MCP Auth

Overview

MCP Auth is a ready‑made authentication layer for Model Context Protocol (MCP) servers. It removes the need to manually implement OAuth 2.1 and OpenID Connect (OIDC) flows, allowing developers to secure their MCP endpoints in a matter of minutes rather than weeks. By adhering strictly to the MCP specification, MCP Auth guarantees that every token exchange, refresh cycle, and scope handling follows the same standards used by AI assistants such as Claude.

The server acts as a gatekeeper for any MCP resource, tools, prompts, or sampling endpoint. Once integrated, every request must present a valid access token issued by an OAuth 2.1/OIDC provider. MCP Auth supports any compliant provider, whether it is a commercial identity service like Okta or Azure AD, an open‑source solution such as Keycloak, or a custom provider that meets the RFCs. The verification step is built into the tool, so developers can confirm provider compliance before deployment.

Key capabilities include:

• Provider‑agnostic integration – plug in any OAuth 2.1/OIDC provider without code changes.
• Spec‑compliant token handling – automatic validation of scopes, audience, and issuer to match MCP expectations.
• Refresh token management – seamless background renewal of tokens, keeping the AI workflow uninterrupted.
• Secure defaults – TLS enforcement, CSRF protection for web flows, and strict redirect URI validation.
• Minimal boilerplate – a single configuration file replaces hundreds of lines of custom code.

Typical use cases are:

1. Enterprise AI services where internal identity providers must control access to sensitive prompts or models.
2. Multi‑tenant SaaS platforms that expose MCP endpoints to customers, each with their own OAuth realm.
3. Rapid prototyping of AI assistants that require secure access without investing in a full identity infrastructure.

In practice, developers add MCP Auth to their server stack, point it at the desired OAuth provider, and then expose MCP resources. AI assistants automatically discover the authentication requirements via the MCP specification, present a login prompt to users, and exchange tokens behind the scenes. The result is a production‑ready, standards‑compliant authentication layer that scales with your AI application and protects both data and user privacy.