MCP on Yanmu

Context7 Guide: Help Your AI Coding Assistant Read the Latest Docs

Sat, 02 May 2026 19:51:00 +0800

Overview

Ever had this experience: you ask AI to write some code, it churns out a bunch, then you run it and get errors. Or you call an API that’s clearly documented, but the AI says it “doesn’t exist.”

It’s not that the AI is dumb — it’s that its training data has an expiration date. The data might be months or even years old, and frameworks have been updated several times since.

Context7 solves exactly this. Built by the Upstash team, it fetches the latest official docs when you ask a question, injects them into the AI’s context, and lets the AI answer based on the current version.

Usage is simple: just add use context7 at the end of your prompt. It’s like telling the AI: “Don’t guess — check the latest docs first before answering.”

Why Do You Need It?

💥 One Example Is Enough

Say you want to add a “Back to Top” button to your personal website — when you scroll down, a button appears in the bottom-right corner; click it and you go back to the top.

What AI writes with outdated knowledge: First load a几十 KB third-party library, then write a bunch of code to use it. The feature works, but for a single button, the page gets slower and the code is bloated.

The truth is, it’s much simpler now: Modern browsers already have smooth scrolling and scroll listening built in — a few lines of code, no extra libraries needed.

AI doesn’t know this because it learned from教材 that’s years old.

With use context7, Context7 checks the latest docs and finds that native features are sufficient. So the AI chooses a lighter approach instead of giving you the old clunky solution.

It’s like asking a friend to fix your phone — they try to拆 it from memory, following steps from 3 years ago. The screw positions have changed. If they’d checked the latest tutorial first, they wouldn’t have broken it.

With vs Without Context7

	Without	With
Information source	Stale knowledge in AI’s brain, potentially outdated	Real-time docs fetched from official sources
API accuracy	Often wrong or uses deprecated APIs	Guaranteed to use current version APIs
Code quality	May use outdated patterns from years ago	Follows latest recommended practices
Version handling	Guesses regardless of version	Checks the version you specify

🔄 How It Works

Just a few steps:

You ask a question (add use context7 at the end)
    ↓
Context7 identifies which package you're asking about
    ↓
Fetches the latest content from GitHub and official docs
    ↓
Filters the most relevant snippets, injects them into the AI's "context"
    ↓
AI answers with the latest docs

“Context” is everything the AI can “see” in your current conversation. Injecting docs is like opening a reference book on the table — the AI reads and answers at the same time.

Where does the doc come from? GitHub repos, official doc sites, and llms.txt files (a special doc index format for AI).

After fetching results, Context7 uses an LLM to intelligently rank them and picks the most relevant snippets for you.

Two ways to use it:

Method	Description
MCP Mode (recommended)	Install once, AI coding assistant calls it automatically. MCP is like a plugin for AI — set it and forget it
CLI Manual Mode	Query docs manually in the terminal, for those who like tinkering

Core Capabilities

Smart Matching: You Say the Name, It Finds the Place

When you ask AI how to use a tool, Context7 needs to find the latest manual online. But multiple things can share the same name — it needs to know which one you mean.

Common names it can identify on its own. For ambiguous or common names, use the owner/repo format to be precise:

`1`	`Use /tailwindlabs/tailwindcss to add a navbar to my page. use context7`

Here tailwindlabs is the author name, tailwindcss is the project name. Like searching for “Apple” — it could be fruit or a phone. Be specific and you won’t go wrong.

Supported Libraries

All popular ones are included: React, Next.js, Vue, Tailwind CSS, Express, Prisma, Supabase, TypeScript… Full list at context7.com/rankings.

Version Awareness

Different versions can have vastly different APIs. Just specify the version and Context7 will fetch docs for that version:

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Write a counter with Vue 3. use context7
Write an API route using Next.js 14's Pages Router. use context7
Configure dark mode with Tailwind CSS v4. use context7

If you ask for an iPhone 12 teardown guide, nobody will hand you the iPhone 15 version.

Installation

One-Click Install

`1`	`npx ctx7 setup`

npx comes with Node.js, no extra installation needed. If you haven’t installed Node.js yet, go to nodejs.org to download it — once installed, you’ll have npx.

Running it will:

Open a browser for you to log in and authorize (OAuth)
Generate an API Key (your “identity credential”)
Auto-configure your editor

Three steps and you’re done.

