Authentiq API MCP Server Integration Guide

Technical Overview & Protocol Integration

The Authentiq API provides a robust foundation for implementing strong, passwordless authentication and identity verification systems. Developed by Authentiq, a specialist in modern digital identity solutions, this API enables the secure management of cryptographic keys and the orchestration of login and scope-based authorization flows. Its core capabilities are centered around the lifecycle management of public-private key pairs, which serve as the user's credentials. The endpoints allow for the creation of a new key pair (POST /key), retrieval of a public key by its ID (GET /key/{PK}), and associated management operations (POST, PUT, DELETE on the key resource). Beyond basic key management, the API facilitates the authentication process itself through the POST /login endpoint, which verifies a signature from the user's private key. The /scope endpoints introduce a layer of fine-grained, permission-based access control, allowing developers to define, query, and manage specific authorization scopes tied to a job or session. This makes the API ideal for enterprise applications requiring secure internal tool access, consumer-facing mobile or web apps seeking seamless login experiences without credential fatigue, and IoT ecosystems where device authentication is paramount.

When exposed as tools via the Model Context Protocol (MCP) to an AI coding assistant, the Authentiq API transforms from a static set of endpoints into a dynamic, interactive capability. An AI agent, such as one running in Cursor or Cline, could be instructed to programmatically manage authentication infrastructure. For example, it could generate a new API key for a specific service (POST /key), rotate existing keys for security compliance (DELETE followed by POST for a given {PK}), or audit the status of currently active keys by retrieving their details (GET /key/{PK}). More profoundly, it could orchestrate complex authorization workflows by querying and validating user scopes (GET /scope/{job}) or dynamically creating new, time-bound authorization scopes for automated tasks (POST /scope/{job}). This integration empowers developers to delegate repetitive security and configuration tasks to the AI, accelerating setup, ensuring consistency in security policy application, and allowing for rapid prototyping of authentication systems within larger applications.

In practical terms, a developer using an MCP-connected AI could issue natural language commands to perform sophisticated operational tasks. For instance, they could instruct, "Onboard a new partner service by generating a dedicated authentication key with the scope 'analytics:read' and 'logs:write'," prompting the AI to first create the key (POST /key) and then define the associated scope (POST /scope/{job}). Alternatively, a command like "Audit all active login sessions for the 'admin' scope" would have the AI agent use GET /scope/{job} to fetch and summarize the relevant records. The AI could also automate security workflows, such as "Revoke and replace the key used by the legacy reporting module" by executing a sequence of DELETE and POST operations. These dynamic interactions turn the AI into a force multiplier for DevOps and security engineering, handling routine yet critical identity management tasks with precision and speed that manual scripting cannot match.

It is critical to note that while the API itself employs no built-in authentication method for its endpoints, this represents a significant security consideration, not a simplification. All interactions with the Authentiq API should occur over strictly encrypted channels (HTTPS). Developers must implement their own robust authentication and authorization layer in front of this API to control access to its powerful key and scope management functions. The principle of least privilege must be rigorously applied; any service or AI agent interacting with the API should be granted only the absolute minimum permissions necessary to perform its specific function. API keys or other secrets used to interact with Authentiq endpoints must be stored securely in environment variables or a secrets vault, never committed to source code. When configuring the MCP server, developers should ensure the AI assistant operates within a sandboxed context with tightly controlled outbound network rules, allowing it to communicate only with the designated Authentiq API endpoint.

By translating the OpenAPI 3.0 specification for Authentiq API into native Model Context Protocol (MCP) tool definitions, developers and AI agents gain programmatic access to endpoints over stdio or HTTP transports. Every endpoint is translated into a discrete tool payload complete with input argument validation, parameter descriptions, and return type definitions.