#fastmcp

We deployed FastMCP behind Docker and nginx, wired it to OAuth token introspection, and tested Streamable HTTP session handling, proxy headers, callback URLs, and DNS rebinding defenses.

You are already in Cursor, mid-debug, when you need to know whether an app is up, what its domains...

Playwright MCP server in Python is the modern architectural pattern that enables autonomous...

Model Context Protocol (MCP) makes it possible for AI assistants to interact with external tools and...

Why a FastMCP agent mail server that works anonymously in dev returns 403 behind TLS ingress, and how to wire bearer tokens without leaking them.

Hello everyone. I want to continue writing about fraud detection MCP server. In this blog tutorial, I...

My sister is a nurse. When I showed her the first version of this tool, she said it felt wrong. That...

How to Build Production-Ready MCP Servers with FastMCP in Python: From Complex Pydantic...

Your AI Needs Eyes on the Web AI models are incredibly smart, but they have a blind spot....

The Pain of Python Apps (And How InjectQ Fixes It) Ever built a Python app that started...

I installed FastMCP 3.2.4, built a working MCP server with @mcp.tool(), @mcp.resource(), and @mcp.prompt() decorators, and tested it end-to-end. A practical guide to implementing an AI tool server that Claude Desktop and Cursor can call — in 30 lines of Python.

MCP went from an obscure Anthropic spec to the de facto standard for connecting AI to real tools in 18 months. Here's the honest first-person build log — setup, working code, what broke, and what you actually get at the end.