Understanding Consent in MCP

Carlisia Campos picture
Carlisia Campos
MCP Technical Strategist

Publish Date October 05, 2025

In the Model Context Protocol (MCP), consent is the foundational security mechanism that governs how to delegate authority to AI agents. It ensures any actions they take are authorized, traceable, and revocable. Think of consent as a detailed, enforceable contract that spells out exactly what agents can do on the user’s behalf, going far beyond simple permissions.

tl;dr

Here’s what consent in MCP covers:

  • Granular Delegation: Permissions are defined with a high degree of specificity. For example, an agent may be authorized to “send a specific email to a designated recipient” rather than having a general permission to “send emails to any contact.”
  • Multi-layer Authorization: Security is enforced through multiple checkpoints, including agent identity verification, user authentication, MCP server access controls, and upstream service permissions.
  • Explicit Scope: Every grant of permission clearly defines the delegator, the specific agent, and the exact purposes for which the authority is granted, thereby prohibiting overly broad or undefined permissions.
  • Revocability and Auditability: Users retain the ability to revoke permissions at any time. All actions are logged to provide a clear and auditable trail of agent activity.
  • Distributed Enforcement: The defined rules are consistently enforced across all components of the system, including MCP Hosts, Clients, and Servers, to ensure comprehensive security.

Note

Consent must be crystal clear, trackable, and enforceable. Otherwise, the door to unauthorized actions is wide open.

The core concept

A core principle of consent in MCP is that it must be explicit and specific, avoiding the ambiguity of a blanket acceptance of terms. The protocol requires a detailed definition of permissions, addressing the following questions:

  • Who is delegating the authority?
  • To which agent is the authority being delegated?
  • For what purpose is the delegation being made?

This level of detail ensures clear lines of responsibility, which is particularly important in environments where multiple agents are operating concurrently.

Warning

Bypassing the explicit consent process can grant AI agents unrestricted access, which may lead to significant liability issues and an erosion of trust in the system.

The five layers of authentication and authorization

The team at Permit.io [1] breaks this down into a five-layer model that helps clarify the process:

LayerDescription
1. Agent IdentityEach AI agent has a unique, traceable identity.
2. Delegator AuthenticationThe user authenticates and establishes their identity.
3. Consent DelegationThe user defines the scope of authority for the agent (actions, conditions, constraints).
4. MCP Server AccessThe agent authenticates to the MCP server, which exposes capabilities consistent with consent.
5. Upstream ServicesExternal APIs respect both the agent’s identity and the user’s delegated permissions.

While consent appears explicitly as Layer 3 (Consent Delegation), it actually serves as the foundational principle that governs the logic and constraints at every other layer. Think of Layer 3 as where consent is formally captured and defined, but its influence extends throughout the entire authentication and authorization chain—from establishing agent identities to validating upstream service access.

Conclusion

Consent in MCP is the foundation that keeps the system secure and accountable. With explicit, granular, and auditable permissions, it is possible to stay in control of what agents can do. This approach builds on the proven foundation of OAuth 2.1, extending it to protect against both classic web security threats and new AI-specific risks.

References

[1] Permit.io — The Ultimate Guide to MCP Auth

[2] MCP Specification: Authorization

[3] MCP Specification: Security Best Practices