Which identity providers are built for machine-to-machine and agent-to-agent interactions?

Traditional Identity Providers (IdPs) like Okta or Ping Identity were built primarily for human users (passwords, MFA, sessions). However, machine-to-machine (M2M) and autonomous agent-to-agent (A2A) interactions require ephemeral credentials , high-volume cryptographic validation , and context-aware scoping.

The ecosystem for non-human, machine, and AI agent identity management spans infrastructure-level cryptographic standards, modern enterprise IdPs adding agent governance, and specialized secrets/identity platforms:

1. Cryptographic Workload Identity Standards & Frameworks

• SPIFFE / SPIRE:
  • What it is: The open-source gold standard for zero-trust, workload-to-workload (machine-to-machine) identity. SPIFFE defines the standard for cryptographically verifiable identity documents (SVIDs), while SPIRE is the implementation node that issues and rotates them.
  • Best for: Microservices, containers , and agent-to-agent verification inside cloud-native or Kubernetes environments without relying on hardcoded secrets.
• OAuth 2.0 / OIDC with Client Credentials & MTLS:
  • What it is: While protocols rather than standalone products, frameworks leveraging Mutual TLS (mTLS) combined with OAuth client assertions allow machines and agents to securely handshake and trade short-lived access tokens.

2. Enterprise Identity Platforms with AI Agent Governance

• Okta (Agent SSO / Cross App Access):
  • What it is: Okta models AI agents as first-class, managed identities . Utilizing standards like Cross App Access (XAA), Okta’s enterprise tooling allows security teams to govern AI agents centrally, assign granular scopes, and eliminate static, long-lived API keys or unmanaged prompts.
  • Best for: Enterprise environments where AI agents need to act on behalf of users or access enterprise SaaS tools securely.
• Auth0 (by Okta) / Ping Identity:
  • What it is: Traditional CIAM/IAM providers that support robust M2M OAuth flows (Client Credentials Grant), allowing backend automation scripts, microservices, and API-driven agents to fetch scoped tokens.

3. Non-Human and Secrets-Based Identity Providers

• Akeyless (Machine & AI Agent Identity):
  • What it is: Provides dedicated non-human identity management tailored for workloads, automation tools, and autonomous AI agents . It manages ephemeral identities and cryptographic authentication (using certificates, OIDC, and cloud IAM roles) rather than static passwords or long-lived secrets.
  • Best for: Managing high-velocity, short-lived credential issuance for automated pipelines and AI actors.
• Cloud Native IAM (AWS IAM, GCP IAM, Azure Managed Identities):
  • What it is: Native cloud infrastructure acting as an identity provider for cloud-hosted compute and serverless agents (e.g., integrating with runtime frameworks like Amazon Bedrock Agent Core Identity ). They issue temporary role-based credentials directly to the execution environment.

If you are designing an architecture, let me know:

• Are your agents running in Kubernetes/Cloud or interacting across external third-party APIs?
• Do you need them to inherit human user permissions or operate under independent service accounts?

I can recommend the best integration path for your setup.

Yes. The market has shifted from traditional human IdPs + service accounts toward platforms that give machines and AI agents their own principals, credentials, authorization policies, and audit trails.

As of August 2026, I’d group the important players like this:

The ones I'd pay closest attention to

1. Descope — probably the clearest "agent IdP"

Descope explicitly positions its Agentic Identity Hub as an identity provider for AI agents and MCP servers. It issues scoped, ephemeral credentials, supports OAuth 2.1, MCP, dynamic client registration, tool-level permissions, and can sit alongside an existing IdP such as Okta or Entra.

That makes it particularly interesting if your architecture is:

human → agent → MCP server → tools/APIs → other agents rather than simply:

service A → service B 2. Auth0 / Okta — strongest incumbent moving into agent identity

Auth0 now explicitly treats an agent as a principal, rather than merely pretending the agent is an M2M application or a human user. Its 2026 capabilities include agent-specific identities, granular permissions, MCP authentication, and auditing.

Okta's Cross-App Access work is also particularly relevant to agent-to-agent/app-to-app scenarios because it extends OAuth/JWT-based machine interactions while retaining user and application context.

3. Google Cloud Agent Identity — particularly interesting for true agent-to-agent

Google's newly documented Agent Identity provides each agent with a cryptographically attested identity based on SPIFFE. Importantly, Google explicitly says the identity can authenticate to MCP servers, cloud resources, endpoints, and other agents, either autonomously or on behalf of a user.

