arguments: dict) -> dict:
if name == "hello_world":
return {"content": f"Hello, {arguments.get('name', 'World')}!"}
TypeScript - Browser Automation
import { MCPClient } from '@modelcontextprotocol/sdk/client/index.js';
import { StdioClientTransport } from '@modelcontextprotocol/sdk/client/stdio.js';
// Connect to browser MCP server
const transport = new StdioClientTransport({
command: 'npx',
args: ['@browserbase/mcp-server-browserbase']
});
const client = new MCPClient({
name: "browser-client",
version: "1.0.0"
}, {
capabilities: {}
});
await client.connect(transport);
// Navigate to a website
const result = await client.callTool({
name: "navigate",
arguments: {
url: "https://example.com"
}
});
Additional Resources
Getting Started
- Choose your MCP server based on your use case
- Install the server using npm, pip, or direct download
- Configure your AI client such as Claude Desktop or Cursor
- Start using natural language to interact with your tools
Tip: MCP servers enable AI models to interact with external tools and services through a standardized protocol, making assistants more useful and more capable.