To specify an editor, add a parameter:

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npx ctx7 setup --claude      # Claude Code
npx ctx7 setup --cursor      # Cursor
npx ctx7 setup --opencode    # OpenCode

Uninstall: npx ctx7 remove

Manual Configuration

If auto-install doesn’t work, manually add the MCP Server:

{
  "mcpServers": {
    "context7": {
      "url": "https://mcp.context7.com/mcp",
      "headers": {
        "CONTEXT7_API_KEY": "your API key"
      }
    }
  }
}

Configuration file locations for different tools (~ represents your user directory, e.g., C:\Users\yourusername on Windows):

Tool	Config Location
Cursor	Settings → MCP, or `~/.cursor/mcp.json`
Claude Code	`~/.claude/settings.json` (global) or `.claude/settings.json` (project)
Windsurf	Settings → Cascade → MCP servers
Cline	VS Code extension → MCP Servers → Configure
OpenCode	Project root `opencode.json`

Get your API Key at context7.com/dashboard. Format is ctx7sk..., free users get quota too.

✅ Verification

Send a test:

`1`	`Write a counter webpage with a button. use context7`

If the AI gives clean, modern code without loading extra libraries, it’s working.

Usage

Basic Usage

Add use context7 at the end of your prompt:

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Write a clean personal resume page. use context7
Write a countdown tool that counts down from a given number of seconds. use context7

Specify a Library Precisely

Use the /owner/repo format to skip name matching:

`1`	`Use /tailwindlabs/tailwindcss to add a navbar to my page. use context7`

Recommended when the library name is ambiguous.

Specify a Version

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Write a card layout using Bootstrap 4 instead of 5. use context7
Write a todo list using Vue 3's Composition API. use context7

Combine Multiple Libraries

`1`	`Build an icon showcase page with Bootstrap + Font Awesome. use context7`

Configure Auto-Trigger

If you don’t want to type use context7 every time, configure it in your rules file:

→ Cursor in .cursorrules:

`1`	`When user questions involve third-party framework/library API usage, automatically use Context7 to query the latest docs.`

→ Claude Code in CLAUDE.md:

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## Documentation Query Rules
- For third-party libraries/frameworks, first use Context7 to query latest docs
- Prioritize generating code based on Context7 results

CLI Commands

If you only use Context7 in AI conversations, you can skip this. CLI is for those who like terminal commands.

npm is Node.js’s built-in package manager, -g means “global install” — install once, use everywhere.

# Install CLI
npm install -g ctx7

# Search libraries
ctx7 library react
ctx7 library nextjs "middleware"

# Get docs
ctx7 docs /facebook/react "hooks state management"
ctx7 docs /vercel/next.js "middleware authentication"

# Skills management
ctx7 skills search        # Search available Skills
ctx7 skills install       # Install Skill
ctx7 skills list          # View installed
ctx7 skills remove        # Uninstall

# Authentication
ctx7 login                # Login
ctx7 whoami               # View status
ctx7 logout               # Logout

❓ FAQ

How is this different from AI’s built-in web search?

Web search returns blog posts and forum threads of varying quality — you still have to judge credibility yourself. Context7 only pulls from official docs, uses an LLM to filter the most relevant snippets, and feeds them directly to the AI.

💰 Will `use context7` cost more?

No. Although there’s an extra doc lookup step, the AI gets accurate information so it doesn’t have to guess, rewrite, or produce long, buggy code. Overall token consumption is actually lower.

What if my library isn’t listed?

Go to context7.com and click “Add Docs” to submit it, or skip use context7 and let the AI fall back to its own knowledge.

I installed it but it doesn’t work?

Check these one by one:

Did npx ctx7 setup report any errors
Is the MCP config JSON format correct (even one extra comma will break it)
Is the API Key valid (starts with ctx7sk...)
Did you completely close and reopen your editor
Is the MCP status light green
Did you include use context7 in your prompt

Does it affect response speed?

It adds one or two seconds of wait time, but you get accurate answers without back-and-forth corrections. One debug-compile-fix cycle takes way longer than that.

Summary

Item	Content
What it is	A platform providing real-time, up-to-date documentation for AI coding assistants
Problem it solves	AI giving incorrect code due to outdated training data
Core principle	Fetch official docs in real-time, inject into AI context
Installation	`npx ctx7 setup` — one command and done
Usage	Add `use context7` at the end of your prompt
Pricing	Free tier available, sufficient for personal use
Website	context7.com
GitHub	github.com/upstash/context7

Once installed, you’ll never have to worry about AI giving you outdated knowledge again.

