From 51c5ad7066442f1c22f11ce5c33d57bd9d2ca1a2 Mon Sep 17 00:00:00 2001
From: Umesh Patel <Umesh.Code1@gmail.com>
Date: Fri, 23 Oct 2026 16:28:25 +0530
Subject: [PATCH] feat(07-ai-agents): add hands-on FastMCP server tutorial
 guide

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+# 🤖 Hands-on Guide: Building Custom Model Context Protocol (MCP) Servers with FastMCP
+
+> Learn how to build and expose custom tools to Claude, Antigravity IDE, Cursor, and autonomous AI agents using the official Python Model Context Protocol (MCP) SDK and FastMCP.
+
+---
+
+## 📌 What is the Model Context Protocol (MCP)?
+
+The **Model Context Protocol (MCP)** is an open industry standard that enables Large Language Models (LLMs) and agentic coding environments to securely discover and call external tools, execute code, access databases, and read local files.
+
+Rather than hard-coding one-off API integrations, MCP provides a unified client-server architecture:
+- **MCP Host / Client:** The agent or IDE (e.g. Claude Desktop, Antigravity IDE, Cursor).
+- **MCP Server:** A lightweight microservice that defines tools, resources, and prompts.
+
+---
+
+## 🚀 1. Installation & Environment Setup
+
+FastMCP is the high-level, decorator-driven interface included in the official Python MCP SDK (`mcp>=1.2.0`).
+
+```bash
+# Create and activate a clean virtual environment
+python -m venv .venv
+source .venv/bin/activate  # On Windows: .venv\Scripts\activate
+
+# Install the official MCP SDK with FastMCP support
+pip install "mcp[cli]>=1.2.0" pydantic
+```
+
+---
+
+## 🛠️ 2. Creating Your First Tool Server (`server.py`)
+
+Here is a complete, production-ready FastMCP server providing mathematical analysis, string hashing, and system inspection tools:
+
+```python
+"""
+AIML Club OCT — FastMCP Reference Server
+Exposes mathematical utilities and string hashing tools to AI agents.
+"""
+
+from mcp.server.fastmcp import FastMCP
+from pydantic import BaseModel, Field
+import hashlib
+import math
+import sys
+
+# Initialize the FastMCP server instance
+mcp = FastMCP("aiml-club-toolkit")
+
+
+class StatisticalInput(BaseModel):
+    numbers: list[float] = Field(
+        ..., 
+        description="List of numeric values to analyze.",
+        min_length=1
+    )
+
+
+@mcp.tool()
+def compute_statistics(payload: StatisticalInput) -> dict:
+    """Compute mean, sample variance, standard deviation, and median for a list of numbers."""
+    nums = sorted(payload.numbers)
+    n = len(nums)
+    mean = sum(nums) / n
+    variance = sum((x - mean) ** 2 for x in nums) / (n - 1) if n > 1 else 0.0
+    std_dev = math.sqrt(variance)
+    median = (nums[n // 2] if n % 2 != 0 else (nums[n // 2 - 1] + nums[n // 2]) / 2)
+
+    return {
+        "count": n,
+        "mean": round(mean, 4),
+        "variance": round(variance, 4),
+        "std_dev": round(std_dev, 4),
+        "median": round(median, 4),
+        "min": nums[0],
+        "max": nums[-1],
+    }
+
+
+@mcp.tool()
+def hash_text(text: str, algorithm: str = "sha256") -> str:
+    """Hash a string using sha256, sha512, or md5."""
+    algo = algorithm.lower()
+    if algo not in {"sha256", "sha512", "md5"}:
+        raise ValueError("Supported algorithms: sha256, sha512, md5")
+    
+    h = getattr(hashlib, algo)()
+    h.update(text.encode("utf-8"))
+    return h.hexdigest()
+
+
+if __name__ == "__main__":
+    # Start the standard stdio server loop
+    mcp.run()
+```
+
+---
+
+## 🔌 3. Connecting to Claude Desktop or Antigravity IDE
+
+To connect your custom MCP server to **Claude Desktop**, edit `claude_desktop_config.json`:
+
+- **Windows:** `%APPDATA%\Claude\claude_desktop_config.json`
+- **macOS:** `~/Library/Application Support/Claude/claude_desktop_config.json`
+
+Add the server configuration:
+
+```json
+{
+  "mcpServers": {
+    "aiml-toolkit": {
+      "command": "python",
+      "args": ["C:/absolute/path/to/server.py"]
+    }
+  }
+}
+```
+
+Restart Claude Desktop, and the hammer icon 🔨 will appear with your `compute_statistics` and `hash_text` tools ready to run!
+
+---
+
+## 💡 Student Exercises
+1. Add an `@mcp.tool()` that queries a SQLite database and returns the top 5 records.
+2. Build an `@mcp.tool()` that takes a URL and extracts clean markdown using `readability` or `trafilatura`.
+3. Open a PR in [`AIMLCLUBOCT/Projects`](https://github.com/AIMLCLUBOCT/Projects) to showcase your tool server!