Insecure MCP Demo Server: Enhancing AI Application Integration through Vulnerable Channels

Overview: What is Insecure MCP Demo Server?

This project serves as an illustrative sandbox environment designed to highlight potential security vulnerabilities within Model Context Protocol (MCP) infrastructure. Specifically, it demonstrates a flawed MCP server that exposes several insecure tools and clients with varying levels of complexity for educational purposes. The setup includes both "good" and "attack" clients, enabling users to explore the protocol's capabilities and the risks inherent in its unsecured implementation.

🔧 Core Features & MCP Capabilities

This demonstration project offers a unique glimpse into the core features and potential vulnerabilities of an MCP server. By providing direct access to a range of functionalities such as data insertion, querying, SQL command execution, and environmental variable retrieval, this setup exposes critical points for security improvements. The inclusion of both benign ("good") and malicious ("attack") clients showcases different ways in which these endpoints can be exploited, facilitating comprehensive educational resources on secure protocol design.

⚙️ MCP Architecture & Protocol Implementation

The architecture of the Insecure MCP Demo Server is designed to mimic a real-world scenario where an AI application connects to a data source or tool via the Model Context Protocol. This server implements various tools that illustrate potential risks, such as unsanitized input, lack of authentication, and unrestricted access to sensitive information. The protocol flow diagram below outlines how these vulnerabilities might manifest in actual implementations.

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

🚀 Getting Started with Installation

To set up and run this Insecure MCP Demo Server, follow these steps:

1. Install Dependencies

pip install -r requirements.txt

2. Start the Server and Good Client

In one terminal window:

python good-mcp-client.py vuln-mcp.py

This will guide you through an interactive session where you can insert and query records using a basic client.

3. Run the Attack Client

Open another terminal window:

python attack-mcp-client.py vuln-mcp.py

The attack client will automatically execute a series of tests to demonstrate potential security breaches, including SQL injection attempts and environment variable access.

💡 Key Use Cases in AI Workflows

While this setup is intentionally insecure, its configuration offers valuable insights into how different AI applications might be affected under real-world conditions. For instance:

1. Claude Desktop Integration: Users can simulate the interaction between Claude Desktop and a vulnerable MCP server by running the good client from the Claude Desktop interface.
2. Cursor API Calls: Similarly, Cursor interactions with the demo server can reveal potential risks in exposing sensitive information or allowing unauthenticated access.

🔌 Integration with MCP Clients

The Insecure MCP Demo Server is compatible with several popular MCP clients:

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

For full compatibility, ensure that the respective clients support the features exposed by this server.

📊 Performance & Compatibility Matrix

The performance and compatibility of the Insecure MCP Demo Server depend on the specific tools and functionalities enabled. For detailed metrics and testing results, refer to the project's codebase and documentation.

🛠️ Advanced Configuration & Security

To mitigate the risks highlighted in this demo project:

1. Use Parameterized Queries: Replace static SQL strings with parameterized queries to prevent injection attacks.
2. Restrict Tool Usage: Limit access to high-risk tools such as execute_sql and get_env_variable.
3. Implement Authentication & Authorization: Require users to authenticate before using sensitive functionalities.
4. Validate Input: Ensure all user inputs are validated and sanitized, especially for database interactions.

❓ Frequently Asked Questions (FAQ)

1. Can I use this server in a live environment?

   • No, the Insecure MCP Demo Server is intended solely for educational purposes. Deployment of this codebase in production environments can pose significant security risks.

2. How do I secure the execute_sql tool?

   • To prevent arbitrary SQL command execution, disable or limit this endpoint and replace it with validated API calls.

3. What are some common tools that should be restricted?

   • Tools like get_env_variable, execute_sql, and unrestricted record queries pose significant risks and should be carefully vetted.

4. How can I monitor the server's performance?

   • Implement logging mechanisms to track tool invocations and identify suspicious activities.

5. Why is environment variable access a security concern?

   • Accessing sensitive environment variables, such as API keys or secret credentials, can lead to unauthorized data exposure or manipulation.

👨‍💻 Development & Contribution Guidelines

Contributions are welcome! To contribute:

1. Fork the repository.
2. Improve documentation and fix any issues you find.
3. Submit a pull request for review.

For technical inquiries or contributions, please reach out to the project maintainer via the GitHub issue tracker.

🌐 MCP Ecosystem & Resources

Explore more resources within the broader MCP ecosystem:

• MCP Protocol Documentation: Comprehensive guides and specifications for implementing secure MCP servers.
• Security Best Practices: Additional security recommendations for maintaining compliant and robust MCP implementations.
• Community Forums: Engage with other developers and discuss best practices, challenges, and solutions.

By addressing these vulnerabilities and adhering to best practices, developers can ensure that their AI applications interact securely through the Model Context Protocol.