Introduction to MCP: The Universal Connector for AI Assistants

TL;DR - What is MCP?

MCP (Model Context Protocol) is an open protocol that lets AI assistants like Claude connect to external tools and data sources. Think of it as “USB for AI” - a universal standard for AI integrations.

Key points:

• 🔌 Industry Standard: Works with Claude, ChatGPT, Copilot, Gemini, Cursor, VS Code, and more
• 🚀 10,000+ Servers: Connect to GitHub, databases, file systems, Notion, Slack, and thousands more
• 🔒 Secure by Design: Runs locally, you control permissions, no cloud middleman
• 🆓 Free & Open Source: Now maintained by Linux Foundation’s Agentic AI Foundation
• ⚡ Easy to Use: Configure in minutes with simple JSON
• 🏛️ December 2025: Donated to Linux Foundation with support from OpenAI, Microsoft, Google, and AWS

Why it matters:

• AI can now read your codebase directly
• AI can query your database with natural language
• AI can manage your Notion workspace, Slack channels, and more
• No more copy-pasting context into every conversation

💡 Example: With GitHub MCP, you can say “Create a pull request with all the changes we discussed” and Claude will actually do it - not just explain how.

The Problem: AI Assistants Are Isolated

You’ve probably experienced this frustration:

Without MCP:

You: "Can you review the code in my project?"
AI: "I'd love to! Please paste the code you'd like me to review."
You: *copies 500 lines from file 1*
You: *copies 300 lines from file 2*  
You: *copies the package.json*
You: "Here's the code..."
AI: "Thanks! Now can you share the test files too?"
You: 😫

AI assistants are incredibly powerful, but they’re isolated bubbles. They can’t see your files, access your databases, or interact with your tools. Every conversation starts from scratch. For more on AI capabilities, see the AI Agents guide.

This limitation forces you to:

• Copy-paste massive amounts of context
• Describe systems instead of showing them
• Manually execute every suggestion the AI makes
• Re-explain your project in every new conversation

MCP solves this problem.

Enter MCP: The Universal Connector

Model Context Protocol (MCP) is an open protocol introduced by Anthropic in November 2024 and now maintained by the Linux Foundation’s Agentic AI Foundation (as of December 2025). It has become the industry standard for AI tool integration, adopted by all major AI providers including OpenAI, Microsoft, and Google. For a complete timeline of how MCP and other AI technologies evolved throughout 2025, see our AI in 2025: Year in Review.

The “USB for AI” Analogy

Before USB, every device had its own proprietary connector:

• Printers needed printer cables
• Cameras needed camera cables
• Phones needed phone cables

USB created a universal standard. Now everything just works.

MCP does the same for AI:

• Before MCP: Every AI tool had its own integration system (ChatGPT plugins, Claude tools, etc.)
• After MCP: Any AI tool can use any MCP server

┌─────────────────┐     ┌─────────────────┐     ┌─────────────────┐
│  Claude Desktop │     │     Cursor      │     │  VS Code        │
│                 │     │                 │     │  + Continue     │
└────────┬────────┘     └────────┬────────┘     └────────┬────────┘
         │                       │                       │
         │         MCP Protocol (Universal Standard)     │
         │                       │                       │
         ▼                       ▼                       ▼
┌─────────────────────────────────────────────────────────────────┐
│                         MCP Servers                             │
├─────────────┬─────────────┬─────────────┬─────────────┬─────────┤
│   GitHub    │  Postgres   │ Filesystem  │   Notion    │  Slack  │
│   Server    │   Server    │   Server    │   Server    │  Server │
└─────────────┴─────────────┴─────────────┴─────────────┴─────────┘

How It Works

MCP has three main components:

When you configure an MCP server:

1. Your AI tool (host) starts the MCP server
2. The server tells the AI what tools are available
3. The AI can now use those tools during conversations

The MCP Ecosystem

The MCP ecosystem has exploded since its launch, reaching 10,000+ active servers by December 2025. Here’s what’s available:

Official Reference Servers (by Agentic AI Foundation)

These are maintained by the Linux Foundation’s Agentic AI Foundation:

Official Integrations (by Companies)

Major companies have built official MCP servers:

Community Servers

The community has built 9,000+ additional servers for:

• Google Drive, Dropbox, OneDrive
• Airtable, Linear, Trello
• Discord, Telegram, WhatsApp
• Docker, Kubernetes
• Stripe, Shopify
• SAP, Oracle, Salesforce
• Custom enterprise integrations
• And thousands more…

MCP Clients (AI Tools That Support MCP)

Real-World Use Cases

Let’s look at practical examples of what you can do with MCP:

🧑‍💻 Developer Workflow

MCP shines in development environments. For more on AI-powered coding, see the AI-Powered IDEs Comparison guide.

