About Mcp Security
Mcp Security is a community registry of security evaluations for MCP server implementations. It uses LLM-based analysis to help developers and organizations assess servers and review actionable recommendations.
Key features
- 01Community security evaluation registry
- 02Standardized MCP server assessments
- 03LLM-based security analysis
- 04Actionable recommendations
Use cases
- 01Reviewing an MCP server before adoption
- 02Comparing security assessments
- 03Finding recommended security improvements
MCP support
The project evaluates MCP server implementations and records assessments in a registry; it is not described as exposing tools to MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project README# MCP Security Registry
A community-driven registry of security evaluations for Model Context Protocol (MCP) server implementations.
## About This Project
The MCP Security Registry provides standardized security evaluations of MCP server implementations to help developers and organizations make informed decisions about which MCP servers to use in their applications. Our approach uses LLM-based analysis to provide comprehensive security assessments with actionable recommendations.
### What is MCP?
The Model Context Protocol (MCP) standardizes how applications provide context to Large Language Models (LLMs). MCP servers act as intermediaries that manage context, handle retrieval, and facilitate communication between applications and LLMs.
### Why Security Matters
MCP servers often handle sensitive information and provide critical functionality for AI applications. Security vulnerabilities in MCP implementations can lead to data breaches, prompt injection attacks, and other security issues.
## Certification Process
Our certification process is designed to be transparent, thorough, and actionable:
1. **Repository Submission**: Developers submit their MCP server repository for evaluation
2. **LLM-Based Analysis**: Our system analyzes the repository using advanced LLM techniques
3. **Security Profile Generation**: A comprehensive security profile is created
4. **Certification Assignment**: The implementation receives a certification level based on its security posture
5. **Private Results Delivery**: Detailed results are delivered privately to the repository owner
## Certification Levels
MCP implementations can receive one of three certification levels:
- **Bronze**: Meets basic security requirements
- **Silver**: Implements recommended security practices
- **Gold**: Follows security best practices with no critical/high vulnerabilities
See our [Evaluation Criteria](evaluation-criterea.md) for detailed information on certification requirements.
## Request a Certification
To request a security evaluation for your MCP server implementation:
1. Ensure your repository is publicly accessible on GitHub
2. Submit your repository URL through our [certification request form](https://example.com/request-certification)
3. Receive detailed security analysis and certification results via email
4. Address any security issues identified
5. Request a re-evaluation to achieve a higher certification level (optional)
## Security Evaluation Template
Our security evaluations follow a standardized template to ensure comprehensive coverage of all security aspects. You can view the [evaluation template](evaluation-template.md) to understand what aspects of your implementation will be assessed.
## Contributing
We welcome contributions from the community! See our [Contributing Guidelines](CONTRIBUTING.md) for information on how to contribute to the MCP Security Registry project.
## License
This project is licensed under the [MIT License](LICENSE).
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.