MCP Protocol: The Complete Developer Guide (2026)

The Model Context Protocol (MCP) is becoming the standard way AI assistants connect to external tools and data sources. Whether you're using Claude Code, Cursor, or building your own AI application, understanding MCP is essential. Here's the complete developer guide.

What Is the Model Context Protocol?

MCP (Model Context Protocol) is an open protocol developed by Anthropic that standardizes how AI assistants connect to external data sources and tools. Think of it as a universal adapter between your AI and the services it needs to access.

Before MCP, every integration was custom:

MCP Architecture: The Three Primitives

MCP servers expose three types of capabilities to AI clients:

Transport Modes: stdio vs HTTP

MCP supports two transport mechanisms for client-server communication:

stdio Configuration Example

{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem", "/path/to/docs"]
    }
  }
}

HTTP Configuration Example

{
  "mcpServers": {
    "snipara": {
      "type": "http",
      "url": "https://api.snipara.com/mcp/your-project",
      "headers": {
        "X-API-Key": "rlm_your_api_key"
      }
    }
  }
}

MCP Clients: Where to Use MCP

These AI assistants and IDEs support MCP natively:

Building Your Own MCP Server

MCP servers can be built in Python, TypeScript, or any language that supports JSON-RPC. Here's a minimal example:

Python MCP Server (FastAPI)

from fastapi import FastAPI
from mcp.server import Server
from mcp.types import Tool, TextContent

app = FastAPI()
mcp = Server("my-server")

@mcp.tool()
async def search_docs(query: str) -> list[TextContent]:
    """Search documentation for relevant content."""
    results = your_search_function(query)
    return [TextContent(type="text", text=results)]

# Mount MCP on /mcp endpoint
app.mount("/mcp", mcp.as_asgi())

TypeScript MCP Server

import { Server } from "@modelcontextprotocol/sdk/server";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio";

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

server.setRequestHandler("tools/call", async (request) => {
  if (request.params.name === "search_docs") {
    const results = await searchDocs(request.params.arguments.query);
    return { content: [{ type: "text", text: results }] };
  }
});

const transport = new StdioServerTransport();
await server.connect(transport);

MCP Best Practices

Snipara: A Production MCP Server

Snipara is a context optimization MCP server with 43+ tools for querying documentation, managing memory, and coordinating multi-agent workflows. It's a good reference for building production-grade MCP servers.