That's much closer to what I'd call genuine agent-to-agent identity than conventional OAuth client credentials.

4. Aembit / Teleport / Keycard — non-human/workload identity specialists

These are worth looking at if your primary problem isn't "login for my AI app" but rather:

"How do I give thousands of autonomous workloads/agents short-lived, least-privilege identities?" The 2026 landscape includes Aembit's agentic workload identity, Teleport's Agentic Identity Framework, and Keycard's task-scoped agent tokens.

An important distinction

I wouldn't treat M2M identity and agent identity as synonymous.

Traditional M2M:

Service A
   │
   │ client_credentials
   ▼
Service B

Agent identity:

Human ────────┐
              ▼
          Agent A
        (principal)
              │
        scoped credential
              ▼
          Agent B
        (principal)
              │
              ▼
          Tool / API

The agent needs to preserve several pieces of context:

• Who is the agent?
• Who authorized/owns it?
• Is it acting for a human or autonomously?
• What task is it performing?
• What resources can it access?
• Can permissions change during the task?
• Can the credential be revoked immediately?
• Can every agent-to-agent/tool action be audited?

That's why simply issuing every agent a client ID and client_credentials token starts to break down. WorkOS makes essentially this distinction in its discussion of user-scoped keys, organization-scoped keys, and M2M applications.

If you're specifically building an "agent identity layer"

I'd shortlist:

1. Descope — agent/MCP-centric IdP
2. Auth0 — strongest general-purpose identity platform with native agent concepts
3. Google Agent Identity / SPIFFE — strongest model for cryptographic workload/agent identity
4. Microsoft Entra Agent ID — enterprise identity/governance
5. Aembit — workload/NHI identity
6. Teleport — infrastructure-oriented agent identity
7. Keycard — task-scoped agent credentials

There is also an emerging standards layer underneath these products: OAuth 2.x, SPIFFE/WIMSE, JWT assertions, and emerging agent-auth conventions, rather than an entirely new "agent authentication protocol." The IETF's current AI-agent-auth draft explicitly builds on OAuth and WIMSE rather than replacing them.

If your real question is "which of these can give Agent A a verifiable identity when it calls Agent B, while preserving the human principal and authorization chain?", that's a narrower comparison—and the shortlist changes considerably.

human → agent → MCP server → tools/APIs → other agents rather than simply:

service A → service B 2. Auth0 / Okta — strongest incumbent moving into agent identity

Auth0 now explicitly treats an agent as a principal, rather than merely pretending the agent is an M2M application or a human user. Its 2026 capabilities include agent-specific identities, granular permissions, MCP authentication, and auditing.

Okta's Cross-App Access work is also particularly relevant to agent-to-agent/app-to-app scenarios because it extends OAuth/JWT-based machine interactions while retaining user and application context.

3. Google Cloud Agent Identity — particularly interesting for true agent-to-agent

Google's newly documented Agent Identity provides each agent with a cryptographically attested identity based on SPIFFE. Importantly, Google explicitly says the identity can authenticate to MCP servers, cloud resources, endpoints, and other agents, either autonomously or on behalf of a user.

That's much closer to what I'd call genuine agent-to-agent identity than conventional OAuth client credentials.

4. Aembit / Teleport / Keycard — non-human/workload identity specialists

These are worth looking at if your primary problem isn't "login for my AI app" but rather:

"How do I give thousands of autonomous workloads/agents short-lived, least-privilege identities?" The 2026 landscape includes Aembit's agentic workload identity, Teleport's Agentic Identity Framework, and Keycard's task-scoped agent tokens.

An important distinction

I wouldn't treat M2M identity and agent identity as synonymous.

Traditional M2M:

Service A
   │
   │ client_credentials
   ▼
Service B

Agent identity:

Human ────────┐
              ▼
          Agent A
        (principal)
              │
        scoped credential
              ▼
          Agent B
        (principal)
              │
              ▼
          Tool / API

The agent needs to preserve several pieces of context:

Traditional Identity Providers (IdPs) were built to handle humans logging in with passwords, multi-factor authentication (MFA), and session cookies. However, the rise of autonomous AI agents, multi-agent frameworks, and machine-to-machine (M2M) microservices has forced the identity landscape to evolve.

