AttestationClient MCP Server

When exposed as tools to an AI coding assistant via the Model Context Protocol, this API unlocks powerful, context-aware automation for developers working on infrastructure-as-code, security automation scripts, or cloud deployment pipelines. The AI can act as a knowledgeable proxy, translating high-level intent into precise API operations. This transforms the developer's workflow from manually crafting and executing curl commands or SDK calls to engaging in a dialogue to achieve complex configuration outcomes. The value lies in accelerating development velocity and reducing errors, especially for developers less familiar with the specific API schema or the nuances of enclave management. The AI assistant, equipped with the MCP tools, can instantly validate the current state, understand dependencies, and execute changes with the necessary precision, effectively becoming a pair programmer specialized in this security-critical domain.

Practical workflows enabled by this MCP server are numerous and highly operational. A developer could instruct the AI to "Check the current attestation policy for my production enclave and summarize its allowed measurement values," prompting the AI to fetch and parse the response from GET /operations/policy/current. For deployment automation, a command like "Update the production enclave policy to allow the new version of our application binary, identified by measurement XYZ," would have the AI agent first fetch the current policy via GET, then use POST or PUT to /operations/policy/updatepolicy with the updated payload, ensuring a safe, incremental change. The AI could also be tasked with compliance audits: "Compare the attestation policies across my staging and production enclaves and report any differences," requiring it to call the relevant endpoints for both environments and perform a logical diff. Furthermore, it could assist in disaster recovery by retrieving the standard policy configuration via GET /operations/policy/current and preparing the command to reapply it in a new region.

Given the endpoint GET /.well-known/openid-configuration, the API itself advertises an OpenID Connect configuration, which is a critical clue to its security model. Although the specified authentication method for direct client access is "None," this likely indicates that the API is designed to be called from within a trusted network perimeter or by services that have already authenticated at a higher layer (e.g., via mutual TLS or a service mesh). Implementers must not mistake "None" for a lack of security requirements. Best practices are paramount: deploy the API behind a strict network access control list or a zero-trust proxy. Implement robust authorization at the application layer, even if not part of the API spec itself, ensuring that only authorized service accounts can perform sensitive operations like policy updates. Always operate under the principle of least privilege, granting write permissions (POST/PUT) only to the specific automation pipelines or privileged users that absolutely require them. All API calls, especially those modifying policy, should be meticulously logged and monitored for anomaly detection to prevent unauthorized changes that could undermine the security of the entire enclave infrastructure.