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AI workflows are the new baseline for businesses today. However, engineering leaders face a critical question when adopting the Model Context Protocol (MCP): Should you build your own authentication layer or adopt a third-party solution?
MCP, introduced in late 2024, enables AI agents to connect to external data and tools. However, the complexity and risks associated with MCP authentication make the build vs. buy decision a strategic consideration.
This guide explores why MCP authentication differs significantly from traditional user authentication, highlights the hidden costs and security implications of building your own solution, and provides a practical decision framework to help you navigate your choice effectively.
While MCP does turn integration complexity from M x N to M + N for the protocol layer, authentication and authorization remain stubbornly M x N problems.
Each MCP server still needs to handle auth differently depending on what it's connecting to. A GitHub MCP server needs GitHub tokens, a database server needs database credentials, an email server needs SMTP auth, etc. The client application now has to manage and securely store N different credential types instead of implementing N different integrations.
So yes, the protocol complexity is reduced, but the real operational headache (managing secrets, handling token refresh, dealing with different auth flows) just gets moved around rather than solved.
-Hacker News user
Why MCP authentication isn't just "OAuth for agents"
At first glance, MCP authentication might seem like just another OAuth implementation. However, MCP introduces distinct challenges:
- Multiple identity layers: Unlike traditional OAuth, MCP must distinguish between requests initiated by human users, AI agents, or system processes, each with unique permissions and audit requirements.
- Dynamic and granular permissions: MCP interactions often involve precise function-level access scopes, unlike the broader API permissions typically seen with traditional OAuth integrations.
- Tool and context security: Each MCP tool acts as a potential code execution point, increasing the overall attack surface and risk of exploits like token leakage and unauthorized access.
- Rapidly evolving standards: As MCP specifications continue evolving, any custom-built solution must adapt quickly to ensure security and compliance.
Handling authentication at the MCP server level is not ideal for developers and does not align well with enterprise use cases.
What we’ve seen above is a high-level overview of the complexities involved. Let’s get into more specifics.
What you need to build for MCP auth
The MCP server consists of three primitives: Tools (functions an LLM can execute), resources (data an LLM can read), and prompts (reusable templates).
This architecture is designed for agentic workflows, a world away from the simple request-response pattern of a web browser. This architectural consideration is why the official MCP authorization specification is stringent.
The specification involves the following complexities that need to be factored in while building MCP auth:
- PKCE (Proof Key for Code Exchange): PKCE is required for all clients, both public and confidential, to mitigate authorization code interception attacks. This adds a cryptographic challenge-response mechanism to the standard OAuth flow.
- Dynamic Client Registration (RFC7591): In the MCP ecosystem, an AI agent (client) must be able to discover and securely connect to a new MCP server it has never seen before, without manual configuration. This requires the authorization server to support dynamic client registration, a protocol where clients can programmatically register themselves to get a client_id.
- Metadata discovery (RFC8414 & RFC9728): To initiate the auth flow, the client first needs to discover the server's capabilities and the location of its authorization server. The MCP spec requires servers to advertise this information via OAuth 2.0 Protected Resource Metadata (/.well-known/oauth-authorization-server). The client, in turn, must be able to fetch and parse this metadata to find the correct endpoints for authorization, token exchange, and registration.
When building MCP auth, you are not building a login page for a person. You are building a full-fledged, standards-compliant auth mechanism for AI workflows. This involves managing security for autonomous agents that may operate for long periods without direct human supervision.
The added complexities led a Redditor to observe:
Now every MCP server needs to implement its own OAuth on top of the existing OAuth or whatever other authentication is required by the underlying API. This is an insane level of complication and abstraction.
Hidden costs and risks of building your own MCP auth solution
A recent incident highlights what can go wrong building your own auth. Earlier this year, a Supabase-run MCP server inadvertently issued agents with overly broad permissions.
An attacker used one of these agents to access unrelated tenant data. While not solely an authentication failure, it stemmed from insufficient separation of concerns and poorly scoped agent tokens, exactly the kind of risk that dedicated authorization servers are designed to mitigate.
Engineering teams might initially favor building their own MCP authentication layer, attracted by the promise of full control. However, this approach carries substantial hidden costs and risks
- Security vulnerabilities: Without dedicated security expertise, teams risk exposing sensitive data through insecure token handling, privilege escalation, and prompt injection vulnerabilities. Addressing these threats demands ongoing vigilance and resources.
- Compliance overhead: Enterprises operating in regulated sectors (finance, healthcare, etc.) must integrate comprehensive audit trails, explicit consent mechanisms, and robust access controls. Achieving this from scratch can consume significant engineering bandwidth.
- Maintenance burden: Ongoing maintenance, keeping pace with MCP spec updates, security advisories, and patching vulnerabilities can quickly drain resources from core business goals.
- Opportunity cost: Time and resources spent building and maintaining your own authentication layer mean less investment in core product features and strategic innovation, potentially delaying your GTM timelines.
I’ve worked on teams where we trusted whatever was in the token without checking if the issuer was even allowed. Makes me think... maybe token validation should be less DIY.
Making the right choice
Building your own solution makes sense if you have dedicated security expertise, extended timelines, and authentication as a core competitive advantage. Most teams underestimate the ongoing maintenance burden and security complexity.
Buying a solution accelerates deployment and delegates security maintenance to specialists, but limits customization and creates vendor dependency.
Auth is infrastructure, while your product represents innovation. For teams that want to move fast without reinventing the wheel, solutions like Scalekit can help. Scalekit offers secure MCP servers with OAuth, providing a drop-in authorization server that’s MCP-spec compliant with Dynamic Client Registration and PKCE. It ships with scoped, short-lived tokens designed for LLM-based agents and AI tools, letting you skip the token plumbing.
FAQ
Q: What does building MCP authentication in-house involve?
You’ll need to design secure token issuance and validation, implement dynamic permission scopes, build audit logs and consent workflows, and maintain compliance, all while keeping up with evolving MCP standards.
Q: When does it make sense to build?
If you have highly specific security or workflow needs, a large team with deep expertise, and see authentication as a core part of your competitive advantage.
Q: When is buying a better choice?
If you need to deploy quickly, have a small or generalist team, and prefer to focus engineering resources on building your product rather than infrastructure.
Q: What are the risks of building in-house?
You take on potential security vulnerabilities, higher compliance burden, ongoing maintenance work, and slower delivery of customer-facing features.
Q: Why do teams choose to buy?
It accelerates time-to-market, lowers risk, provides built-in compliance and auditability, and frees your team to focus on what makes your product unique.