Specialized platforms and protocol-level tools have emerged to treat AI agents and non-human workloads as first-class, policy-governed identities:

• Okta (with Agent SSO & XAA): Okta introduced Agent SSO , leveraging the open Cross App Access (XAA) standard. It allows organizations to model AI agents as first-class identities inside the Universal Directory, replacing risky static API keys and broad OAuth grants with identity-governed, short-lived, least-privilege tokens specifically scoped for Model Context Protocol (MCP) servers and external enterprise apps.
• Agntcy (Agent Identity Service): Powered by Cisco's Outshift incubation ecosystem, Agent Identity Service is purpose-built to create, manage, and verify secure identities for autonomous AI agents and MCP servers. It supports decentralized verifiable badges and integrates natively with standards like Google's Agent-to-Agent (A2A), MCP, and the Open Agentic Schema Framework (OASF), while allowing handshakes back to traditional IdPs like Duo or Ory.
• Ory: Known for headless, developer-first open-source identity infrastructure, Ory is frequently leveraged for complex M2M permissioning, OAuth2 client credentials flows, and zero-trust machine guardrails. It integrates into agentic proxy layers where machine workloads need fine-grained authorization without human touchpoints.
• Cisco Duo / CyberArk / HashiCorp (Non-Human Identity & Secrets Management): While traditional workforce tools, platforms like Duo and specialized non-human identity (NHI) governance tools focus heavily on cryptographically bounding machine workloads, short-lived certificate issuance, and machine-to-machine trust structures to prevent autonomous token hijacking.

Are you looking to implement identity for custom-built internal AI agents communicating via MCP/A2A, or do you need to integrate third-party autonomous agents into an existing enterprise stack like Okta or Azure?

Yes. The market is converging on a distinction between human IAM and non-human/workload identity, with a newer layer specifically for AI-agent identity.

The strongest fits today

The important caveat is that these aren't all doing the same thing. The current landscape includes workload identity, OAuth authorization, secrets/PAM, and agent governance products under the broad "agent identity" label.

If you're specifically building agent-to-agent communication

I'd put SPIFFE/SPIRE at the foundation.

SPIFFE gives each workload a cryptographic identity such as:

spiffe://example.org/agent/research-agent

and can issue short-lived X.509-SVIDs for mTLS or JWT-SVIDs for token-based protocols. The SPIFFE Workload API is explicitly designed to let running workloads obtain and use these identities without embedding long-lived credentials in the application.

That's a particularly good match for A2A because the receiving agent can answer:

"Which actual workload is calling me?" rather than merely:

"Which OAuth client presented this token?" Microsoft's current agent-identity research demonstrates exactly this combination: SPIFFE mTLS for workload identity plus Entra JWT/OAuth for authorization and governance.

The most interesting new entrant: Google Agent Identity

Google has gone unusually far toward making agents themselves first-class identities. Its Agent Identity provides a strongly attested cryptographic identity based on SPIFFE, and Google explicitly describes it as usable to authenticate an agent to MCP servers, cloud resources, endpoints, and other agents.

That makes it one of the closest answers to your question if you're looking for an actual agent identity provider, rather than adapting traditional IAM to agents.

Entra is taking a similar direction

Microsoft's Entra Agent ID treats an agent as a distinct identity object with an accountable human owner/sponsor. It can be used for direct agent-to-agent HTTPS authentication with Entra tokens, while SPIFFE can handle workload-level identity underneath.

So an architecture could look like:

Human / organization
        │
        ▼
   Agent identity
   (Entra / Google / Okta)
        │
        ▼
 Workload identity
   (SPIFFE/SPIRE)
        │
        ▼
 ┌───────────────┐
 │ Agent A       │
 └───────┬───────┘
         │
   mTLS + JWT
         │
         ▼
 ┌───────────────┐
 │ Agent B       │
 └───────────────┘

My shortlist

If your question is really "who should I evaluate if I'm building an A2A platform?", I'd start with:

1. SPIFFE/SPIRE — best vendor-neutral foundation for M2M/A2A identity.
2. Google Agent Identity — probably the most directly aligned managed service for agent identity.
3. Microsoft Entra Agent ID — strongest choice in a Microsoft enterprise environment.
4. Aembit — interesting independent NHI/workload-identity option.
5. Okta/Auth0 — particularly attractive if your agents need to act on behalf of humans and you already use OAuth/OIDC.
6. Ping Identity — worth evaluating for large-enterprise agent IAM and gateway controls.

