Modern systems, especially those powered by AI agents, microservices, and ephemeral workloads, need to authenticate securely without being bottlenecked by manual setup. In OAuth2, every application that needs access to protected resources must first register as a client and get a client secret.
Traditionally, this registration is a static, manual process, fine for monoliths, but ill-suited for dynamic environments where services spin up, scale down, or self-replicate constantly. That’s where Dynamic Client Registration (DCR) enters the picture.
In this blog, we’ll explore how DCR works, why it’s crucial for agentic identity models, and how it enables scalable, automated authentication for transient clients. We’ll break down the OAuth2 client model, explain the mechanics of dynamic registration, walk through a real-world flow, and show why DCR is foundational for systems like Model Context Protocol (MCP), where identity must be flexible, secure, and fast.
OAuth2 defines a client application as any application or service that wants to access a protected resource on behalf of a user or itself. This could be a web app, mobile app, server-side API, or, more recently, an autonomous AI agent. To interact securely with an OAuth2 authorization server, each client application must identify itself using credentials, usually in the form of a client_id and client_secret.
In most OAuth2 implementations, client registration is static:
While this model works for long-lived client applications, it introduces several problems in modern, dynamic environments.
Static registration has inherent constraints:
As architectures shift toward ephemeral compute, multi-tenant microservices, and autonomous agents, static registration becomes a bottleneck:
Transient agents: In agentic systems like those following the Model Context Protocol (MCP), each AI agent often acts as an independent actor with its own access scope, lifecycle, and context. That means it needs a unique identity to securely interact with APIs or third-party systems.
But what kind of systems actually need thousands of agents (and therefore identities)? Here are developer-relevant examples:
Dynamic Client Registration (DCR) is an extension of the OAuth2 specification that allows clients applications to register themselves programmatically with an authorization server at runtime, no human intervention required. Instead of logging into a dashboard and manually copying credentials, a client application (like an AI agent or microservice) can send a registration request to the client registration endpoint and receive everything it needs to authenticate and request access tokens.
DCR is defined in two key IETF specifications:
These standards provide a consistent way to create, manage, and update client metadata via API endpoints.
Client sends metadata to the registration endpoint: A JSON payload includes details such as:
Authorization server responds with credentials: The server replies with a unique client_id, possibly a client_secret, and metadata such as a registration_access_token.
When DCR is paired with strong authentication methods, its security posture improves significantly:
By combining DCR with these techniques, you not only gain flexibility but also significantly reduce the attack surface in identity workflows.
To support interoperability, the OAuth 2 spec defines a discovery document at a well-known location. This is the entry point for clients to locate all relevant endpoints, including the dynamic registration endpoint.
GET /.well-known/openid-configuration
Example response:
Imagine you’re building a DevOps dashboard that needs to dynamically register itself with your company’s OAuth2 provider during CI deployment. Instead of hardcoding the token and registration URLs, your CI job fetches the discovery document first:
This allows the same script to work across environments (dev/staging/prod) or even across different IdPs, zero config changes required.
Clients submit a POST request to the registration_endpoint with metadata describing themselves. Example using curl:
This request can also include additional fields like scope, logo_uri, or jwks_uri if the client uses JWT-based authentication.
The authorization server responds with a set of credentials and metadata:
These values are then used by the client to authenticate with the token endpoint.
Not all DCR endpoints are open to unauthenticated requests. Depending on the deployment, the registration API may require one of the following:
mTLS (Mutual TLS): One common method to protect the DCR endpoint is using mutual TLS (mTLS). Unlike standard TLS, where only the server proves its identity using a certificate, mTLS requires both the client and the server to present valid certificates. These client certificates serve as strong, cryptographic proof that the client is trusted and authorized to make registration requests. It ensures that only clients with valid client certificates can register.
JWT-based software statements: Trusted issuers (e.g., a platform operator) sign a JWT containing client metadata. The server verifies the signature before registration.
Access tokens: The client may first authenticate with a bootstrap token to prove eligibility.