Without MCP:

You: "Review my authentication code"
AI: "Please paste the code..."
*You spend 5 minutes copying files*

With MCP (Filesystem + Git + GitHub):

You: "Review the authentication code in src/auth/, 
      check git history for recent changes, 
      and create an issue for any security concerns"

AI: *reads files from src/auth/*
    *checks git log for recent commits*
    *analyzes code*
    *creates GitHub issue #47: "Potential session fixation vulnerability"*

"I reviewed the authentication module. Found 2 issues:
1. Created GitHub Issue #47 for a session fixation risk
2. The password hashing uses an outdated algorithm

Here are my recommended fixes..."

📊 Data Analysis

With MCP (PostgreSQL + Filesystem):

You: "What were our top 10 products last month? 
      Export to a CSV on my desktop."

AI: *queries database*
    *writes file to ~/Desktop/top_products.csv*

"Done! I found the top 10 products by revenue:
1. Widget Pro - $45,230
2. Gadget Plus - $38,100
...
Exported to your Desktop as 'top_products.csv'"

📝 Productivity

With MCP (Notion + Slack):

You: "Summarize what happened in #engineering today 
      and add action items to my Notion task database"

AI: *reads Slack channel*
    *creates Notion tasks*

"Here's today's summary from #engineering:
- Deployed v2.3.1 to production
- Discussed new auth system

I added 3 action items to your Notion:
✅ Review PR #892
✅ Schedule security audit
✅ Update documentation"

🔍 Research

With MCP (Fetch + Memory):

You: "Research the latest trends in AI agents. 
      Remember what you find for future reference."

AI: *fetches articles from web*
    *stores in knowledge graph*

"I researched AI agent trends and saved key findings:
- Multi-agent systems are trending
- Tool use is the fastest growing capability
- MCP adoption is accelerating

I've stored this in memory. Ask me about AI agents 
anytime and I'll remember this context."

For more on research techniques with AI, see the RAG, Embeddings & Vector Databases guide.

Getting Started with MCP

Ready to try MCP? Here’s a quick start:

Step 1: Choose Your MCP Client

Pick an AI tool that supports MCP:

Step 2: Configure Your First MCP Server

Here’s how to add the Filesystem MCP server to Claude Desktop:

1. Find your config file:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%/Claude/claude_desktop_config.json
• Linux: ~/.config/Claude/claude_desktop_config.json

2. Add this configuration:

{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-filesystem",
        "/Users/yourname/projects"
      ]
    }
  }
}

3. Restart Claude Desktop

4. Test it:

You: "What files are in my projects folder?"
Claude: "I can see the following files and folders..."

Step 3: Add More Servers

Once you’re comfortable, add more servers:

{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem", "/Users/me/projects"]
    },
    "github": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-github"],
      "env": {
        "GITHUB_PERSONAL_ACCESS_TOKEN": "ghp_your_token_here"
      }
    },
    "postgres": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-postgres", "postgresql://localhost/mydb"]
    }
  }
}

📖 Next Article: How to Install and Configure MCP Servers - Complete setup guide for Claude, Cursor, VS Code, and more.

Security Best Practices

MCP is designed with security in mind, but you should still follow best practices:

✅ Do’s

❌ Don’ts

For more on responsible AI usage, see the Understanding AI Safety, Ethics, and Limitations guide.