OpenCode In-Depth Guide: Installation, Configuration, and Advanced Techniques for the Open-Source Claude Code

Thu, 30 Apr 2026 02:00:15 +0800

📋 Table of Contents

1. What is OpenCode?

OpenCode is currently the hottest AI programming tool, essentially an open-source version of Claude Code. It has replicated almost all core features of Claude Code while solving common pain points for Chinese users such as rate limiting and account bans.

Comparison with Claude Code

Dimension	Claude Code	OpenCode
Open Source	❌ Closed source	✅ Open source
Free models	❌ Paid API required	✅ Built-in free models
China-friendly	⚠️ Rate limit/ban risk	✅ No restrictions
Skills/MCP	✅ Supported	✅ Fully compatible
Session parallelism	❌	✅ Core highlight

Core Positioning

Open-source Claude Code: Nearly all features, China-friendly, no rate limits or bans
Free models: Out-of-the-box GLM-4.7, MiniMax-2.1 and other free models, zero configuration needed
Top-tier model integration: Free access to Gemini 3 Pro and Claude 4.5 Opus via Antigravity plugin; GPT Codex via /connect
Killer features: Session parallelism, Timeline rollback, Share, Ultra Work multi-agent collaboration
Plugin ecosystem: Oh My Open Code (OMO) with seven programming agents + three MCP Servers + various tools

2. Four Installation Forms

⭐ 1. Command Line Version (Primary Recommendation)

The most stable and feature-complete way to use it.

# Install (Node.js required first)
npm i -g opencode-ai

# Launch
opencode

Prerequisite: Node.js must be installed (download from nodejs.org)

2. Desktop Client (Beta)

Download the client from the official website, install it, and select your project folder.

⚠️ Currently in Beta testing phase with more bugs — not recommended as your primary tool yet.

3. VS Code Plugin Version

Prerequisite: OpenCode CLI must be installed. The plugin’s core value lies in seamless IDE integration, letting AI directly perceive your code context.

Search for OpenCode in the VS Code Extensions marketplace and install it
Shortcut Ctrl + Shift + P → type open opencode and press Enter
The plugin automatically associates with code files open in the left panel
Select code and press Ctrl + Alt + K to quickly paste into the OpenCode chat window

4. Cloud Runtime Environment (GitHub Actions)

Perfect for automated Issue fixing in open-source projects:

Upload your project to a public GitHub repository
Configure API Key in the repository (Settings → Secrets and Variables → Actions)
Type /opencode + requirement description in an Issue comment
GitHub Actions automatically runs the OpenCode workflow
Automatically creates a Pull Request upon completion

3. Free Model Configuration

View Available Models

`1`	`/models # View all available models (ones marked "free" can be used at no cost)`

Recommended Free Models

Model	Features
GLM-4.7	Strong programming ability, zero configuration
MiniMax-2.1	Excellent programming skills, fast response

💡 These two free models are more than enough for beginners practicing AI programming.

Connect Top-tier Models

Method 1: Antigravity Plugin (Free Gemini + Claude Access)

Antigravity is Google’s AI programming IDE, generously providing Gemini 3 Pro and Claude 4.5 Opus for free.

Paste the installation prompt in OpenCode (copy from the Antigravity GitHub homepage)
Wait for AI to complete the installation automatically
Open a new terminal and run the login command, select Google → Antigravity login
Log in to your Google account, paste the generated URL
Restart OpenCode — Gemini 3 Pro and Claude 4.5 Opus will appear in /models

Method 2: GPT Codex (Official OpenAI Partnership)

OpenAI has officially partnered with OpenCode, enabling direct ChatGPT Codex integration.

`1`	`/connect # Select OpenAI → GPT Pro → Browser login`

Prerequisite: ChatGPT Plus subscription or higher required.

Method 3: OpenRouter (Universal Connector)

OpenRouter provides access to virtually every major model available, and Chinese users can easily obtain credits.

`1`	`/connect # Select OpenRouter → Enter API Key`

OpenCode supports 75 AI integration methods, covering almost all model providers.

4. Core Feature Highlights

1. Clarifying Questions Before Coding

Before starting to code, OpenCode will ask you a series of questions:

Do you just need a code sample, or a complete runnable program?
Which features are must-haves?
Which model should be used?
How should environment variables be stored?

