FastMCP v2 MCP Server

@Sobroinc

Repository

Basic information

About FastMCP v2 MCP Server

FastMCP server containerized for deployment in Google Kubernetes Engine alongside enhanced-mcp-agent

#fastmcp #mcp #python

FastMCP v2 MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "fast-mcp": {
      "command": "uv",
      "args": [
        "pip",
        "install",
        "fastmcp"
      ]
    }
  }
}

FastMCP v2 MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is FastMCP v2 🚀?

FastMCP v2 is the standard Python framework for building and interacting with Model Context Protocol (MCP) servers and clients. It provides a high-level, Pythonic interface for exposing tools, resources, and prompts, and includes advanced features like client support, server composition, authentication, and automatic generation from OpenAPI specs.

How to use FastMCP v2 🚀?

Install with uv pip install fastmcp, then create a server instance with FastMCP("name") and decorate Python functions as tools, resources, or prompts. Run locally with fastmcp run server.py or mcp.run(). Use the Client class to connect to any MCP server programmatically via stdio, SSE, or in-memory transports.

Key features of FastMCP v2 🚀?

Build tools, resources, and prompts with minimal boilerplate
Client support for stdio, SSE, and in-memory transports
Server composition and proxy servers for remote MCP servers
Automatic generation of MCP servers from OpenAPI specs
Built-in in-memory testing via FastMCPTransport
Authentication and security features for production deployments

Use cases of FastMCP v2 🚀?

Expose custom Python functions as tools for LLMs
Serve static or dynamic data resources to AI applications
Build reusable prompt templates for AI assistants
Convert existing OpenAPI specifications into MCP servers
Test MCP server logic without network overhead using in-memory transport
Unify multiple MCP servers under a single client interface

Frequently asked questions

What is the Model Context Protocol (MCP)?

MCP is a standardized way for LLM applications to securely access data and functionality. It is described as "the USB-C port for AI" and lets servers expose resources, tools, and prompts.

How does FastMCP v2 differ from the official MCP Python SDK?

FastMCP 1.0 was incorporated into the official low-level Python SDK. FastMCP 2.0 is a complete toolkit that goes beyond the core protocol, adding client libraries, authentication, server composition, OpenAPI generation, testing tools, and production-ready infrastructure.

What transports does the FastMCP Client support?

The Client supports Stdio, SSE, and In-Memory transports. It often auto-detects the correct transport from the connection string and also supports connecting to multiple servers through a unified

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