How MCP Security Works

┌──────────────────────────────────────────────────────┐
│                   YOUR MACHINE                        │
│  ┌─────────────┐     ┌─────────────┐                 │
│  │   Claude    │────▶│  MCP Server │◀──┐             │
│  │   Desktop   │     │ (runs here) │   │             │
│  └─────────────┘     └──────┬──────┘   │             │
│                             │          │             │
│                    ┌────────▼─────┐    │             │
│                    │  Only paths  │    │ Sandboxed   │
│                    │  you specify │    │ Access      │
│                    └──────────────┘    │             │
└──────────────────────────────────────────────────────┘
                             │
                    ❌ Cannot access
                             │
                    ┌────────▼────────┐
                    │  Other files    │
                    │  System files   │
                    │  External APIs  │
                    └─────────────────┘

Key security features:

• Local execution: Servers run on your machine, not in the cloud
• Sandboxed access: Only resources you explicitly allow
• No network by default: Most servers don’t make external calls
• Transparent operation: You can inspect server source code

MCP vs. Other Approaches

How does MCP compare to other AI integration approaches?

Bottom line: MCP has become the industry standard, supported by all major AI providers. It gives you the flexibility of custom APIs with the ease of configuration, while keeping your data secure.

Recent Major Updates (2025)

MCP has evolved significantly since launch:

December 2025: Linux Foundation Donation

• 🏛️ Agentic AI Foundation formed under Linux Foundation
• 🤝 Founding supporters: OpenAI, Microsoft, Google, AWS, Anthropic, Block, Cloudflare
• 📖 Open governance: Ensures MCP remains neutral and community-driven
• 🎯 Mission: Prevent fragmentation, accelerate innovation in agentic AI

November 2025: Major Protocol Update

• ⚡ Task-based workflows: Track long-running operations
• 🔐 Streamlined OAuth: URL-based client registration
• 🔄 Asynchronous operations: Better handling of slow tools
• 🆔 Server identity: Improved security and authentication
• 📦 Official extensions: Standardized extension mechanism

New Features in Claude

• 📂 75+ MCP connectors in Claude’s directory
• 🔍 Tool Search: Find tools across many connected servers
• 🤖 Programmatic Tool Calling: Optimized for large-scale deployments

What’s Coming

• 🔮 Managed remote MCP servers (Google Cloud already offers this)
• 🔮 Visual configuration tools
• 🔮 Mobile app support
• 🔮 Enterprise SSO and audit logging

Next Steps

Ready to dive deeper? Here’s your learning path:

Beginner Path

1. ✅ You are here: Introduction to MCP
2. ➡️ Next: Install & Configure MCP Servers
3. ➡️ Then: Filesystem MCP Guide
4. ➡️ Then: GitHub MCP Guide

Developer Path

1. ✅ You are here: Introduction to MCP
2. ➡️ Next: Build Your First MCP Server
3. ➡️ Then: PostgreSQL MCP Guide
4. ➡️ Then: Best MCP Combinations

Power User Path

1. ✅ You are here: Introduction to MCP
2. ➡️ Next: GitHub MCP Guide
3. ➡️ Then: Notion MCP Guide
4. ➡️ Then: Memory MCP Guide

Quick Reference

Essential Commands

# Run any MCP server with npx (no install needed)
npx -y @modelcontextprotocol/server-filesystem /path/to/allow

# Test MCP servers with Inspector
npx @modelcontextprotocol/inspector

# Check Node.js version (v18+ required)
node --version

Config File Locations

Popular MCP Servers

Resources

• 🔗 Official MCP Documentation
• 🔗 MCP Server Registry
• 🔗 MCP GitHub Organization
• 🔗 MCP Discord Community

Summary

MCP (Model Context Protocol) has become the industry standard for AI integrations:

• ✅ Universal standard adopted by OpenAI, Microsoft, Google, and Anthropic
• ✅ 10,000+ servers for every use case imaginable
• ✅ Linux Foundation governance ensures openness and neutrality
• ✅ Secure by design with local execution
• ✅ Easy to use with simple JSON configuration
• ✅ Free and open source forever

The days of copy-pasting context into AI chats are coming to an end. With MCP, your AI assistant becomes a true partner that can access your tools, data, and workflows directly.

Next: Learn how to Install and Configure MCP Servers →

Have questions about MCP? Found an issue with this guide? Contact us or join the MCP community on Discord.