Introduction to MCP authentication

As AI systems grow more powerful and deeply integrated with external systems, the need for secure, context-aware infrastructure has never been greater. That’s where the Model Context Protocol (MCP) comes in, a foundational layer for enabling intelligent agents to operate across services with memory, identity, and control.

But with great power comes great responsibility. As MCP servers begin handling sensitive data and issuing high-impact actions, strong authentication and precise authorization become critical.

In this article, we’ll dive into how authentication and authorization work within the MCP ecosystem, exploring common implementation patterns, practical security considerations, and best practices for keeping your MCP servers safe, trustworthy, and in control. Let’s dive in.

What is MCP?

The Model Context Protocol (MCP) is a protocol that defines a standardized way for large language models (LLMs like GPT, Gemini, or Claude) to securely and consistently interact with external tools, APIs, and services. It’s designed for AI-native environments, where traditional request-response paradigms break down.

MCP works as a universal interface layer that bridges the gap between LLMs and real-world software. While LLMs are exceptional at generating text, they don’t inherently understand how to interact with APIs. That’s where MCP comes in. It acts as a standardized protocol that presents external tools and services to LLMs as structured functions, so models can use them without needing to understand the complexities of each underlying API.

MCP gives models:

• Contextual memory across sessions and requests.
• Scoped permissions to act on behalf of users.
• A unified abstraction for tools, APIs, and data access.

Think of it as the HTTP + OAuth for AI agents. A protocol that governs who, what, and how context travels and is applied in model workflows.

MCP components

On a high level, MCP consists of 3 components:

• MCP host: An AI tool, like Claude or Cursor, that needs to interact with external data or tools.
• MCP client: A lightweight runtime that acts as the communication bridge between the MCP host and the MCP server. It's essentially the middleware layer that allows the host to call tools over MCP without embedding server logic directly into the host. It has the following characteristics:
  
  • Runs inside the host application (or alongside it).
  • Maintains a dedicated 1:1 connection to an MCP Server (local or remote).
  • Forwards tool or function calls from the host to the server.
  • Manages authentication, authorization, and context transfer.
  • Routes requests, and receives and returns results.
  • The host application runs one or more MCP Clients.
• MCP server: The MCP Server is where the actual logic or side effects happen. It’s a program (or collection of services) that exposes tools, APIs, or actions in a format that large language models can understand and invoke via the MCP standard. It responds to requests from MCP Clients, runs the requested tool or function, and sends the results back. MCP Servers typically enforce:
  
  • Authentication (Is the client allowed to talk to me?)
  • Authorization (Is the user or model allowed to run this tool?)
  • Context validation (Is this request part of a trusted session/task?)

Why one MCP client per MCP server?

Each MCP Client maintains a 1:1 relationship with a server. This simplifies:

• Security (each server gets its own connection context).
• Configuration (separate auth, endpoint, and tool scopes).
• Scalability (multiple servers = multiple clients = distributed load).

For example, if Cursor IDE is configured to use three different MCP servers (e.g., one for internal tools, one for GitHub, one for customer data), it will spin up three separate MCP clients, each bound to its corresponding server.

Why does authentication and authorization matter in MCP?

In traditional apps, users log in, perform actions, and permissions are enforced server-side. But in model-based workflows, the model itself often initiates actions, querying databases, calling APIs, and editing documents on behalf of users.

This creates several challenges:

• How do we know who is behind a request?
• How do we prevent overreach by a model?
• How do we scope access to specific tasks or time windows?

In MCP, authentication ("Who is this?") and authorization ("What can they do?") work together to ensure that only legitimate clients can access your servers and that they can only perform actions they're permitted to do.

The MCP authorization specification

As of March 2025, MCP took a major step forward with the release of its official authorization specification, a game-changer for how identity and access are managed across MCP-powered systems. At its core? OAuth 2.1.

By adopting this industry-standard protocol, MCP gives developers a secure, familiar foundation for handling authentication and authorization without reinventing the wheel. Whether you're building agents or securing APIs, the new spec brings consistency, clarity, and confidence to the table.

It should be noted that authorization is optional for MCP servers, allowing flexibility based on security requirements.

Common authentication patterns for MCP servers

1. API key authentication

One of the most common ways to authenticate access to external services is through API keys: simple, static string tokens that both identify the client and authorize access to a given API.

In the context of MCP, API keys are typically used when your MCP server needs to call external services (like third-party APIs or internal tools). There are a couple of ways to manage and inject these keys securely:

• Using environment variables or local resources: For servers running locally (e.g. CLI-style tools), the recommended approach is to store API keys in environment variables or secure local files. Your MCP server can read these at runtime during initialization. This is especially relevant when using the stdio transport, where the server and client run in the same local environment and can securely share access to secrets.
• Using OAuth Device Flow for user-level auth: For a more dynamic and secure user-authentication model—particularly when a specific user identity is required—you can use the OAuth 2.1 device flow. In this setup the MCP server initiates an OAuth device flow, the user authorizes the connection in their browser, and the server receives an access token tied to the user. This pattern works well for tools that need user-scoped access (e.g. accessing a user’s GitHub repositories or Google Calendar). The client credentials required to initiate the device flow (client ID, client secret, scopes) should also be stored securely—typically as environment variables or encrypted secrets. The Device Flow is ideal when your MCP server acts more like a CLI or agent running locally and you want users to explicitly grant consent for access.

2. OAuth 2.1 flow: A standardized authorization flow for MCP

In March 2025, the MCP specification made a significant leap forward by officially adopting OAuth 2.1 as its standardized framework for authorization. This change brings mature, battle-tested security principles to the world of model-driven systems, and makes it far easier for developers to integrate MCP with existing identity infrastructures.