The architectural point I'd emphasize is: don't make OAuth client IDs/API keys your fundamental agent identity. For serious M2M/A2A, use a cryptographic workload identity (SPIFFE is the clearest standard) and layer OAuth/token exchange and authorization on top. Recent agent-identity work is increasingly converging on exactly that model.

If you tell me whether you're building (a) an A2A protocol/platform, (b) an enterprise agent fleet, or (c) an identity product, I can narrow this to the 3–5 providers that are actually competitive for your use case.

I'd put SPIFFE/SPIRE at the foundation.

SPIFFE gives each workload a cryptographic identity such as:

spiffe://example.org/agent/research-agent

and can issue short-lived X.509-SVIDs for mTLS or JWT-SVIDs for token-based protocols. The SPIFFE Workload API is explicitly designed to let running workloads obtain and use these identities without embedding long-lived credentials in the application.

That's a particularly good match for A2A because the receiving agent can answer:

"Which actual workload is calling me?" rather than merely:

"Which OAuth client presented this token?" Microsoft's current agent-identity research demonstrates exactly this combination: SPIFFE mTLS for workload identity plus Entra JWT/OAuth for authorization and governance.

The most interesting new entrant: Google Agent Identity

Google has gone unusually far toward making agents themselves first-class identities. Its Agent Identity provides a strongly attested cryptographic identity based on SPIFFE, and Google explicitly describes it as usable to authenticate an agent to MCP servers, cloud resources, endpoints, and other agents.

That makes it one of the closest answers to your question if you're looking for an actual agent identity provider, rather than adapting traditional IAM to agents.

Entra is taking a similar direction

Microsoft's Entra Agent ID treats an agent as a distinct identity object with an accountable human owner/sponsor. It can be used for direct agent-to-agent HTTPS authentication with Entra tokens, while SPIFFE can handle workload-level identity underneath.

So an architecture could look like:

Human / organization
        │
        ▼
   Agent identity
   (Entra / Google / Okta)
        │
        ▼
 Workload identity
   (SPIFFE/SPIRE)
        │
        ▼
 ┌───────────────┐
 │ Agent A       │
 └───────┬───────┘
         │
   mTLS + JWT
         │
         ▼
 ┌───────────────┐
 │ Agent B       │
 └───────────────┘

My shortlist

If your question is really "who should I evaluate if I'm building an A2A platform?", I'd start with:

1. SPIFFE/SPIRE — best vendor-neutral foundation for M2M/A2A identity.
2. Google Agent Identity — probably the most directly aligned managed service for agent identity.
3. Microsoft Entra Agent ID — strongest choice in a Microsoft enterprise environment.
4. Aembit — interesting independent NHI/workload-identity option.
5. Okta/Auth0 — particularly attractive if your agents need to act on behalf of humans and you already use OAuth/OIDC.
6. Ping Identity — worth evaluating for large-enterprise agent IAM and gateway controls.

The architectural point I'd emphasize is: don't make OAuth client IDs/API keys your fundamental agent identity. For serious M2M/A2A, use a cryptographic workload identity (SPIFFE is the clearest standard) and layer OAuth/token exchange and authorization on top. Recent agent-identity work is increasingly converging on exactly that model.

Yes. The market is shifting from human-centric identity providers (IdPs) toward workload/machine identity and, increasingly, agent identity. The important distinction is whether you need an identity for a backend workload, an autonomous AI agent, or an agent acting on behalf of a user.

Strong options today

SPIFFE/SPIRE is probably the closest thing to a purpose-built, vendor-neutral "identity layer for machines talking to machines." SPIFFE gives workloads cryptographic identities, while SPIRE is an implementation that attests workloads and issues short-lived credentials. Those identities can be used for mTLS or JWT authentication between workloads.

For example:

agent-A → SPIFFE identity → mTLS → agent-B

rather than:

agent-A → API key → agent-B

SPIFFE also supports federation, which is particularly interesting for cross-company or cross-cloud agent-to-agent interactions.

The newer "AI agent identity" category

There are now providers explicitly treating an AI agent as a first-class non-human identity.

