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What is MCP (Model Context Protocol)? A Simple and Easy Guide to Connecting to an MCP Server
In today’s rapidly evolving world of artificial intelligence (AI), MCP – Model Context Protocol – is becoming an essential communication standard between users and modern AI models. However, since it’s a relatively new concept, many people – especially those without an IT background – may find it confusing to understand or use. This article will help you clearly grasp what MCP is, why it matters, and how to easily connect to an MCP Server to fully leverage the power of AI models like Claude or ChatGPT.
Table of content
1. What is MCP and Why Should You Care?
MCP – Model Context Protocol is an intermediate protocol that helps AI understand the real-world context behind your requests, rather than just the plain text you type.
Imagine AI as a highly intelligent assistant. But if you don’t provide “context,” it will start fresh with every question. MCP helps the assistant understand:
Who you are
What you're working on
What stage you're at
What outcome you want
More specifically, what can MCP do?
Feature | Explanation |
Maintain context | AI knows you're in a specific workflow (e.g., writing, planning, analyzing data…) |
Multidimensional communication | You can attach instructions, supporting data, and roles for more precise AI responses |
Trigger actions | MCP enables the AI to perform specific actions like opening a URL, reading files, accessing APIs, extracting website info |
Custom AI objectives | You can assign roles to the AI like “Copywriter,” “Data Analyst,” or “Developer” for customized replies |
Here’s a relatable example:
Without MCP (no context): | With MCP (context-aware): |
You: “Summarize the content on this page: https://example.com/article” Such a hassle! You need to manually open the browser, copy a lengthy article, and paste it in. Why? Most current AI models (unless on expensive premium plans) can’t access the internet or fetch live content. They only understand what you type. | You: “Summarize this article: https://example.com/article” -> Open a headless browser -> Visit the page -> Extract the full content like you see it -> Send it to the AI for processing Faster, more convenient – and you don’t lift a finger. |
2. How MCP Works
MCP acts as a middleware between your app and the AI model. It manages:
Session – Keeps conversations coherent and ongoing
Context – Stores user information, tasks, conversation history, input data, etc.
Instructions – Adds custom instructions or roles for the AI to follow
General flow:
User → Claude Desktop (or AI App) → MCP Server → AI Model (Claude, ChatGPT, etc.)
The MCP Server acts as a “context brain,” preparing everything the AI needs to respond accurately.
Choose the right MCP Server depending on the task:
Summarize website content → use mcp-puppeteer
Read local files → use mcp-localfile
Fetch data from APIs → use mcp-http
Analyze spreadsheets → use mcp-excel, etc.
Why is MCP important?
Increases answer accuracy and relevance
Helps AI retain long-term context
Extends AI beyond chatting to real-world actions
Optimizes productivity when using AI at work
3. How to Connect to an MCP Server – Step-by-Step
Hình: tìm hình minh họa về claude desktop
claude-desktop- software-integrated-with-MCP-connectivity
Step 1: Install an MCP-compatible app
Start with an app that supports MCP. A good example is Claude Desktop, which lets you chat with Claude AI right on your computer.
Simply:
Download the app from the official site (available for Windows/macOS)
Run the installer and follow the basic steps
→ That’s it. No complex setup required.
Step 2: Install Node.js
MCP runs on Node.js. If your system doesn’t have it yet:
Visit: https://nodejs.org
Download the LTS (Long-Term Support) version
Install like any regular app
Step 3: Visit MCP’s GitHub page
Scroll to the Pinned section → click "servers"
Step 4: Choose the right MCP for your task
For example, to summarize a website URL → click MCP Puppeteer (uses a browser to load and parse the page)
The page shows full setup instructions
Scroll down to the npx section → copy the configuration JSON
Step 5: Open Claude Desktop and edit config
Go to: File → Settings → Developer → Edit Config
Find the claude_desktop_config.json file → open it in Notepad (or any text editor)
Step 6: Paste the MCP configuration into the config file
Paste the JSON from step 4
Adjust paths or keys if needed (e.g., folder path for local files, API key for APIs)
Save the file (Ctrl + S)
Step 7: Restart Claude Desktop
Completely close and reopen the app
→ It will now load the new MCP configuration
Step 8: Start using MCP features
Once restarted, you’ll see a “wrench” icon indicating MCP tools are active.
Now you can ask:
“Visit https://abc.com and summarize the content”
“Read the file on my desktop and rewrite it in a formal style”
4. Real-World Applications of MCP with AI
4.1 Summarize Web Content (MCP Puppeteer)
Use case: You want the AI to summarize a news article or product page
→ Just provide the URL → AI opens, reads, and extracts insights
Practical uses: SEO writing, news curation, product research, competitor monitoring
4.2 Read and Process Local Files (MCP LocalFile)
Use case: You have a .txt, .pdf, or .docx file and want AI to summarize, edit, or translate it
→ Drag and drop the file → AI handles the rest
Practical uses: Document translation, report writing, contract editing, content improvement
4.3 Analyze Excel Data (MCP Excel)
Use case: You have spreadsheets with financial, sales, or research data
→ AI can understand tables, answer questions, and generate reports
Practical uses: Business analysis, financial summaries, trend visualization, anomaly detection
4.4 Work with APIs (MCP HTTP)
Use case:You’re a developer or working with systems that use APIs
→ AI can send API requests and interpret responses
Practical uses: System integration, API testing, pulling data from CRM/CMS, backend monitoring
4.5 Maintain Workflow Context (MCP Context / Role)
Use case: You want AI to “remember” your task and respond accordingly
→ Define a “work session” with goals, roles, and inputs
Practical uses: Team collaboration with AI, long-term projects, training AI as your personal assistant
This is a big step toward turning AI from a “smart chatbot” into a true productivity partner.
5. No Coding Needed – Great for Non-Tech Users
The best part is you don’t need programming skills to use MCP. With user-friendly apps, you simply fill in details and select the right options. The visual interface makes everything accessible – no need for command lines or technical setup.
6. Conclusion
MCP (Model Context Protocol) is more than just a technical protocol – it’s a powerful tool that helps AI understand you better. Connecting to an MCP Server is now easier and more user-friendly than ever, even for non-technical users. If you work with AI tools like Claude or ChatGPT, this is the upgrade you need to elevate your experience and productivity.
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In today’s rapidly evolving world of artificial intelligence (AI), MCP – Model Context Protocol – is becoming an essential communication standard between users and modern AI models. However, since it’s a relatively new concept, many people – especially those without an IT background – may find it confusing to understand or use. This article will help you clearly grasp what MCP is, why it matters, and how to easily connect to an MCP Server to fully leverage the power of AI models like Claude or ChatGPT.