Overview of the Model Context Protocol (MCP)
The Model Context Protocol (MCP) is a standard that allows various AI clients, like digital assistants and web applications, to communicate with servers in a structured way. It uses a format called JSON-RPC and focuses on three main components: tools, resources, and prompts. This setup helps organizations ensure interactions between AI agents and tools are clear and can be audited, enhancing security measures.
What MCP Standardizes
MCP servers provide:
- Tools: These are specific actions that the model can call, defined by a schema.
- Resources: These are data objects that clients can access and use as context.
- Prompts: These are reusable message templates that users can initiate.
By clearly defining these components, MCP helps identify who controls each aspect of the interaction, which is crucial for understanding potential security risks. For instance, prompt injection, a common attack method, often targets model-controlled paths.
Transport Mechanisms
MCP specifies two main transport methods for communication:
- Standard Input/Output (stdio): This method is used for local server connections and minimizes network exposure.
- Streamable HTTP: This method is suitable for remote connections and supports multiple clients, making it adaptable for web applications.
Choosing the right transport can significantly impact security. For example, using local stdio can reduce potential vulnerabilities, while Streamable HTTP requires robust authentication and logging to ensure secure data exchanges.
Authorization Controls
One of the standout features of MCP is its stringent approach to authorization. Here are some key points:
- No Token Passthrough: MCP servers do not pass along tokens received from clients. This prevents misuse and keeps the audit trail intact.
- Audience Binding: Servers must validate that access tokens are specifically meant for them, preventing unauthorized access from other services.
This strong focus on authorization helps protect sensitive data and maintain the integrity of the system.
Real-World Applications of MCP
MCP is designed to create clear boundaries between clients and servers, which can be critical for security. By implementing consent interfaces, logging, and minimal privilege principles, organizations can significantly reduce risks.
A notable case study occurred in September 2025, when a trojanized npm package mimicking a legitimate MCP server was discovered. This incident highlighted the importance of vetting MCP servers, as they often operate with high trust.
Operational Takeaways
To enhance security when using MCP, organizations should:
- Maintain an allowlist of approved servers and pin versions to avoid malicious packages.
- Monitor for unusual data egress patterns that could indicate data breaches.
- Regularly practice credential rotation and emergency drills.
These practices are not just theoretical; they directly mitigate risks associated with over-trusting server code.
Structuring Red-Team Exercises with MCP
MCP can be effectively used to create realistic red-team exercises. Here are some strategies:
- Prompt Injection Drills: Test how the client handles adversarial inputs and ensure that server post-conditions are maintained.
- Token Misuse Probes: Attempt to induce servers to use incorrect tokens, which should be rejected according to MCP specifications.
- Session Resilience Testing: Evaluate how well remote transports handle reconnections and session management.
These exercises can help identify vulnerabilities before adversaries exploit them.
Implementation Checklist for Security Hardening
To maximize the security of MCP implementations, consider the following checklist:
Client-Side Security
- Clearly display the commands used to start local servers and require explicit user consent.
- Log every tool call and resource fetch for audit purposes.
Server-Side Security
- Implement OAuth 2.1 resource-server behavior, validating tokens before processing requests.
- Minimize the scopes of access to limit potential damage from breaches.
Detection and Response
- Set up alerts for unusual server activity, such as unexpected egress patterns.
- Prepare automated processes for quickly revoking approvals and rotating credentials in case of a flagged server.
Governance Alignment
MCP’s design aligns well with established frameworks like NIST’s AI RMF, making it easier to justify security controls during audits and reviews.
Current Adoption
Several organizations are already implementing MCP:
- Anthropic/Claude: Uses MCP for external tool connections.
- Google’s Data Commons MCP: A standard for accessing public datasets.
- Delinea MCP: Focuses on secure access to secrets and OAuth compliance.
Summary
MCP is not just another security tool; it’s a comprehensive protocol that provides essential controls for managing AI interactions. By establishing clear boundaries, enforcing strict authorization, and enabling detailed logging, organizations can enhance their security posture. Treat MCP servers as privileged connectors—vet them, pin their versions, and monitor their activity. With these practices, MCP can serve as a robust foundation for secure AI systems.
FAQ
- What is the primary purpose of MCP? MCP standardizes communication between AI clients and servers, enhancing security and auditability.
- How does MCP improve security? It establishes clear boundaries, enforces strict authorization, and provides detailed logging for interactions.
- What are the main components of MCP? The three main components are tools, resources, and prompts.
- Can MCP be used for red teaming? Yes, MCP can structure realistic red-team exercises to identify vulnerabilities.
- What should organizations do to secure MCP servers? Maintain an allowlist, monitor egress patterns, and regularly practice credential rotation.
