---
type: source
title: "The ULTIMATE Guide to Building Your Own MCP Servers (Free Template)"
description: "Building your own MCP server is the real unlock of the Model Context Protocol, and with a best-practices Python template (FastMCP + lifespan + dual transports) you can connect your agents to any service you want."
youtube_id: lbyPJqCI-tw
url: https://www.youtube.com/watch?v=lbyPJqCI-tw
slug: the-ultimate-guide-to-building-your-own-mcp-servers-free-template
published: 2025-04-13
duration: "0:27:54"
recency_rank: 100
raw: "../raw/the-ultimate-guide-to-building-your-own-mcp-servers-free-template.md"
tags: [mcp, build-mcp-server, python, fastmcp]
created: 2026-07-21
updated: 2026-07-21
---

# The ULTIMATE Guide to Building Your Own MCP Servers (Free Template)

Cole frames Anthropic's Model Context Protocol (MCP) as the first-ever standard for connecting LLMs to external services (Gmail, Slack, GitHub, web search, long-term memory). He shows that while many prebuilt MCP servers already exist (e.g., Brave Search) and drop into any MCP client (Claude Desktop, Cursor, Windsurf, n8n) via a simple JSON config, the true power comes from building your own so you get full customization and can connect to services no existing server covers. He proves his custom Mem0 memory server behaves identically to Anthropic's official ones by using it interchangeably across Claude Desktop, a custom Pydantic AI agent, and n8n.

The core of the video is a free, best-practices Python MCP template built around Mem0 for agent long-term memory. Cole walks the three structural components he says most servers get wrong: (1) a lifespan/lifecycle that instantiates a single shared client (like the singleton pattern) once for the whole server and gracefully cleans it up, passed into every tool via context; (2) instantiating the FastMCP server with name, description, lifespan, host, and port; and (3) defining tools with @mcp.tool, where the function docstring becomes the tool description the LLM reads to decide when and how to call it. The example exposes save-memory, get-all-memories, and search-memories tools.

He emphasizes supporting BOTH transport protocols: stdio (client launches the server as a subprocess, ideal for fast local same-machine use) and SSE/HTTP (for remote hosting, monetization, and clients like n8n that only support SSE), toggled via an environment variable. He also shows how to accelerate building servers with AI coding assistants by feeding them the full MCP docs (llms.txt / native Windsurf @MCP RAG) plus his template's main function as a concrete example, then demonstrates running the finished server via Docker and confirming it works end-to-end across clients.

## Concepts covered

- [Model Context Protocol (MCP)](../concepts/mcp.md)
- [Build Your Own MCP Server](../concepts/build-your-own-mcp-server.md)
- [Tool Design](../concepts/tool-design.md)
- [MCP Server & Client Architecture](../concepts/mcp-architecture.md)
- [Agent Protocols](../concepts/agent-protocols.md)
- [Docs and Templates as Coding-Assistant Context](../concepts/docs-as-agent-context.md)
- [Memory Systems](../concepts/memory-systems.md)
- [Vibe Coding](../concepts/vibe-coding.md)

## Entities

- [Cole Medin](../entities/people/cole-medin.md)
- [Anthropic](../entities/organizations/anthropic.md)
- [MCP (Model Context Protocol)](../entities/tools/mcp.md)
- [Mem0](../entities/tools/mem0.md)
- [Claude Desktop](../entities/tools/claude-desktop.md)
- [n8n](../entities/tools/n8n.md)
- [Pydantic AI](../entities/tools/pydantic-ai.md)
- [Windsurf](../entities/tools/windsurf.md)
- [Brave Search API](../entities/tools/brave-search.md)
- [Docker](../entities/tools/docker.md)
- [Archon](../entities/tools/archon.md)
- [Dynamous](../entities/organizations/dynamous.md)
- [Supabase](../entities/tools/supabase.md)

## Key moments

- **[0:00:00]** MCP framed as the first standard for connecting LLMs to services; own servers are the real power
- **[0:02:14]** What it means to build your own server; walkthrough of using an existing Brave Search MCP server in Claude Desktop
- **[0:04:43]** Custom Mem0 memory server shown behaving identically to Anthropic's official servers
- **[0:05:55]** Same server reused across Claude Desktop, a Pydantic AI agent, and n8n
- **[0:07:17]** Introduces the free Python MCP template (Mem0) built with best practices
- **[0:11:24]** High-level structure: pip install mcp, FastMCP, @mcp.tool
- **[0:13:11]** Using AI coding assistants with the MCP docs (llms.txt) plus the template as an example prompt
- **[0:15:53]** Component 1, lifespan: one shared client for the whole server + graceful cleanup (singleton pattern)
- **[0:17:26]** Component 2, instantiate FastMCP with name, description, lifespan, host, port
- **[0:17:57]** Component 3, tools via @mcp.tool; docstring becomes the tool description for the LLM
- **[0:21:05]** Transports: stdio vs SSE, pros/cons, why to support both, env-var toggle
- **[0:24:12]** Setup via README; running with Docker; end-to-end demo across clients

## Transcript

[Raw transcript](../raw/the-ultimate-guide-to-building-your-own-mcp-servers-free-template.md)
