Basicmcpserver

This project provides a basic MCP server implementation, including simple examples, Docker containerization demonstrations, and automation scripts, supporting the rapid construction of custom MCP services and integration with systems such as Jira.

Artificial intelligence chatbots Developer tools #MCP service #Docker #Jira integration #AI tools .Python

rating : 2 points

downloads : 8.3K

update time : 2025-04-28

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What is BasicMcpServer?

BasicMcpServer is an out-of-the-box MCP server implementation that allows AI assistants to interact with your business systems (such as Jira) through standard protocols. It offers three usage methods: basic templates, Docker containers, and automated generation scripts.

How to use BasicMcpServer?

You can choose from three ways to use it: 1) Clone the template directly and modify it. 2) Learn the Docker deployment method. 3) Run the script to automatically generate a Jira integration server.

Applicable scenarios

It is suitable for enterprises that want to integrate AI assistants into existing workflows, such as project management (Jira), customer relationship management (CRM) and other systems, enabling AI to query and operate system data.

Main features

Ready-to-use template

Provides a basic MCP server implementation, including all necessary components, which can be directly modified and used.

Docker containerization

Complete Docker configuration, supporting multi-stage builds, facilitating deployment and expansion.

Automated generation

Automatically generates complex MCP servers (such as Jira integration) through scripts, saving development time.

End-to-end testing

Built-in testing framework to ensure the integrity and stability of the MCP server's functions.

Advantages

Out-of-the-box, reducing development time

Standardized protocols ensure compatibility with various AI assistants

Flexible deployment options (local/Docker)

Detailed implementation guides and reference documentation

Limitations

Requires basic technical knowledge for customized development

Additional development is required for complex business logic

Depends on the stability of external service APIs

How to use

Select the usage method

Choose the template, Docker, or automated generation method according to your needs.

Get the project code

Clone the repository or run the generation script.

Configure the environment

Set the necessary environment variables and API credentials.

Run the server

Start the MCP server.

Usage examples

Jira ticket query

The AI assistant queries the current status and assignee of a specified Jira ticket.

Create a service ticket

The AI assistant creates a new service ticket based on the user's request.

Frequently Asked Questions

What technical foundation is required for the MCP server?

Which external services can be integrated?

How to test whether the MCP server is working properly?

Related resources

MCP official documentation

Official introduction and specifications of the Model Context Protocol

Python SDK repository

Official Python SDK implementation

HTTP client example

Reference implementation of the MCP HTTP client

🚀 BasicMcpServer: MCP Server Implementation Repository

This repository primarily serves three functions:

Simple Example MCP Server: Offers a basic reference implementation that you can clone and modify as needed.
Docker Containerization Demo: Demonstrates how to set up an MCP server with end - to - end tests in Docker.
Automated Installation and Configuration: Provides scripts for generating more complex MCP servers (e.g., Jira integration).

MCP - Related Resources

Key references for building this implementation:

MCP Official Documentation - Formal documentation and introduction to the Model Context Protocol.
Python SDK Repository - The official Python SDK for MCP development.
MCP HTTP Client Example - A reference implementation that helped develop the test code in this repository.

Content Summary

Basic MCP Server: A simple reference implementation with basic tools.
Docker Configuration: A container - based setup with multi - stage builds to optimize the image.
End - to - End Tests: Demonstrates the correct way to test an MCP server.
setup_jira_mcp_server.sh Script: A script for generating an MCP server integrated with Jira.
mcp_server_implementation_guide.md Guide: A comprehensive guide to implementing an MCP server.

🚀 Quick Start

Option 1: Use the Basic MCP Server as a Template

The simplest approach is to clone this repository and modify it as needed:

# Clone the repository
git clone https://github.com/yourusername/BasicMcpServer.git my-mcp-server
cd my-mcp-server

# Modify src/server.py to implement your custom tools and resources
# Update config.py to configure the required environment variables
# Start the server using Docker or directly in a Python environment

Option 2: Learn the Dockerized MCP Server Implementation

To experience the advantages of containerized deployment, refer to the docker-compose.yml file:

# Build and start the service
docker-compose build
docker-compose up -d

Option 3: Run the Script to Generate a Jira - Integrated MCP Server

Use this script to quickly set up an MCP server environment integrated with Jira:

chmod +x setup_jira_mcp_server.sh
./setup_jira_mcp_server.sh

Extending to Other Services

It's very simple to extend this implementation to other APIs (e.g., GitHub, LDAP, etc.). Just replace the corresponding service interface code and adjust the parameter settings in the configuration file.

What is MCP?

The Model Context Protocol (MCP) is a protocol for standardizing data models and context information, aiming to improve data interoperability between different systems.