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 — 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Tired of outdated or hallucinated examples from your LLM?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 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.

{
  "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.

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

The GitHub MCP server provides structured access to GitHub resources — issues, PRs, repositories, and workflows — all via a secure interface.

{
  "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

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3. 🗄️ DBHub MCP — Schema-Aware SQL Access

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.

{
  "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

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🧩 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.