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 clients and the problem with static registration

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.

How clients traditionally register

In most OAuth2 implementations, client registration is static:

• A developer manually sets up the client in an identity provider’s dashboard or admin portal.
  
  
• They define redirect URIs, choose grant types, and retrieve a static client_id and client_secret.
  
  
• These credentials are then hardcoded into the app or stored in configuration files or secret stores.

While this model works for long-lived client applications, it introduces several problems in modern, dynamic environments.

Static registration: Operational friction and security risk

Static registration has inherent constraints:

• Manual setup: Every client instance must be registered manually, which becomes unmanageable as the number of clients grows.
  
• Credential sprawl: Secrets are often duplicated across environments and systems, increasing the risk of leakage.
  
• Configuration drift: Any update to client metadata (e.g., redirect URIs, scopes) must be synced manually, often leading to mismatches between environments.
  
• Hard to automate: CI/CD pipelines can't provision clients on the fly without scripting against admin APIs (if they even exist).

Why static doesn’t scale for agentic or ephemeral systems

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:

• AI customer assistants: Imagine a contact center platform where each incoming support session spins up an AI agent to assist the user. A busy B2C company could run 10,000+ such sessions daily, each agent requiring scoped access to the user’s CRM and support history.‍
• Tenant-isolated analytics bots: A SaaS product offers per-customer analytics. Each customer’s data processing agent runs independently and should have credentials scoped only to that tenant’s data store, never shared across accounts.‍
• Microservice proliferation: In service mesh or serverless environments, new service instances may come and go dynamically, requiring their own credentials at runtime.
• Developers must wait on Ops or IAM teams to provision clients, slowing down testing, prototyping, and production releases.

What is Dynamic Client Registration (DCR)?

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:

• RFC 7591: OAuth 2.0 Dynamic Client Registration Protocol
  
• RFC 7592: OAuth 2.0 Dynamic Client Registration Management Protocol

These standards provide a consistent way to create, manage, and update client metadata via API endpoints.

Core mechanics of DCR

Client sends metadata to the registration endpoint: A JSON payload includes details such as:

• ^client_name
  
• ^{redirect_uris}
  
• ^grant_types
  
• ^{token_endpoint_auth_method}
  

‍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}.

Scaling OAuth2: Why you need DCR now

• Eliminates pre-provisioning: Clients don’t need to be created manually ahead of time, and each client dynamic registration ensures efficient automated workflows.
  
• Enables ephemeral clients: Perfect for AI agents or microservices that spin up temporarily.
  
• Fits modern automation pipelines: Works well with GitOps, CI/CD, and dynamic infrastructure.
  
• Reduces credential reuse: Each client can be isolated with unique credentials and permissions.

Security benefits

When DCR is paired with strong authentication methods, its security posture improves significantly:‍

• Mutual TLS (mTLS): Validates the client at the network layer, ensuring only trusted workloads can register.
• Software statements (JWTs): Clients can prove their identity using signed assertions from a trusted authority.
• Scoped registration access: registration_access_token allows granular control over who can update or revoke client configurations.
  

By combining DCR with these techniques, you not only gain flexibility but also significantly reduce the attack surface in identity workflows.

How DCR works: A technical perspective

1. The discovery phase

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:

Real-world example: Dev login integration

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.

2. Registration payload: The request

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.

3. Registration response: The output

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.

4. Securing the registration flow

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.

Why DCR is critical for agentic identity systems

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.

Why pre-registration 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:

• CI/CD pipelines can’t wait for manual OAuth setup.
  
• Credential rotation across thousands of identities becomes infeasible.
  
• Shared secrets increase blast radius and violate least-privilege principles.

Zero-touch onboarding

DCR makes automated self-onboarding possible. Here’s what a newly spawned agent can do:

• Discover the DCR endpoint via OpenID Connect discovery.
  
• Register dynamically, providing metadata like redirect URIs and grant types.
  
• Receive client credentials and immediately begin authenticating with the authorization server.

All of this happens programmatically, within seconds, enabling just-in-time identity bootstrapping for agents, without manual setup or human intervention.

Automation-first identity

DCR moves identity management from dashboards to code. You can now:

• Create: Dynamically register clients on spin-up.
  
• Rotate: Automate periodic credential rotation through CI/CD workflows.
  
• Revoke: Tear down client credentials automatically after task completion.
  

This “identity-as-code” approach mirrors the benefits GitOps brought to infrastructure: it’s repeatable, auditable, and scalable.

Granular isolation by design

Rather than assigning one client_id to thousands of agents, DCR enables per-agent identities:

• Each agent gets a unique client_id and optionally a scoped ^{client_secret}.
  
