Mcpserve
MCP Serve is a powerful deep learning model server tool that supports deployment through Shell execution, Ngrok connection, or Docker containers, and integrates multiple advanced AI technologies.
2.5 points
6.3K

What is MCP Serve?

MCP Serve is a server tool designed for deep learning models. It helps users easily deploy and run various AI models. Whether you are an AI researcher or a developer, you can manage and use your models through simple operations.

How to use MCP Serve?

Using MCP Serve is very simple. Just clone the repository, install the dependencies, and start the server. You can choose to execute commands directly through the Shell, use Ngrok for remote connection, or run it in a Docker container.

Applicable scenarios

MCP Serve is very suitable for scenarios that require rapid deployment and testing of deep learning models, such as AI research, model development, and educational demonstrations. It also supports integration with multiple AI platforms (such as OpenAI, Anthropic, etc.).

Main features

Simple MCP server
Provide a simple interface to manage and run your deep learning models
Shell execution
Execute commands directly in the server Shell to gain full control
Ngrok connection
Easily achieve remote access to the local server through Ngrok
Docker container support
Use Docker to host Ubuntu24 containers and provide a stable operating environment
Multi - platform integration
Support multiple AI platforms such as Anthropic, Gemini, and LangChain
Advantages
A simple and easy - to - use interface that lowers the technical threshold
Multiple connection methods to adapt to different usage scenarios
Support for mainstream AI platforms with strong scalability
Docker containers provide a stable and isolated environment
Limitations
Requires basic knowledge of command - line operations
Some advanced functions may require additional configuration
Performance depends on local hardware resources

How to use

Download and install
Download the latest version of the application from the GitHub release page
Clone the repository
Use the git command to clone the project locally
Install dependencies
Enter the project directory and install the required dependencies
Start the server
Run the start command to start the MCP server

Usage examples

Local model testing
Quickly test newly developed deep learning models locally
Remote demonstration
Use Ngrok to share the locally running model with remote team members
Multi - model management
Manage multiple models of different frameworks in one environment

Frequently Asked Questions

Which deep learning frameworks does MCP Serve support?
Is there a fee for using it?
How to solve the port conflict problem?
Does it support the Windows system?

Related resources

GitHub repository
Project source code and latest version
Docker documentation
Docker usage guide
Ngrok official website
Ngrok service introduction and usage method
ModelContextProtocol introduction
MCP protocol technical documentation

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

Alternatives

R
Rsdoctor
Rsdoctor is a build analysis tool specifically designed for the Rspack ecosystem, fully compatible with webpack. It provides visual build analysis, multi - dimensional performance diagnosis, and intelligent optimization suggestions to help developers improve build efficiency and engineering quality.
TypeScript
9.4K
5 points
N
Next Devtools MCP
The Next.js development tools MCP server provides Next.js development tools and utilities for AI programming assistants such as Claude and Cursor, including runtime diagnostics, development automation, and document access functions.
TypeScript
9.1K
5 points
T
Testkube
Testkube is a test orchestration and execution framework for cloud-native applications, providing a unified platform to define, run, and analyze tests. It supports existing testing tools and Kubernetes infrastructure.
Go
5.6K
5 points
M
MCP Windbg
An MCP server that integrates AI models with WinDbg/CDB for analyzing Windows crash dump files and remote debugging, supporting natural language interaction to execute debugging commands.
Python
9.2K
5 points
R
Runno
Runno is a collection of JavaScript toolkits for securely running code in multiple programming languages in environments such as browsers and Node.js. It achieves sandboxed execution through WebAssembly and WASI, supports languages such as Python, Ruby, JavaScript, SQLite, C/C++, and provides integration methods such as web components and MCP servers.
TypeScript
8.6K
5 points
N
Netdata
Netdata is an open-source real-time infrastructure monitoring platform that provides second-level metric collection, visualization, machine learning-driven anomaly detection, and automated alerts. It can achieve full-stack monitoring without complex configuration.
Go
9.1K
5 points
M
MCP Server
The Mapbox MCP Server is a model context protocol server implemented in Node.js, providing AI applications with access to Mapbox geospatial APIs, including functions such as geocoding, point - of - interest search, route planning, isochrone analysis, and static map generation.
TypeScript
8.2K
4 points
U
Uniprof
Uniprof is a tool that simplifies CPU performance analysis. It supports multiple programming languages and runtimes, does not require code modification or additional dependencies, and can perform one-click performance profiling and hotspot analysis through Docker containers or the host mode.
TypeScript
8.4K
4.5 points
M
Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
32.3K
5 points
N
Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
19.1K
4.5 points
D
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
65.1K
4.3 points
G
Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
21.8K
4.3 points
U
Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
29.3K
5 points
F
Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
58.6K
4.5 points
G
Gmail MCP Server
A Gmail automatic authentication MCP server designed for Claude Desktop, supporting Gmail management through natural language interaction, including complete functions such as sending emails, label management, and batch operations.
TypeScript
19.8K
4.5 points
M
Minimax MCP Server
The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.
Python
44.3K
4.8 points
AIBase
Zhiqi Future, Your AI Solution Think Tank
© 2026AIBase