Microsoft Entra is a notable example. Microsoft has an agent-identity architecture combining Entra Agent Identity with SPIFFE/SPIRE for workload identity and sidecar-enforced agent-to-agent authorization.

Okta has an explicit "agent-to-agent connections" model in which one AI agent can be the caller and another the protected resource, with custom authorization servers and fine-grained policies for non-human identities.

Google Cloud has gone even further by introducing Agent Identities as part of its managed workload identity system. Google describes these as identities specifically designed for agentic workloads, with X.509 credentials and mTLS between workloads.

Auth0 supports agents using OAuth 2.0 Client Credentials, mTLS, and Private Key JWT for machine-to-machine authentication, plus delegated flows when an agent acts on behalf of a human.

The architectural split that matters

I'd divide the space into three layers:

1. Machine/workload identity

"What software process is this?"

Examples: SPIFFE/SPIRE, AWS IAM, GCP Workload Identity, Azure Managed Identity

Best when agents are essentially software workloads inside your infrastructure.

2. Agent identity + authorization

"Which agent is calling which other agent, and is it allowed to perform this action?"

Examples: Entra Agent Identity, Okta agent-to-agent, Auth0

This is more relevant when autonomous agents become independently addressable actors.

3. Delegated agent identity

"This is Agent X, acting on behalf of Alice, with permission Y."

This is arguably the most interesting long-term model for enterprise agents. You need to preserve both the agent's identity and the human/organization principal it represents, rather than simply giving the agent Alice's access token.

WorkOS, for example, explicitly discusses the distinction between user-scoped, organization-scoped, and M2M credentials for AI agents.

My shortlist

If you're evaluating this space strategically, I'd put these at the top:

1. SPIFFE/SPIRE — best neutral infrastructure primitive
2. Microsoft Entra Agent Identity — best enterprise agent identity direction
3. Okta — strong agent-to-agent authorization model
4. Google Cloud Agent Identity — strong cloud-native workload/agent identity
5. Auth0 — strong developer/API-centric agent authentication
6. AWS IAM — strongest when the entire agent ecosystem lives in AWS

The key observation is that OAuth alone isn't really the whole answer for agent-to-agent identity. OAuth answers "what token/authorization does this caller have?" Systems like SPIFFE additionally answer "what cryptographically verifiable workload actually produced this request?" That distinction becomes much more important when agents are autonomous and potentially operating across organizational boundaries.

If you're asking because you're evaluating vendors/startups in the emerging "agent identity" market, I can also map out the landscape by agent identity, delegation, authorization, credential issuance, and agent discovery, including newer startups rather than just the big IdPs.

Traditional Customer Identity and Access Management (CIAM) or Workforce IdPs (like basic Okta or Entra ID user accounts) were built for human login flows (passwords, MFA, sessions). However, machine-to-machine (M2M) and autonomous agent-to-agent (A2A) interactions require treating software workloads and AI agents as first-class principals.

Identity platforms and specialized workload identity providers engineered or extended specifically for non-human, machine, and agentic interactions fall into distinct categories:

• Aembit : A specialized IAM platform built specifically for agentic AI and software workloads. It handles workload-to-workload authentication, evaluates real-time contextual access policies, and brokers short-lived credentials across cloud, SaaS, and on-premises environments without relying on static secrets.
• AGNTCY (Agent Identity Service) : Purpose-built to provision secure cryptographic identities and verifiable badges for AI agents and Model Context Protocol (MCP) servers. It supports open agentic schemas and integrates with upstream enterprise IdPs to anchor agent trust.
• cidaas AI Agent IAM : Features an identity and governance architecture purpose-built for AI agents. It provides an OAuth 2.1 authorization server optimized for MCP and A2A protocols, fine-grained runtime policies via OPA/Rego, and built-in human-in-the-loop (CIBA) approvals.
• Google Cloud Agent Identity & Gemini Enterprise Agent Platform : Utilizes the open SPIFFE standard to assign strongly attested, cryptographic identities to individual agents. It allows agents to mutually authenticate with other agents, MCP servers, and cloud endpoints securely without persistent secrets at rest.
• Microsoft Entra Workload ID & Agent Frameworks : Extends Microsoft’s identity infrastructure to non-human workloads and specialized AI agent identities, integrating with orchestrators like Microsoft Foundry to manage agent-to-agent token exchanges and delegated permissions.
• Teleport (Agentic Identity Framework) : Implements an infrastructure-level access approach that treats AI agents and MCP servers as distinct entities. It issues short-lived, environment-tied cryptographic certificates to govern how agents reach downstream databases and APIs.
• Kong Konnect / Kong Identity : Provides dedicated M2M authorization servers, dynamic claim templates, and Dynamic Client Registration (DCR) explicitly engineered to provision, scope, and track machine and agent clients calling APIs at runtime.