This “ask first, act later” mechanism significantly reduces rework.

2. Command Line Code Diff Interface

OpenCode’s command line diff display is considered the best among all command line programming tools, making code changes clear at a glance.

⭐ 3. Session Parallel Processing

This is OpenCode’s most distinctive feature — multiple Sessions running in parallel:

# Start the first task (e.g., add a timer)
# While the task is running, create a new session
/new

# Start the second task (e.g., brush color)
# View all session statuses
/sessions

# Switch between sessions
/session <id>

The spinning symbol indicates a Session is running in the background. Two tasks can be developed in parallel without interfering with each other.

4. Timeline Checkpoint Rollback

`1`	`/timeline # View the complete conversation history of the current Session`

Select any historical node:

Revert: Roll back both code and chat content to that point in time
View: See what modifications the AI made at that time

Like a “time machine” for programming, allowing you to boldly try different approaches.

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/share      # Share conversation history as a web page
/unshare    # Stop sharing
/export     # Export conversation history as a file

After sharing, a web link is generated displaying the complete conversation history and code modification process, convenient for collaboration or demonstration.

5. Skills Migration

OpenCode is fully compatible with Claude Code’s Skills directory structure, making migration extremely easy:

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# Directory structure mapping
.claude/skills/<skill-name>/    →    .opencode/skills/<skill-name>/

Steps

Create a new .opencode folder in the project root directory
Create a skills folder inside .opencode
Copy the skill folders from .claude/skills/ directly into it
Restart OpenCode — the AI will recognize and call these Skills

Each Skill is essentially an instruction manual with its own directory, telling the AI how to complete tasks in a specific domain.

6. MCP Configuration

OpenCode supports two MCP (Model Context Protocol) modes:

Local MCP

Executed via local commands. Configure in ~/.config/opencode/opencode.json:

{
  "mcpServers": {
    "shed-cn": {
      "type": "local",
      "command": "npx",
      "args": ["shed-cn"],
      "enabled": true
    }
  }
}

Remote MCP

Called remotely via URL. Using Context7 as an example:

{
  "mcpServers": {
    "context7": {
      "type": "remote",
      "url": "https://context7-mcp-server-url",
      "headers": {
        "Authorization": "Bearer <your-api-key>"
      },
      "enabled": true
    }
  }
}

After configuration, restart OpenCode and enter /mcp to view configured MCP Servers.

7. Oh My Open Code (OMO) Super Plugin ⭐

OMO is the most popular programming plugin for OpenCode, essentially a bundled package of Tools + MCP + Programming Agents.

Seven Programming Agents

Agent	Role	Recommended Model
🧠 Sisyphus	Main agent, planning & orchestration	Claude 4.5 Opus / GPT 5.2
🔮 Prophet	Architecture design, code review	—
📚 Librarian	Literature review, document retrieval	—
🔍 Explorer	Web search	—
🎨 Frontend Engineer	Frontend development	Gemini 3 Pro
📝 Document Writer	Document generation	—
🖼️ Multimodal	Image/PDF understanding	—

Each agent is assigned the most suitable model for its work. The author reportedly spent $24,000 worth of Tokens to find the optimal combination.

Three MCP Servers

Web Search: Web search
Context7: Access latest technical documentation
Grep App: Fast code search across GitHub repositories

Integrated Tools

LSP Advanced: Helps AI quickly locate code through language syntax and semantics
AST Tool: Related search through code syntax trees
LOC Tool: Understand images and PDFs via multimodal vision
Delegate Task / Background Task: Agent task assignment and background scheduling

Installation and Usage

Configuration file location: C:\Users\<username>\.config\opencode\oh-my-opencode.json

Copy the install prompt from the OMO GitHub homepage
Paste it into OpenCode and answer configuration questions (subscription status, etc.)
Installation completes automatically

Two Core Usage Patterns

① @ Designate Specific Agent

`1`	`@Frontend Engineer Help me optimize the responsive layout of this page`

② Ultra Work Mode (Magic Word ULW)

`1`	`ULW Help me create a pet store application`

In Ultra Work mode, Sisyphus as the main agent will:

Break down tasks into a Todo List
Launch multiple background tasks running in parallel
Orchestrate all agents from the center
Deliver the complete project

Ralph Loop Mode

Forces AI to work in continuous loops, suitable for extremely difficult tasks:

`1`	`/ralph-loop`

Example: “Refactor the entire project using the latest Spring Boot 4 standards until all test cases pass” — can run for hours until the task is complete.

