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Description

The Docker MCP Gateway is a fundamental open source element of the Docker MCP Catalog and Toolkit, designed to run Model Context Protocol (MCP) servers within isolated Docker containers that have limited privileges, restricted network access, and defined resource constraints, thereby providing secure and consistent environments for AI applications. This component oversees the complete lifecycle of MCP servers by launching containers as needed when an AI application requires a specific tool, injecting necessary credentials, enforcing security measures, and directing requests so that servers can effectively process them and deliver outcomes through a single, cohesive gateway interface. By positioning all operational MCP containers behind one unified access point, the Gateway enhances the ease with which AI clients can discover and utilize various MCP services, minimizing redundancy, boosting performance, and centralizing aspects of configuration and authentication. In essence, it streamlines the interaction between AI applications and multiple services, fostering a more efficient development process and elevating overall system security.

Description

FastMCP is a Python-based open-source framework designed to facilitate the development of Model Context Protocol (MCP) applications, simplifying the creation, management, and interaction with MCP servers while managing the complexities of the protocol so that developers can concentrate on their core business logic. The Model Context Protocol (MCP) serves as a standardized method for enabling large language models to connect securely with tools, data, and services, and FastMCP offers a streamlined API that allows for easy implementation of this protocol with minimal boilerplate code by utilizing Python decorators for registering tools, resources, and prompts. To set up a typical FastMCP server, one would instantiate a FastMCP object, use decorators to mark Python functions as tools (which can be invoked by the LLM), and then launch the server with various built-in transport options such as stdio or HTTP; this setup enables AI clients to interact with your code seamlessly as if it were integrated into the model’s context. Additionally, FastMCP’s design promotes efficient development practices, allowing teams to quickly iterate on their applications while maintaining high standards of code quality and performance.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Model Context Protocol (MCP)
Docker
Markdown
Python

Integrations

Model Context Protocol (MCP)
Docker
Markdown
Python

Pricing Details

Free
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Docker

Founded

2013

Country

United States

Website

docs.docker.com/ai/mcp-catalog-and-toolkit/mcp-gateway/

Vendor Details

Company Name

fastmcp

Founded

2025

Country

United States

Website

gofastmcp.com/getting-started/welcome

Product Features

Product Features

Alternatives

Alternatives