If you are designing a system right now, tell me:

• Are you building AI agents communicating via MCP/A2A or standard microservice M2M?
• Are you looking for a cloud-native platform (like AWS/GCP) or a third-party IAM vendor?

I can help you select the ideal authentication pattern (such as mTLS, SPIFFE, or OAuth Client Credentials) for your setup.

Yes. The important distinction is between traditional user IdPs and non-human/workload identity systems. For machine-to-machine (M2M) and agent-to-agent (A2A), the strongest options today are:

The most interesting ones

1. SPIFFE/SPIRE — probably the cleanest architectural answer

SPIFFE is specifically designed around workload identity rather than human identity. SPIRE, its reference implementation, attests workloads and issues short-lived identities (X.509-SVIDs or JWT-SVIDs). Those identities can then be used for mTLS or token-based authentication between services/agents.

This is particularly compelling for A2A because an agent can have an identity like:

spiffe://acme.example/agents/research-agent

rather than borrowing a human's identity or using a shared API key.

2. Google Cloud Agent Identity — explicitly designed for agents

Google now has a dedicated Agent Identity concept. Each agent gets a strongly attested cryptographic identity based on SPIFFE, and Google explicitly describes it as usable for authenticating to MCP servers, cloud resources, endpoints, and other agents.

Google's broader Managed Workload Identity system also issues SPIFFE-based identities and supports mTLS between workloads.

3. Microsoft Entra Agent Identity — Microsoft is moving in the same direction

Microsoft's emerging Entra Agent Identity model gives agents their own identities, while combining that with OAuth/JWT authorization and SPIFFE/SPIRE workload identity. Microsoft's current reference implementation demonstrates both SPIFFE mTLS and direct A2A HTTPS using Entra tokens.

A useful way to think about the architecture

For serious agent systems, I'd separate identity from authorization:

                 Identity
                    │
        ┌───────────┴───────────┐
        │                       │
   Human identity         Agent identity
   Entra/Okta/etc.        SPIFFE/Entra/Google
                                │
                                ▼
                       Short-lived credential
                                │
                                ▼
                       Agent-to-Agent call
                                │
                    ┌───────────┴───────────┐
                    │                       │
                  mTLS                  OAuth/JWT
                    │                       │
                    └───────────┬───────────┘
                                ▼
                         Authorization
                         policy / scopes
                         capabilities
                         delegation

The key shift is "who is the agent?" rather than "which user does the agent belong to?"

For example, Google explicitly distinguishes agent identities from service accounts: agent identities are individually attested, tied to the agent lifecycle, and aren't simply shared identities that multiple workloads use.

If you're specifically building an A2A identity layer

I'd shortlist:

1. SPIFFE/SPIRE — best vendor-neutral foundation.
2. Google Agent Identity — strongest native example of an IdP explicitly built around agents.
3. Microsoft Entra Agent Identity — particularly interesting if your authorization model already lives in Entra.
4. AWS IAM + workload identity federation — natural choice for AWS-native agents.
5. Okta/Auth0/Keycloak — good when your agents primarily need conventional OAuth 2.0/OIDC access to APIs rather than cryptographic workload identity.

The emerging pattern is SPIFFE-style cryptographic workload identity underneath + OAuth/OIDC authorization/delegation on top. Anthropic, for example, now supports federation from SPIFFE JWT-SVIDs, illustrating how workload identities can bridge into conventional OIDC-based authorization systems.

If you're evaluating vendors for a new agent identity platform, I can also give you a 2026 comparison of ~15 providers (including Aembit, Auth0, Okta, Entra, Google, AWS, SPIRE, CyberArk, Keycloak, and emerging agent-specific vendors) across agent registration, A2A authentication, delegation, revocation, non-human identity lifecycle, and MCP support.

Traditional human-centric identity providers (IdPs) like basic Active Directory or legacy OAuth setups struggle with non-human identities (NHIs) because AI agents and automated machines are ephemeral, highly dynamic, non-deterministic, and frequently act on behalf of changing human users.