As AI agents and microservices take on more autonomy in modern systems, identity and access management must evolve to match their dynamic nature. In Model Context Protocol (MCP)-style architectures, where agents execute user tasks, fetch data, or orchestrate workflows, each agent effectively behaves as its own identity-bound client. Manually managing OAuth2 credentials for these agents simply doesn’t scale.
Agentic systems are defined by ephemerality. A single agent might exist only for a few minutes, just long enough to complete a search query, API call, or transaction, before terminating. Pre-registering each of these entities defeats the goal of automation:
DCR makes automated self-onboarding possible. Here’s what a newly spawned agent can do:
All of this happens programmatically, within seconds, enabling just-in-time identity bootstrapping for agents, without manual setup or human intervention.
DCR moves identity management from dashboards to code. You can now:
This “identity-as-code” approach mirrors the benefits GitOps brought to infrastructure: it’s repeatable, auditable, and scalable.
Rather than assigning one client_id to thousands of agents, DCR enables per-agent identities:
DCR allows organizations to handle thousands of transient clients without losing control:
This makes DCR not just useful, but essential, in scalable, agent-rich environments.
Before we dive into the registration flow, it's helpful to clarify a couple of key OAuth2 concepts that appear in DCR payloads:
With that in mind, let’s walk through a typical DCR flow using the client_credentials grant and client_secret_basic authentication.
Here’s how an agent might register using axios in a Node.js environment:
In the example, the client is receiving the initial access token upon registration. The client registration endpoint serves as the starting point in this flow. This sends client metadata to the DCR endpoint. The grant_types and token_endpoint_auth_method define how the agent will later authenticate and request tokens.
The server replies with the credentials and access information:
Once registered, the agent can authenticate like any standard OAuth2 client:
You can optionally:
Dynamic Client Registration (DCR) brings flexibility and scalability to OAuth2, but to safely operate it in production environments, a few best practices are essential.
Automated cleanup: Set up a scheduled job (e.g., cron task or Lambda function) to query registered clients via the registration_access_token or your internal registry. Build logic to:
Client expiry metadata: Optionally include expires_at during registration and enforce it via policy.: Keep an internal database or dashboard of registered agent clients, linked to their lifecycle, purpose, or user session.
Maintain a registry: Keep an internal database or dashboard of registered agent clients, linked to their lifecycle, purpose, or user session.
As AI agents and ephemeral workloads continue to grow, authentication models must evolve.
DCR aligns with the shift toward identity-as-code, where registration, credential management, and policy assignment are all embedded in CI/CD workflows. Just like GitOps revolutionized infrastructure provisioning, DCR helps automate identity provisioning.
DCR pairs well with self-sovereign identity (SSI) models and decentralized identifiers (DIDs). You can envision agents registering dynamically while also presenting cryptographic claims about their provenance or trust source.
Instead of assuming long-lived users or applications, future auth systems should:
This inversion of traditional auth logic is critical for agent-based compute.
In Model Context Protocol (MCP) systems, where thousands of AI agents spawn per hour, DCR isn’t just nice to have. It’s foundational infrastructure. You need a way for agents to onboard themselves securely and scalably, without human involvement.
Dynamic Client Registration (DCR) unlocks a scalable, secure, and automation-friendly approach to client identity in OAuth2. In dynamic, agent-rich environments like AI orchestration platforms, serverless apps, or MCP-style infrastructures, static registration models simply don’t hold up.
DCR allows each agent to self-identify, receive credentials, and access resources without any human bottlenecks. This aligns OAuth2 with the future of cloud-native and agentic computing.
Next steps:
A: Static registration requires pre-configuring clients manually, often through an admin UI. Dynamic registration allows clients to self-register via an API at runtime.
A: Yes, when properly implemented with access control (e.g., software statements, mTLS, or token-protected endpoints), DCR is a secure and flexible mechanism.
A: Absolutely. OAuth providers like Auth0, Okta, ForgeRock, Keycloak, and Cloudflare offer varying levels of support for DCR in production settings.
A: Clients can be updated or de-registered using the registration_access_token. Rotation can be built into automation pipelines.
A: Self-hosted solutions like Keycloak or ForgeRock give you full control over DCR endpoints and policies, making them ideal for custom agentic systems.