8. Other Useful Features

`/init` — Project Knowledge Initialization

Let AI read through the entire project folder, generating an agents.md file as a system prompt to help AI quickly understand the project.

`/compact` — Context Compression

Refine previous conversations into a concise summary, freeing up the model’s context window to avoid Token overflow.

Custom Commands

Create .md files under ~/.config/opencode/commands/ to define custom commands:

# Run Tests
Mode: build
Command: npm test
Description: Run all test cases for the project

Usage: /Run Tests to trigger.

Custom Agents

Create .md files under ~/.config/opencode/agents/:

# Code Review Agent
Type: subagent
Model: claude-4.5-opus
Description: Specializes in code review, checking code quality, security vulnerabilities, and best practices.

Primary Agent: Switch with Tab key, use directly in conversation
Sub Agent: Automatically dispatched by the main agent in the background

9. Summary and Recommendations

Use Cases

Scenario	Rating	Notes
Beginner AI programming	⭐⭐⭐⭐⭐	Free models, zero-cost start
Daily development assistance	⭐⭐⭐⭐⭐	Session parallelism + Timeline rollback
Complex project development	⭐⭐⭐⭐⭐	OMO plugin multi-agent collaboration
Open-source project maintenance	⭐⭐⭐⭐	GitHub Actions cloud automation
Skills/MCP practice	⭐⭐⭐⭐⭐	Fully compatible with Claude Code ecosystem

Recommended Configuration Path

Beginner → CLI installation + built-in free models
  ↓
Advanced → Configure Antigravity for Gemini/Claude access
  ↓
Efficient → Configure Skills + MCP
  ↓
Ultimate → Install OMO plugin, enable Ultra Work mode

OpenCode breaks down the high barriers of AI programming tools, allowing everyone to explore the infinite possibilities of AI-assisted programming at zero cost. Especially for Chinese users, there’s no longer any need to worry about rate limits and bans — you can “build freely, experiment freely.”

10. Hands-on Record: Installing Oh My OpenAgent

Below is the complete conversation record from personally installing Oh My OpenAgent (formerly Oh My Open Code), in a Windows + PowerShell environment.

Environment Check

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opencode --version
# Output: 1.14.39

Installation Process

Tell AI directly in an OpenCode conversation:

“Install and configure oh-my-openagent by following the instructions here: https://raw.githubusercontent.com/code-yeongyu/oh-my-openagent/refs/heads/dev/docs/guide/installation.md"

AI will first ask about your model subscriptions:

Subscription	My Status
Claude Pro/Max	❌ None
OpenAI / ChatGPT Plus	❌ None
Gemini	❌ None
GitHub Copilot	✅ Student certified
OpenCode Zen	✅ Free available
Z.ai Coding Plan	❌ None
OpenCode Go	❌ None
Kimi for Coding	❌ None
Vercel AI Gateway	❌ None

⚠️ AI will prompt “Without a Claude subscription, the Sisyphus agent might not work ideally” — but GitHub Copilot will automatically take over as a fallback model.

After confirming subscriptions, AI automatically executes the installation command:

bunx oh-my-openagent install --no-tui \
  --claude=no --openai=no --gemini=no \
  --copilot=yes --opencode-zen=yes \
  --zai-coding-plan=no --opencode-go=no \
  --kimi-for-coding=no --vercel-ai-gateway=no

Successful installation output:

[1/4] Checking OpenCode installation...
[OK] OpenCode 1.14.39 detected
[2/4] Adding oh-my-openagent plugin...
[OK] Plugin added -> C:\Users\<username>\.config\opencode\opencode.json

Post-Installation Configuration Files

Main configuration file ~/.config/opencode/opencode.json:

{
  "plugin": [
    "oh-my-openagent@latest"
  ]
}

Agent model configuration ~/.config/opencode/oh-my-openagent.json:

AI automatically assigned models based on GitHub Copilot subscription:

Agent	Assigned Model
Sisyphus (Main agent)	`github-copilot/claude-opus-4.7`
Oracle (Prophet)	`github-copilot/gpt-5.5` (medium)
Other Agents	Auto-selected from Copilot available models

Authentication Configuration

After installation, you need to manually authenticate GitHub Copilot:

`1`	`opencode auth login`

Interactive steps:

Use arrow keys to select GitHub Copilot
Press Enter to confirm
Browser opens automatically, log in to your GitHub student account
Authorization complete, terminal shows successful authentication

How to Reconfigure Agent Models?