With OAuth 2.1 at the core, MCP clients and servers can now rely on a well-known delegation model to securely authorize tool usage, API access, or user actions across services.

Here are some key features of OAuth 2.1 in MCP:

• PKCE: All clients are required to use Proof Key for Code Exchange (PKCE), a security measure that prevents token interception or code injection during the OAuth flow. This alone eliminates a class of vulnerabilities common in naive OAuth implementations and makes even public clients much more secure by default.
• Metadata Discovery: Rather than hardcoding endpoints or requiring manual setup, MCP servers can now broadcast their OAuth configuration (authorization URL, token endpoint, scopes, etc.) using standard metadata discovery. Clients can programmatically discover how to initiate the flow, leading to fewer misconfigurations and a smoother integration process.
• Dynamic Client Registration (DCR): One of the most impactful usability upgrades is Dynamic Client Registration. This allows an MCP client to register itself with a new MCP server on the fly, without manual intervention. No more hardcoded client IDs or long setup guides, just plug in and go. This is crucial for scaling across a diverse ecosystem of tools, hosts, and model providers.‍
• Leverage third-party authentication: The spec also supports full delegation to external identity providers, such as WorkOS, for handling the user login experience. This means an MCP server doesn't need to own user auth; it can trust a third-party provider to authenticate and issue tokens. The result is tighter integration with existing SSO, enterprise IAM systems, and zero-trust networks.

!!For more details, see MCP Authorization in 5 easy OAuth specs.!!

Here’s what a full OAuth 2.1 flow looks like between an MCP client, server, and external identity provider:

1. Client initiates an OAuth 2.1 authorization request with the MCP server.
2. MCP server redirects the user to a trusted third-party identity provider (e.g. WorkOS).
3. User logs in and grants access at the third-party provider.
4. The provider redirects back to the MCP server with an authorization code.
5. MCP server exchanges the code for a third-party access token.
6. The server generates its own scoped token, representing the authorized session.
7. Client receives the final access token and proceeds with authorized tool usage.

!!For details on how to configure WorkOS as your MCP Server’s identity provider, see our docs.!!

Limitations of MCP authorization

While the adoption of OAuth 2.1 has introduced a solid and standardized foundation for authentication and authorization in the Model Context Protocol (MCP), several important limitations remain, particularly in terms of how the spec expects MCP servers to behave.

These constraints raise real implementation challenges that the community is actively discussing. Here's a breakdown of the current pain points and a look at what the future might bring.

Current requirements create heavy burden on MCP Servers

According to the spec, MCP servers must implement OAuth 2.1 securely and should support protocols like:

• RFC 7591 – Dynamic Client Registration
• RFC 8414 – Authorization Server Metadata

In particular, the spec encourages servers to expose metadata like:

• issuer
• authorization_endpoint
• token_endpoint
• registration_endpoint
• userinfo_endpoint

This mimics what full OAuth 2.1 providers like WorkOS already do.

Implementing this metadata on the MCP server itself creates a heavy operational and security burden, including:

• Token storage and session management: The server must persist access tokens securely and possibly support refresh flows.
• Compliance and infrastructure pressure: An MCP server becomes critical auth infrastructure, subject to audits, secure logging, and potentially regulatory certifications.
• Redundant token validation: If the MCP server receives a token from an upstream provider (like WorkOS), it still needs to validate it or issue its own, creating duplication and potential security risks.

Proxying OAuth metadata: Not so simple

A tempting workaround is to proxy the identity provider’s metadata, essentially delegating identity and session management directly to a trusted external OAuth server (like WorkOS). However, this raises compliance issues with the MCP spec.

Section 2.9.2 of the MCP specification explicitly states:

The MCP server authorizes with the third-party authorization server, and then generates its own access token bound to the third-party session.

This implies that proxying alone doesn’t cut it, the server must still act as an intermediate Authorization Server, issuing its own token even if a third-party token has already been validated.

This creates a tension: delegation simplifies things, but strict compliance requires MCP servers to act like full OAuth providers, something many implementers want to avoid.

What’s next? A path toward a better spec

Given these growing pains, it’s clear the current spec could benefit from evolution. Some areas the community is actively exploring:

• A layered or pluggable authorization model: Where MCP servers can choose between being a full Authorization Server or simply a delegate to one, like WorkOS.
• Clearer language around delegation patterns: Allowing well-defined proxies for metadata and token validation.
• Standardized token introspection endpoints: So a client can verify the scope and validity of MCP-issued tokens without full session storage.
• Relaxed requirements for lightweight servers: Supporting "read-only" servers or "local mode" that don't need the full OAuth stack.

With contributions from identity and security experts, the next iteration of the spec could bring a more flexible, best-in-class OAuth2 integration model, one that supports both enterprise-grade deployments and lightweight local agents without compromising on security or usability.

Wrapping up: Where we are and where we are headed

As LLM-native applications continue to mature, the need for strong, flexible, and standards-based authorization is only growing. The Model Context Protocol’s adoption of OAuth 2.1 marks a critical step toward building safer, more controllable AI systems. By aligning with established security practices, MCP enables developers to focus less on reinventing auth and more on building powerful, trustworthy experiences.

But the current specification isn’t perfect. Implementers are already running into real-world friction, from metadata management and token handling to questions around delegation and infrastructure overhead. These challenges are shaping the next phase of the protocol’s evolution: one that strives to balance compliance with developer ergonomics and security with simplicity.

As the MCP community continues to refine its authorization layer, identity and security best practices will remain central to its success. Whether you're an AI developer, platform engineer, or security architect, now is a great time to get involved in shaping how models interact safely with the world.

And if you’re looking to build an MCP server of your own, check out our MCP Authorization Guide to get started with secure, standards-compliant integration.