The Model Context Protocol (MCP) is an open standard that lets AI assistants connect to external tools, data sources, and services. Instead of AI being trapped inside a chat window, MCP gives it hands to actually do things.
What Problem Does MCP Solve?
AI assistants like Claude, ChatGPT, and Copilot are powerful—but isolated. They can write code, answer questions, and generate content. What they can’t do (without help) is:
- Read your actual files and databases
- Execute commands on your systems
- Connect to your business tools
- Take actions in the real world
You end up copy-pasting between the AI and wherever the work actually happens. The AI writes a blog post, you paste it into WordPress. The AI suggests a database query, you run it manually. The AI drafts an email, you send it yourself.
MCP eliminates the copy-paste. It creates a standardized way for AI to discover what tools are available and use them directly.
How MCP Works
The Model Context Protocol has three core components:
1. MCP Servers
An MCP server exposes capabilities that AI can use. It might provide access to:
- A filesystem (read and write files)
- A database (query and update records)
- An API (call external services)
- A CMS like WordPress (manage content)
Each server publishes a list of “tools” (actions it can perform) and “resources” (data it can provide). Any MCP-compatible AI client can discover these automatically.
2. MCP Clients
The AI assistant acts as an MCP client. When you connect it to an MCP server, it:
- Discovers available tools and resources
- Understands what each tool does (from descriptions)
- Decides when to use them based on your requests
- Executes tool calls and handles the results
Popular MCP clients include:
- Claude Desktop — Anthropic’s official app
- Cursor — AI-powered code editor
- VS Code + Copilot — GitHub’s AI assistant
- OpenClaw — Open-source AI agent framework
- Cline — VS Code extension for Claude
3. The Protocol
MCP defines how clients and servers communicate:
- JSON-RPC 2.0 — Message format
- Capability negotiation — Client and server agree on features
- Tool schemas — Describe inputs, outputs, and behavior
- Resource URIs — Standard way to reference data
The protocol is transport-agnostic—it works over stdio, HTTP, WebSockets, or any other channel.
MCP vs. Function Calling vs. Plugins
You might be thinking: “Don’t AI tools already have plugins and function calling?” Yes, but MCP is different:
| Approach | Pros | Cons |
|---|---|---|
| ChatGPT Plugins | Easy to use | OpenAI-only, limited to their marketplace |
| Function Calling | Flexible | You build everything yourself |
| Custom APIs | Full control | Different for every AI, no standard |
| MCP | Open standard, works with any compatible AI | Newer, still growing ecosystem |
The key advantage: build once, use everywhere. An MCP server works with Claude, Cursor, OpenClaw, and any future AI that supports the protocol. No vendor lock-in.
What Can You Build with MCP?
MCP servers exist for almost anything you’d want AI to control:
Development & DevOps
- Filesystem — Read, write, search files
- Git — Manage repositories, commits, branches
- Docker — Control containers
- Databases — PostgreSQL, MySQL, SQLite queries
- Cloud — AWS, GCP, Kubernetes operations
Productivity
- Google Workspace — Gmail, Calendar, Drive
- Slack — Send messages, read channels
- Notion — Manage pages and databases
- Linear/GitHub — Issue tracking, project management
Content & Web
- WordPress — Create posts, manage sites, update content
- Web scraping — Fetch and parse web pages
- Search — Brave, Google, specialized searches
Data & Research
- RAG systems — Query vector databases
- APIs — Connect to any REST/GraphQL service
- Memory — Persistent knowledge bases
Getting Started with MCP
The fastest way to try MCP:
Option 1: Claude Desktop
- Download Claude Desktop
- Open Settings → Developer → Edit Config
- Add an MCP server (filesystem is a good start)
- Restart Claude and start using your files
Option 2: OpenClaw
- Install:
npm install -g openclaw - Configure your AI provider
- Add MCP servers to your config
- Start chatting with tool access
Option 3: Build Your Own Server
The MCP SDK is available for:
- TypeScript/JavaScript
- Python
- Rust
- Go (community)
A basic server takes ~50 lines of code.
MCP for WordPress
If you manage WordPress sites, MCP changes how you work.
The WordPress MCP Adapter turns any WordPress installation into an MCP server. Once connected, your AI assistant can:
- Create, edit, and publish posts
- Manage pages, categories, and tags
- Update plugins and themes
- Configure site settings
- Query content and generate reports
- Handle WooCommerce products and orders
Instead of logging into dashboards, you tell your AI what you want in plain English. It handles the WordPress mechanics.
Get Started with WordPress MCP →
The Future of MCP
MCP is still early, but momentum is building:
- Anthropic created it and uses it in Claude
- Cursor has native MCP support
- WordPress shipped an official MCP Adapter
- Hundreds of servers are available on GitHub
As AI assistants become more capable, the bottleneck shifts from “what can AI do?” to “what can AI access?” MCP solves the access problem with an open standard anyone can implement.
The protocol will likely evolve—better auth, streaming, multi-modal support—but the core idea is here to stay: give AI a standard way to connect to the world.