# My Top 3 MCP Servers for 2025

As AI agents become more capable, they need secure, structured ways to interact with real-world systems, such as databases, filesystems, APIs, and developer tools. That’s where **MCP servers** come in.

### **🧠 What is MCP?**

**MCP (Model Context Protocol)** is an open protocol that enables AI models to interact with external systems in a controlled, predictable, and auditable way. MCP servers bridge your AI agent and the tools it needs, such as GitHub repositories, SQL databases, or Redis streams.

🔗 *Explore more:* [Awesome MCP Servers](https://github.com/punkpeye/awesome-mcp-servers) — a curated list of production-ready, community-maintained servers.

## **🚀 My Top 3 MCP Servers**

### **1\. 🔍 Context7 MCP — Instant, Version-Aware Code Docs**

Tired of outdated or hallucinated examples from your LLM?

[**Context7**](https://github.com/upstash/context7) injects fresh, version-specific documentation directly into your agent’s prompt context. It’s like giving your AI assistant real-time access to the right docs — no tabs, no guesswork.

```json
{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": ["-y", "@upstash/context7-mcp@latest"]
    }
  }
}
```

**How it works:**

* Context7 fetches live documentation and usage examples based on the exact version.
    
* The result? More accurate, context-aware responses from your AI.
    

---

### **2\. 🧑‍💻 GitHub MCP — First-Party Integration for Dev Workflows**

The [**GitHub MCP server**](https://github.com/github/github-mcp-server) provides structured access to GitHub resources — issues, PRs, repositories, and workflows — all via a secure interface.

```json
{
  "mcpServers": {
    "github": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "GITHUB_PERSONAL_ACCESS_TOKEN",
        "ghcr.io/github/github-mcp-server"
      ],
      "env": {
        "GITHUB_PERSONAL_ACCESS_TOKEN": "gho_*********"
      }
    }
  }
}
```

**Why I use it:**

* ✅ Official, maintained by GitHub
    
* 🔍 Enables PR automation and repo introspection
    
* 🔄 Seamless for GitOps and CI/CD workflows
    

---

### **3\. 🗄️ DBHub MCP — Schema-Aware SQL Access**

[**DBHub**](https://github.com/bytebase/dbhub) connects agents to relational databases with full schema introspection. I use it internally with Microsoft SQL Server for tasks like query validation, schema analysis, and review automation.

```json
{
  "mcpServers": {
    "dbhub-sqlserver": {
      "command": "npx",
      "args": [
        "-y",
        "@bytebase/dbhub@0.4.5",
        "--transport",
        "stdio",
        "--dsn",
        "sqlserver://dung:********@localhost:1433/db?sslmode=require"
      ]
    }
  }
}
```

**Core features:**

* ✅ Supports PostgreSQL, MySQL, MariaDB, SQL Server, SQLite, and Oracle
    
* 🔐 Read-only mode for safe, production-grade access
    
* 📊 Understands tables, indexes, procedures, and more
    

---

### **🧩 Final Thoughts**

MCP servers are transforming how AI agents operate within real environments. These top picks — **Context7**, **GitHub MCP**, and **DBHub** — are my essential tools for building intelligent, secure, and context-aware agents in 2025.