MCP (Model Context Protocol) is an open standard that lets AI models connect to external tools, data sources, and services through a common interface. Instead of writing a custom integration for every AI model and every application, developers implement MCP once, and any MCP-compatible AI client can use it.
A simple way to think about it:
Components
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Host – The AI application (ChatGPT, Claude Desktop, VS Code, Cursor, etc.)
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MCP Client – Connects the host to one or more MCP servers.
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MCP Server – Exposes tools, resources, and prompts.
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Tools – Functions the AI can call.
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Resources – Data the AI can read.
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Prompts – Reusable prompt templates.
Example
Without MCP:
With MCP:
The AI discovers available tools automatically instead of requiring a separate integration for each service.
Common MCP Servers
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Filesystem
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GitHub
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GitLab
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PostgreSQL
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SQLite
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MySQL/MariaDB
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Docker
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Kubernetes
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Slack
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Google Drive
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Notion
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Jira
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Browser automation
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REST APIs
Why developers like MCP
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One standard instead of dozens of custom APIs
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AI can discover available tools dynamically
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Easier maintenance
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Language-independent (Python, C++, Java, Go, C#, Rust, PHP, and others)
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JSON-RPC based communication
For your environment
Since you've been working with:
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Gentoo Linux
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C++
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PHP
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MariaDB
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Ollama
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Local LLMs
you could create an MCP server that exposes:
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MariaDB queries
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PHP project management
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Bash commands
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File editing
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Git operations
Then your local LLM (or ChatGPT, where supported) could perform actions like:
"Show me all PHP files modified today."
"Run my unit tests."
"Query the customer database."
"Commit the changes to Git."
without you writing a different integration for each AI model.
For C++ developers, there are mature MCP SDKs in Python, TypeScript, Java, C#, Go, Rust, PHP, and additional community implementations, while the protocol itself is language-agnostic because it uses JSON-RPC for communication.