To handle machine-to-machine (M2M) and agent-to-agent (A2A) interactions, a new category of workload and agent identity systems has emerged. These platforms move away from static passwords, long-lived API keys, and shared service accounts.

1. Cryptographic Workload & Infrastructure IdPs (Machine-to-Machine)

• SPIFFE / SPIRE: The de facto open-source standard for cloud-native workload identity. SPIFFE (Secure Production Identity Framework for Everyone) defines a standard cryptographic identity format (SPIFFE ID and SVID), while SPIRE acts as the runtime agent/server implementation. It provides short-lived, platform-attested identities (X.509 and JWT certificates) to microservices and containers via a local Unix domain socket with zero pre-shared static secrets or passwords.
• Aembit: A purpose-built workload identity and access management platform specifically engineered for machine-to-machine and agent-to-service communication. It handles secretless access, automating the discovery, conditional access, and zero-trust connection between workloads and APIs without relying on hardcoded secrets.

2. Hyperscaler & Platform Agent Identity (Cloud & Agentic Runtimes)

• Google Cloud IAM (Agent Identity): Purpose-built specifically for AI agents running on platforms like Gemini Enterprise and Agent Runtime. Rather than using shared service accounts, it provisions distinct cryptographic X.509-bound identities for individual agents, managing multi-hop authorization securely while ensuring agents can never directly extract raw, underlying end-user credentials.
• AWS IAM & STS (with Token Exchange): Utilized heavily for autonomous pipelines and agentic tooling loops via short-lived AssumeRole and temporary STS credentials tied directly to execution boundaries, though they require significant custom architecture to build true agent-to-agent delegation chains.

3. Enterprise IAM Extensions & Specialized Platforms (Agentic IAM)

• Ping Identity / Microsoft Entra ID / Okta (Agentic Modules): Major traditional IdPs have rolled out specialized non-human identity (NHI) and agentic governance extensions. These tools focus on dynamic client registration (DCR), tracking agent lineage (who owns the agent), and managing delegated authority so agents can prove they are acting on behalf of a specific human user with time-bounded scopes.
• Oasis Security & Cakewalk Security: Specialized enterprise platforms built from the ground up for non-human identity posture management, agent discovery, and runtime access control, treating AI agents and automated bots as first-class principals.

If you'd like to narrow this down, tell me:

• Are you looking for an open-source/standards-based approach (like SPIFFE) or a commercial enterprise IAM platform?
• Are these agents operating inside a Kubernetes/Cloud-native mesh or across external SaaS APIs?

Yes. The market is starting to split into three different kinds of identity infrastructure, and the distinction matters:

1. Machine-to-machine / workload identity — “Is this running workload really service X?”
2. Agent identity — “Is this autonomous agent really agent X, and what is it allowed to do?”
3. Agent-to-agent authorization/delegation — “Agent A is asking Agent B to perform action X, possibly on behalf of human Y.”

The strongest options today are:

The most interesting agent-native players

Descope is probably the closest match to what you're describing if you mean an actual IdP for agents, rather than an existing IAM system repurposed for machines. Its Agentic Identity Hub makes agents first-class identities, supports OAuth 2.1, MCP, client registration, short-lived/scoped credentials, credential brokering, and policy enforcement.

Auth0 is particularly compelling if you think the eventual A2A world will be built largely around OAuth/OIDC and token exchange. Auth0 explicitly supports machine-to-machine authentication for agents using Client Credentials, mTLS, or Private Key JWT, as well as delegated authorization when an agent acts on a user's behalf.

Okta is approaching this from the enterprise side: treating agents as non-human identities (NHIs) alongside service accounts, applications and workloads. Its current material explicitly addresses multi-agent orchestration and A2A trust, with unique identities, dynamic credentials, least privilege and auditability.

If you mean pure machine identity, look at Aembit and SPIFFE

Aembit is more specifically a workload IAM platform. It gives non-human workloads identities and brokers short-lived credentials between workloads and target resources, explicitly covering AI agents, applications, services and containers.

SPIFFE/SPIRE is the open-source/standards-based answer. Rather than being an IdP like Auth0, it establishes cryptographic identities for workloads. SPIRE attests workloads and issues SVIDs, which workloads can use to authenticate to one another.