Method 1: Tell AI Directly

“Change Sisyphus’s model to claude-sonnet-4.6” “Oracle use gpt-5.5”

Method 2: Manually Edit Configuration File

Directly modify the model field for the corresponding agent in ~/.config/opencode/oh-my-openagent.json.

Additional Configuration: Add OpenCode Zen as Fallback

The free OpenCode Zen was missed during installation (--opencode-zen=no). In a new OpenCode conversation, ask AI to fix it:

“I also have your free OpenCode Zen, but I’ve already logged into GitHub Copilot — help me modify it”

AI’s first attempt set OpenCode Zen as primary (opencode/claude-opus-4-7), making GitHub Copilot the fallback. The actual need was the opposite:

“No, GitHub Copilot should be primary, and OpenCode Zen’s built-in free model as fallback”

After AI corrected it, the final configuration strategy:

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Primary model: github-copilot/*     (paid, use first)
Fallback model: opencode/*          (free credits, auto-switch when Copilot unavailable)

Key configuration snippet (using Sisyphus as example):

{
  "sisyphus": {
    "model": "github-copilot/claude-opus-4-7",
    "fallback_models": [
      { "model": "opencode/claude-opus-4-7" },
      { "model": "opencode/gpt-5.5" }
    ]
  }
}

💡 Tip: When describing configuration needs, make the primary/secondary relationship clear — “XX as primary, YY as fallback” — to avoid AI getting it reversed.

Usage Tips

After installation, type opencode in the terminal to get started:

Include ultrawork or ulw in your prompt to trigger automatic parallel processing
Press Tab to enter Prometheus (planner) mode
Run /start-work to execute full orchestration

Appendix: Troubleshooting Notes

Issue	Solution
`doctor` command timeout (30s)	Some checks may hang; add `--verbose` to troubleshoot, or skip — it doesn’t affect usage
PowerShell `if` syntax errors	OpenCode’s bash commands need syntax conversion under PowerShell
Sisyphus performance drops with non-Claude models	This is a known limitation; experience is best with a Claude subscription
AI swaps primary/fallback models	State the primary/secondary relationship clearly: “XX as primary, YY as fallback” — don’t just say “add YY for me”

📚 Sources: Tech Shrimp - OpenCode Detailed Guide, Oh My OpenAgent Installation Guide

MCP Beginner's Guide: The Universal AI Plug Anyone Can Understand

Mon, 01 Dec 2025 01:46:03 +0800

Overview

Have you ever thought: ChatGPT, Claude and other AIs are smart, but they can only chat in a dialog box — they can’t help you check your calendar, manage files, or operate databases because they’re “locked in a cage” with no access to the outside world.

MCP (Model Context Protocol) is here to break down that wall.

Simply put, MCP is an open standard protocol that enables AI applications to connect to external systems — files, databases, APIs, various tools — just like giving AI a universal plug (USB-C port). Plug in anything and it works.

One sentence to understand MCP: It’s the “USB-C port” for the AI world — a unified standard, plug and play.

Why Use MCP?

Before MCP

Before MCP existed, if you wanted to connect AI to external tools (like checking the weather, reading calendars, operating databases), each AI application and each tool required custom integration development.

This was like the early days of phone charging ports — one for Android, one for Apple, one for Type-C. Every time you switched devices, you needed a new cable.

The problems were obvious:

High development costs: Every integration started from scratch
Not universal: Tools written for Claude couldn’t be used by ChatGPT
Difficult to maintain: When a tool was upgraded, all integrations had to be changed

After MCP

MCP defines a unified standard:

Tool providers develop an MCP Server following the MCP standard
AI applications act as MCP Clients to connect to it
As long as both sides follow the MCP protocol, plug and play, no redundant development

This is like how USB-C unified charging ports — one cable to rule them all.

What Can MCP Do? Use Cases at a Glance

1. Personal AI Assistant

Let AI help you manage your daily life:

Connect Google Calendar to check schedules and create meeting reminders
Connect Notion to organize notes and manage to-do lists
Connect Gmail to read and reply to emails
Connect Slack to summarize chat history

Example: You tell the AI “check what meetings I have tomorrow and summarize last week’s project progress notes” — the AI can automatically check your calendar, go through Notion, and give you a summary.