• Permissions can be scoped individually, based on role or task.
  
• Compromise of one agent doesn’t jeopardize others, credential isolation limits risk.
  
• Access logs and audit trails are more precise and traceable per-agent.

Scale without sacrificing security

DCR allows organizations to handle thousands of transient clients without losing control:

• AI agents can dynamically self-register, obtain credentials, and access resources, no waiting, no pre-wiring.
  
• Security practices like mTLS, JWT software statements, and access tokens ensure that only trusted agents can participate.
  
• Lifecycle events, create, rotate, revoke, can all be driven by policy or automation.
  

This makes DCR not just useful, but essential, in scalable, agent-rich environments.

Example: OAuth DCR flow in action

Before we dive into the registration flow, it's helpful to clarify a couple of key OAuth2 concepts that appear in DCR payloads:

• Grant types: These define how a client gets an access token. Common ones include:
  
  • ^{authorization_code}: For apps acting on behalf of users, with a browser redirect flow
    
  • ^{client_credentials}: For backend-to-backend communication where no user is involved
    
  • ^{refresh_token}: To obtain new access tokens without user interaction
    
• Token endpoint authentication methods: These define how the client proves its identity when requesting tokens:
  
  • ^{client_secret_basic}: Client ID and secret are sent using HTTP Basic Auth
    
  • ^{client_secret_post}: Credentials are included in the POST body
    
  • ^{private_key_jwt}: The client signs a JWT with a private key
    
  • ^{tls_client_auth}: Uses mutual TLS (mTLS) for strong authentication
    

With that in mind, let’s walk through a typical DCR flow using the client_credentials grant and client_secret_basic authentication.

Registration request

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.

Sample response from authorization server

The server replies with the credentials and access information:

• ^client_id and ^{client_secret}: Used to obtain tokens
  
• ^{registration_access_token}: Used to manage (update or delete) the client later
  
• ^{client_id_issued_at}: Timestamp for credential creation

Post-registration flow

Once registered, the agent can authenticate like any standard OAuth2 client:

You can optionally:

• Persist credentials in a secure store for reuse
  
• Revoke credentials using the ^{registration_client_uri} or by deleting the agent
  
• Rotate secrets periodically or before reuse to tighten security

Considerations and best practices

Dynamic Client Registration (DCR) brings flexibility and scalability to OAuth2, but to safely operate it in production environments, a few best practices are essential.

Security and token hygiene

• Use short-lived secrets: Don’t let client_secrets live forever. Keep token TTLs short and rotate credentials regularly
  
• Leverage software statement JWTs: When appropriate, use signed JWTs from a trusted authority to authenticate registration requests. This protects against unauthorized or spoofed clients
  
• Restrict metadata fields: Validate and sanitize client metadata like redirect URIs to avoid open redirect vulnerabilities or injection risks

Lifecycle management

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:

• Identify clients that haven’t requested a token or accessed an endpoint within a defined TTL (e.g., 30 minutes).
  
• Automatically call the client de-registration endpoint:

• Log removals for auditing and anomaly detection.‍

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.

Future of agentic auth and role of DCR

As AI agents and ephemeral workloads continue to grow, authentication models must evolve.

Identity-as-code

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.

Decentralized identity + DCR

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.

Transient-first auth models

Instead of assuming long-lived users or applications, future auth systems should:

• Assume short-lived, single-purpose clients.
  
  
• Provide scoped access with zero manual provisioning.
  
  
• Rotate or revoke credentials automatically after task completion.

This inversion of traditional auth logic is critical for agent-based compute.

DCR in MCP: From feature to foundation

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.

Conclusion

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:

• Evaluate DCR support in your OAuth provider
  
  
• Try implementing a DCR flow using tools like Postman, curl, or Node.js
  
  
• Read up on the Model Context Protocol authorization layer
  
  
• Explore pairing DCR with mTLS, software statements, or OIDC discovery for production-grade auth

FAQs

Q: What is the difference between static and dynamic client registration?

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.

Q: Is DCR secure?

A: Yes, when properly implemented with access control (e.g., software statements, mTLS, or token-protected endpoints), DCR is a secure and flexible mechanism.

Q: Can I use DCR in production today?

A: Absolutely. OAuth providers like Auth0, Okta, ForgeRock, Keycloak, and Cloudflare offer varying levels of support for DCR in production settings.

Q: How does DCR handle rotation and revocation?

A: Clients can be updated or de-registered using the registration_access_token. Rotation can be built into automation pipelines.

Q: What’s the link between DCR and self-hosted OAuth servers?

A: Self-hosted solutions like Keycloak or ForgeRock give you full control over DCR endpoints and policies, making them ideal for custom agentic systems.