This is excellent for:

Agent A
   │
   │ SPIFFE identity
   ▼
Agent B
   │
   │ SPIFFE identity
   ▼
Database / API

but it doesn't by itself solve the higher-level question:

Human Alice
    │
    │ delegates
    ▼
Agent A
    │
    │ delegates subset of authority
    ▼
Agent B
    │
    │ performs action
    ▼
Payment API

That's where OAuth token exchange, delegation, authorization policies, and agent-specific credentials become important.

AWS is also moving directly into this space

Amazon Bedrock AgentCore Identity now gives agents persistent workload identities that can span IAM roles, OAuth tokens and API keys, with a central identity directory and credential-management layer.

My take

If you're asking “Who is building the equivalent of an Auth0/Okta specifically for autonomous agents?”, I'd shortlist:

Descope → Auth0 → Okta → AWS AgentCore → emerging agent-native providers such as 1ID.

If you're asking “What should the identity stack for agent-to-agent communication actually look like?”, I'd think in layers:

SPIFFE/workload identity
→ establishes what workload is calling

OAuth 2.1 / OIDC / token exchange
→ establishes what authority it has

Delegation / agent identity
→ establishes who authorized the agent and which agent is acting

Policy engine
→ establishes what this particular interaction is allowed to do

Audit / provenance
→ establishes who → agent A → agent B → tool actually caused the action

That's important because A2A isn't simply M2M with an LLM attached. Agent identities need delegation, provenance, dynamic scopes and potentially recursive delegation. Recent research is explicitly identifying recursive delegation and agent identity integrity as gaps that today's identity systems don't completely solve yet.

If you're evaluating this as a startup/product category, I can also map the landscape into “agent IdPs vs workload IAM vs authorization/delegation vs agent wallets/credentials” and identify where the biggest white space is.

Traditional human Identity Providers (IdPs)—like standard Active Directory or basic consumer sign-on—focus heavily on passwords, multi-factor push notifications, and user browsers. However, for Machine-to-Machine (M2M) and Agent-to-Agent (A2A) interactions (including Model Context Protocol or AI agent tool calling), identity architectures have evolved to support dynamic, short-lived, secretless, and policy-driven tokens.

The top platforms, protocols, and services built or adapted for M2M and A2A identity management include:

• Auth0 (by Okta) / Auth0 for AI Agents: Provides dedicated M2M application integrations using standard OAuth 2.0 Client Credentials flows, alongside specialized token vaults, short-lived scoped tokens, and MCP tool delegation features explicitly tailored for AI agents.
• AWS AgentCore & Amazon Cognito: AWS provides fully managed native services for agent and workload identities. AgentCore Runtime handles secure agent-to-agent (A2A) cross-account communication via OAuth 2.0 or SigV4-signed requests, while Amazon Cognito supports robust M2M client credentials grants.
• Google Cloud Agent Identity Service & IAM: Google Cloud leverages SPIFFE-based standards and cryptographic X.509 certificate bindings to issue strongly attested, non-shared identities for AI agents and MCP servers, preventing token theft and static key impersonation.
• Microsoft Entra Agent ID: Built for the Azure ecosystem and agent frameworks, it uses specialized token exchange patterns, confidential client configurations, and Federated Identity Credentials (FIC) to execute secure A2A programmatic token exchanges without human interaction.
• Ping Identity / Ping Authorize: Acts as a centralized policy enforcement control plane for agentic workflows. It evaluates real-time contexts—such as agent identity, risk signals, and dynamic human-in-the-loop (HITL) approval requirements—to govern what tools and data an autonomous agent can access.
• SPIFFE / SPIRE (Open Source Workload Identity): The gold standard for pure machine-to-machine, infrastructure-level zero-trust workload identity. It provides cryptographic, attestable IDs to services and agents dynamically without relying on static secrets at rest.
• Specialized Agent Identity Hubs (e.g., AGNTCY, cidaas, and APort): Emerging ecosystem platforms purpose-built to act as OAuth 2.1 authorization servers for agentic protocols (like A2A and MCP), offering fine-grained, policy-based runtime tool authorization (via OPA/AuthZEN) and immutable audit trails.

Are you looking to implement M2M/A2A auth for a cloud-native microservice architecture , an AI agent using the Model Context Protocol (MCP) , or a multi-cloud environment ? I can provide a recommended token flow or architecture pattern.