2. Programming & Development

Let AI coding assistants actually “get their hands dirty”:

Connect to the local file system via MCP to read and write project files
Connect to databases to directly query and modify data
Connect to GitHub to automatically create Issues and submit PRs
Connect to Figma to generate code directly from design mockups

Example: Claude Code connects to Figma via MCP, obtains the design mockup, and generates a complete web application.

3. Enterprise Applications

Make a big impact in the corporate world:

Connect to multiple databases so employees can query business data in natural language
Connect to internal systems (CRM, ERP) for AI to automatically compile reports
Connect to knowledge bases so AI can answer questions based on company documentation

4. Creative & Design

Connect to Blender to let AI generate 3D models
Connect to 3D printers to print designs directly
Connect to video editing tools to automate the editing workflow

MCP Core Architecture

MCP’s architecture is very simple, with only three roles:

┌──────────────┐         ┌──────────────┐         ┌──────────────┐
│  AI App      │ ◄─────► │  MCP Protocol │ ◄─────► │ MCP Server   │
│ (MCP Client) │         │ (Transport)   │         │ (External    │
└──────────────┘         └──────────────┘         │  Tool)       │
                                                   └──────────────┘

Role	Description	Analogy
MCP Client	AI applications (Claude, ChatGPT, Cursor)	Phone
MCP Server	Services providing specific capabilities (weather, file management)	Charger
MCP Protocol	The “language” both sides communicate in	USB-C Standard

What Can an MCP Server Provide?

An MCP Server can expose three types of capabilities to AI:

Type	Description	Examples
Tools	Functions/operations AI can call	Search the web, send emails, query databases
Resources	Data AI can read	File contents, database records, API responses
Prompts	Preset prompt templates	Code review templates, translation templates

How to Use MCP?

Method 1: Use Existing MCP Servers (Recommended for Beginners)

This is the simplest approach — others have already written the MCP Server, you just need to “install and connect”.

Step 1: Find the MCP Server You Need

The MCP ecosystem already has a large number of Servers available. Common sources:

Official repository: github.com/modelcontextprotocol/servers
MCP marketplaces: mcp.so, smithery.ai
GitHub search: Search for mcp-server

Popular MCP Servers:

MCP Server	Function
`filesystem`	Read and write local files
`github`	Operate GitHub (Issues, PRs)
`fetch`	Fetch web page content
`sqlite`	Operate SQLite databases
`notion`	Operate Notion notes
`memory`	Persistent memory storage

Step 2: Configure MCP Server in Your AI Application

Using Claude Desktop as an example, find the configuration file:

Windows: %APPDATA%\Claude\claude_desktop_config.json
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

Add MCP Server configuration (using filesystem as an example):

{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-filesystem",
        "/your/work/directory/path"
      ]
    }
  }
}

After saving, restart Claude Desktop, and the AI will have file management capabilities.

Step 3: Start Using

After restarting, simply ask the AI to use these tools in conversation:

“Create a notes folder in my work directory”
“Read the README.md content and give me a summary”
“Search for recent project Issues”

The AI will automatically call the corresponding MCP Server to complete the task.

Method 2: Use MCP in Cursor / VS Code

If you use Cursor or VS Code for programming development, the configuration is similar.

Create .cursor/mcp.json (Cursor) or .vscode/mcp.json (VS Code) in your project root:

{
  "mcpServers": {
    "fetch": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-fetch"]
    },
    "sqlite": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-sqlite", "./data.db"]
    }
  }
}

After configuration, you can use these tools in AI conversations.

Method 3: Develop Your Own MCP Server (Advanced)

If you want to connect AI to your own systems (like a company’s internal API), you can write your own MCP Server.

MCP supports multiple programming languages with official SDKs:

Language	SDK
TypeScript	`@modelcontextprotocol/sdk`
Python	`mcp` (PyPI)
Java / Kotlin	`io.modelcontextprotocol`

Minimal example (TypeScript):

import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";

const server = new McpServer({
  name: "my-server",
  version: "1.0.0"
});

// Define a "check weather" tool
server.tool(
  "get_weather",
  { city: z.string().describe("City name") },
  async ({ city }) => {
    // Your business logic here
    const weather = `${city} is sunny today, 25°C`;
    return {
      content: [{ type: "text", text: weather }]
    };
  }
);

// Start the service
const transport = new StdioServerTransport();
await server.connect(transport);

Once written, configure it in your AI application and start using it.

