MCP Api Server Wrapper

🚀 MCP API Server Template

A template for MCP servers used for API integration. With the help of AI, you can easily encapsulate external APIs into an MCP server.

🚀 Quick Start

Using this template, you can easily encapsulate external APIs into an MCP server with the help of AI.

Usage

1. Clone the project

git clone https://github.com/fnf-deepHeading/mcp-api-server-wrapper.git your-api-name-mcp  
cd your-api-name-mcp

2. Configure the development environment

# Synchronize dependencies  
uv sync

3. Make a request to the AI in the following format:

# Goal: ~~ Implementation of an MCP server for API calls
# Guidance: The guidance described in the `HOWTOMAKE.md` file, especially the **"Core Guidance for AI Assistants"** section (required prompt)
# API information:
# 1. Function 1: [Link]
# 2. Function 2: [Link]
# Working mode: (Optional prompt)
Process the entire task at once instead of one by one, create a TODO.md and a detailed execution plan file, and then complete them one by one.
Process the detailed execution plan once without asking for progress.

Example:

# Goal: Integrate three Naver APIs (Blog Search, News Search, Search Volume Query) to implement an MCP server

# Guidance: The guidance described in the `HOWTOMAKE.md` file, especially the **"Core Guidance for AI Assistants"** section.

# API information:
# 1. Naver Blog Search: https://developers.naver.com/docs/serviceapi/search/blog/blog.md#%EB%B8%94%EB%A1%9C%EA%B7%B8 
# 2. Naver News Search: https://developers.naver.com/docs/serviceapi/search/news/news.md#%EB%89%B4%EC%8A%A4 
# 3. Naver Search Volume Query: https://developers.naver.com/docs/serviceapi/datalab/search/search.md#%ED%86%B5%ED%95%A9-%EA%B2%80%EC%83%89%EC%96%B4-%ED%8A%B8%EB%A0%8C%EB%93%9C

4. The AI will automatically generate code and configuration files, and users can run them directly.

✨ Features

• Automate API integration with AI
• Manage configurations using command-line parameters
• Support Docker
• Provide detailed guide documentation

💻 Usage Examples

Basic Usage

Suppose a user wants to integrate a weather API:

1. The user sends a request to the AI:

# Goal: Implement an MCP server for the weather API
# Guidance: The guidance described in the `HOWTOMAKE.md` file, especially the **"Core Guidance for AI Assistants"** section.
# API information:
# 1. Weather API: https://openweathermap.org/api

2. The AI automatically generates code and configuration files, and the user can run the generated server directly.

📚 Documentation

• AI Integration: Users only need to provide API documentation links, and the AI will automatically parse the documents and generate the corresponding MCP server code.
• Command-line Configuration: It supports configuration via command-line parameters, making it easy to adjust settings quickly.
• Docker Support: It provides support for Docker image building, allowing users to easily deploy to the production environment.

❓ Frequently Asked Questions

• API Errors: If the generated code cannot call the API correctly, check if the API documentation is correct.
• Dependency Installation Failure: Ensure that the network connection is normal and use the latest Python version.
• Docker Deployment Issues: Ensure that Docker is installed correctly and the image building command is correct.

🌟 Advantages

• Rapid Development: Leverage AI automation to reduce manual coding time.
• Standardized Structure: Maintain a unified architecture for MCP servers, facilitating maintenance.
• Efficient Integration: Support integration of multiple APIs, improving development efficiency.

With this template, users can easily encapsulate various external APIs into a fully functional MCP server while leveraging the powerful capabilities of AI to accelerate the development process.