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MCP Server Python
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MCP Server Python

This project is an implementation of the Model Context Protocol (MCP) server, demonstrating how to build a functional server that can be integrated with multiple language model clients. As a standardized protocol, MCP provides a unified way for AI applications to connect data sources and tools, supporting three types of capabilities: resources, tools, and prompts.
Developer toolsArtificial intelligence chatbots#Protocol Standard#AI Integration#Data Connection#Language Model.Python
2 points
7.0K
Open Site

Overview

Installation

Content Details

Alternatives

What is the MCP server?

The MCP server is a standardized protocol that allows different applications (such as IDEs and AI tools) to access multiple data sources and services through a unified interface. It simplifies the data integration process, enabling developers to focus on building smarter applications.

How to use the MCP server?

Just follow simple steps to install and configure, and your application can easily connect to the MCP server and start using rich data and features.

Applicable scenarios

It is suitable for developers who need to collaborate with AI models, such as those building personalized recommendation systems, knowledge management systems, or intelligent customer service platforms.

Main Features

Resource Access
Supports reading data from local files or returned by remote APIs.
Tool Integration
Provides powerful tool invocation capabilities to meet specific business needs.
Preset Templates
Comes with multiple task templates to quickly generate high-quality outputs.
Advantages
Standardized interface, easy to expand and maintain
Supports multi-source data fusion to enhance application flexibility
Protects data security, ensuring transmission only within the internal network
Limitations
Initial configuration may be slightly complex
Support for high-concurrency requests needs optimization

How to Use

Install the Dependent Environment
Ensure that Python 3.10 or a higher version is installed, and initialize the project through the `uv` management tool.
Create a Server Instance
Write the main script `main.py` to define the MCP server logic.
Start the Server
Run the server to listen for client requests.

Usage Examples

Example 1: Load a Local File
Read a local file through the MCP server and pass it to the AI model.
Example 2: Call an External API
Use the MCP server to integrate third - party API data to enhance application functionality.

Frequently Asked Questions

How to confirm whether the MCP server is working properly?
Why can't my Claude Desktop find the MCP server?

Related Resources

Official Documentation
Detailed introduction and technical guide of the MCP protocol.
GitHub Repository
Open - source code and community support.
Installation Tutorial Video
Step - by - step demonstration of the installation and configuration process.

Installation

Copy the following command to your Client for configuration
{
    "mcpServers": {
        "mcp-server": {
            "command": "uv",
            "args": [
                "--directory",
                "/RUTA/ABSOLUTA/A/TU/mcp-server",
                "run",
                "main.py"
            ]
        }
    }
}
Note: Your key is sensitive information, do not share it with anyone.

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