Which AI Applications Support MCP?

MCP has become an industry standard, with mainstream AI applications offering support:

AI Application	Support Status
Claude Desktop / Claude Code	Native support
ChatGPT	Supported
Cursor	Supported
VS Code (Copilot)	Supported
Windsurf	Supported
OpenCode	Supported

Configure once, use everywhere — an MCP Server configured in Claude will work in other applications too.

FAQ

Q: What’s the difference between MCP and APIs?

An API is a “private protocol” between two parties, with each API having different calling methods. MCP is a unified standard — all tools that follow MCP can be called by AI in the same way. Think of MCP as “a standard API layer specifically for AI.”

Q: Do I need programming skills to use MCP?

No! If you’re just using existing MCP Servers, you only need to know how to copy and paste configuration files. Programming is only needed when developing your own MCP Server.

Q: Is MCP secure?

MCP Servers run locally by default, and data is not uploaded to the cloud. However, when using third-party MCP Servers, it’s recommended to check their source code and permissions to ensure security.

Q: What environment does an MCP Server need to run?

Most MCP Servers run on Node.js, so you need to install Node.js first. Python-based Servers require a Python environment.

Summary

Question	Answer
What is MCP?	A unified standard protocol for AI to connect to external tools
Why use it?	To let AI actually “do work” instead of just chatting
Who can use it?	Everyone — beginners use existing Servers, developers can write their own
How to use it?	Find an MCP Server → Configure it in your AI app → Restart and use

The essence of MCP is: creating a unified “plug standard” for the AI world, allowing tools and AI to connect freely.

Further reading:

MCP Official Documentation

MCP Server Repository

MCP Marketplace

MCP on Yanmu

Context7 Guide: Help Your AI Coding Assistant Read the Latest Docs

Overview

Why Do You Need It?

💥 One Example Is Enough

With vs Without Context7

🔄 How It Works

Core Capabilities

Smart Matching: You Say the Name, It Finds the Place

Supported Libraries

Version Awareness

Installation

One-Click Install

Manual Configuration

✅ Verification

Usage

Basic Usage

Specify a Library Precisely

Specify a Version

Combine Multiple Libraries

Configure Auto-Trigger

CLI Commands

❓ FAQ

How is this different from AI’s built-in web search?

💰 Will use context7 cost more?

What if my library isn’t listed?

I installed it but it doesn’t work?

Does it affect response speed?

Summary

OpenCode In-Depth Guide: Installation, Configuration, and Advanced Techniques for the Open-Source Claude Code

📋 Table of Contents

1. What is OpenCode?

Comparison with Claude Code

Core Positioning

2. Four Installation Forms

⭐ 1. Command Line Version (Primary Recommendation)

2. Desktop Client (Beta)

3. VS Code Plugin Version

4. Cloud Runtime Environment (GitHub Actions)

3. Free Model Configuration

View Available Models

Recommended Free Models

Connect Top-tier Models

Method 1: Antigravity Plugin (Free Gemini + Claude Access)

Method 2: GPT Codex (Official OpenAI Partnership)

Method 3: OpenRouter (Universal Connector)

4. Core Feature Highlights

1. Clarifying Questions Before Coding

2. Command Line Code Diff Interface

⭐ 3. Session Parallel Processing

4. Timeline Checkpoint Rollback

5. Share

5. Skills Migration

Steps

6. MCP Configuration

Local MCP

Remote MCP

7. Oh My Open Code (OMO) Super Plugin ⭐

Seven Programming Agents

Three MCP Servers

Integrated Tools

Installation and Usage

Two Core Usage Patterns

① @ Designate Specific Agent

② Ultra Work Mode (Magic Word ULW)

Ralph Loop Mode

8. Other Useful Features

/init — Project Knowledge Initialization

/compact — Context Compression

Custom Commands

Custom Agents

9. Summary and Recommendations

Use Cases

Recommended Configuration Path

10. Hands-on Record: Installing Oh My OpenAgent

Environment Check

Installation Process

Post-Installation Configuration Files

Authentication Configuration

How to Reconfigure Agent Models?

💰 Will `use context7` cost more?

`/init` — Project Knowledge Initialization

`/compact` — Context Compression