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CESAR NIKOLAS CAMAC MELENDEZ
CESAR NIKOLAS CAMAC MELENDEZ

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🌐 Build Your Own MCP Server — and Connect It to *Any* MCP Client (Claude, VSCode, GitHub, and More)

#ai #developers #opensource #programming

Imagine building a tool once… and instantly using it across Claude Desktop, VSCode, GitHub, or any future AI platform that supports MCP.

Welcome to the next evolution of AI/tool interoperability.

🚀 What is MCP?

MCP (Model Context Protocol) is an open-source standard designed to enable seamless integration between LLM-based clients and external systems/tools/data sources. :contentReference[oaicite:1]{index=1}

It defines how clients (which may wrap chat-apps, IDEs, or other AI interfaces) connect to servers exposing context, tools, resources, and prompts — abstracting away most compatibility issues. :contentReference[oaicite:2]{index=2}

🔧 Example Public Repositories

You don’t have to reinvent the wheel — there are reference MCP server implementations available to get you started:

Repo / SDK / Server Description / Key Features
GitHub MCP Server — github/github-mcp-server A server that connects AI clients to GitHub: enables reading repos, managing issues/PRs, analyzing code, automating workflows via natural-language interactions. :contentReference[oaicite:4]{index=4}
ModelContextProtocol/servers — modelcontextprotocol/servers A curated collection of reference MCP server implementations: includes Template MCP Server, mcp-open-library, MCP-OpenStack-Ops, and more, in various languages/contexts. :contentReference[oaicite:6]{index=6}

These repos let you fork, modify, or extend existing MCP servers — saving time and helping you follow established patterns.

🛠️ How to Spin Up a Sample MCP Server Locally (Example with GitHub MCP Server)

Here’s how you could get started with the GitHub MCP Server:

git clone https://github.com/github/github-mcp-server.git
cd github-mcp-server
# follow setup instructions (auth, env vars, etc.)
# likely you'll need to provide a GitHub token or configure OAuth
npm install   # or the appropriate build/deploy command
node ./server.js   # or equivalent start command
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⚠️ Security warning: MCP servers can execute arbitrary logic/tools, so only run trusted servers or audit code carefully before using them. MCP supports various transports including stdio, http, etc. ([Visual Studio Code][1])

Once running, you can configure your MCP-aware client (Claude Desktop, VSCode, or others) to connect to it — more on configuration below.

💡 Client Configuration & Usage

Most MCP clients support multiple “server” transports (HTTP, stdio, SSE, etc.). ([Visual Studio Code][1])

Here’s a minimal example of what your MCP config might look like in VSCode’s .vscode/mcp.json:

json
{
"servers": {
"my-github-mcp": {
"type": "http",
"url": "http://localhost:PORT"
}
}
}

Replace PORT with what your server is listening on. With this, your AI-assisted environment will be able to call the exposed MCP tools (e.g. list repos, open issues, analyze code) securely and interactively.

🚀 Why This is Awesome

  • Interoperability — One server + many clients.
  • Modular AI tooling — Expose custom logic/APIs as tools the AI can call.
  • Open-source & community-driven — Benefit from reference servers and SDKs maintained by the wider ecosystem (TS, Python, Java, etc.). ([GitHub][2])
  • Incremental adoption — Start small (e.g. expose a weather or search tool), then grow.

💬 What’s Next — Extend & Share

  1. Fork one of the example MCP servers above.
  2. Add your own tools/resources (DB access, private APIs, file parsers, whatever).
  3. Connect it to any UI client (Claude, VSCode, or home-grown client).
  4. Publish & share — the community thrives on real-world use-cases and feedback.

🔗 References & Resources

  • Official servers listing: modelcontextprotocol/servers repo.
  • GitHub-specific MCP server: github/github-mcp-server.
  • Official MCP docs: build guides, spec, transports, resource/types. ([Model Context Protocol][3])

🧠 Discussion — Over to You

What’s the coolest tool you’d build using MCP?

  • A code review bot that hooks directly into GitHub
  • A knowledge assistant over private docs/DB
  • A UI-driven tool that visually exposes data via AI prompts

Drop your thoughts, ideas or questions — let’s hack this together 👇

Top comments (1)

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jefferson_rosas profile image
JEFFERSON ROSAS CHAMBILLA •

What really stands out here is how MCP subtly shifts the mental model for tool integration: instead of wiring features into each client, you essentially treat the client as a lightweight window into a shared backend of capabilities. That inversion is huge especially for teams maintaining the same internal tools across IDEs, chat UIs, and CI bots. The fact that the GitHub MCP server already exposes repo operations as callable tools makes it feel less like a protocol spec and more like the beginning of a portable ‘AI ops layer.’ Curious to see how people standardize domain-specific toolpacks on top of this.