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Agent Security – The Permissions Gateway for Agentic AI Tools (MCPs)

Agent Security is a security gateway that provides instant control and visibility over every Model Context Protocol (MCP) server interaction. With a single configuration change, it wraps AI agents' tool access in enterprise-grade security, offering identity-based access checks, comprehensive audit trails, and human-in-the-loop approvals—all without requiring SDKs or code changes.

New to MCP?

The Model Context Protocol (MCP) is an open standard that lets AI tools connect to external services. MCP clients are the AI tools your team uses daily — Cursor, Claude Desktop, VS Code Copilot, Claude Code. MCP servers are the services they connect to — GitHub, Linear, Slack, Jira, and hundreds more. Agent Security sits between the two, giving you control over those connections.

The Challenge: Uncontrolled AI Agents and Invisible Risks​

Enterprise adoption of agentic AI is surging, but security controls haven't kept pace. Teams deploy and consume MCP servers — the "USB-C for AI" that lets LLM agents plug into apps and data — without consistent oversight. Traditional API gateways and IAM tools were never designed for autonomous, context-driven agents.

Organizations and CISOs face critical questions:

  • Which AI agents are touching which systems?
  • What data are they accessing?
  • Who ultimately authorized those actions?

The Solution: Agent Security Gateway​

Agent Security acts as a smart proxy between AI agents (MCP clients) and the tools or data they seek (MCP servers). It authenticates, authorizes, and audits every interaction, functioning as a zero-trust checkpoint for AI actions:

  1. Authenticate the originator (human) and the agent acting on their behalf
  2. Authorize the requested action against fine-grained policy
  3. Audit the outcome for compliance and threat-hunting

All this happens transparently — no modification to AI agents or MCP servers, just a URL switch.

Key Capabilities​

Fine-Grained ReBAC, Identity-Based Access Control​

  • Combine user identity, agent identity, and resource scope in one policy
  • Enforce true least-privilege down to individual MCP functions

Unified Policy Management​

  • One central policy layer instead of scattered configs
  • Rules consistently apply to internal or third-party MCP servers

Complete Visibility & Auditing​

  • Real-time logs of every agent action with rich context
  • Immediate traceability for incident response and compliance reporting

Human-in-the-Loop Workflows​

  • Configurable step-up approvals for sensitive operations
  • Optional but critical when AI touches high-risk data or funds

Enterprise Integration​

  • Leverages existing SSO (OIDC, SAML) and social providers (Google, GitHub, Microsoft)
  • Configurable per host with email domain restrictions and forced SSO redirect

Zero-Code Deployment​

  • Works as a proxy; adopt by routing MCP traffic to the gateway
  • Roll out governance in minutes, even across dozens of AI integrations

Compliance Assurance​

  • Enforce data-privacy rules (GDPR, HIPAA) and strengthen SOC 2 controls
  • Stop unauthorized PII access or data exfiltration before it happens

Current Security Risks & Compliance Gaps​

  1. Lack of Visibility & Oversight

    • AI agents often act with powerful access yet leave no usable logs
    • Makes malicious or mistaken actions hard to detect

  2. Unauthorized Actions & Privilege Abuse

    • Over-permissive agents can delete data, transfer funds, or leak secrets
    • Risks from error, prompt injection, or insider threat

  3. Shadow IT in AI Form

    • Teams spin up MCP integrations in minutes
    • Bypasses standard review and creates unvetted connections

  4. Compliance & Data-Privacy Violations

    • Unchecked agent activities risk breaching GDPR, HIPAA, and SOC 2
    • Particularly concerning for PII or regulated data access

  5. Operational Chaos & Security Drift

    • Manual processes can't keep pace with agent sprawl
    • Leads to mismatched policies and difficulty in incident forensics

How It Works​

  1. Admin connects to app.agent.security and creates a host linked to their Permit environment
  2. Admin imports upstream MCP servers and defines the trust policy for each tool
  3. Admin grants specific users permission to connect to specific MCP servers
  4. User connects their MCP client (e.g., Cursor) to the gateway and signs in

Consent flow — sign in

  1. User picks an MCP server from their allowed list, chooses a trust level, and consents

Consent flow — select MCP server

Consent flow — set trust level and review tools

  1. Gateway enforces per-tool authorization on every call — denied actions return a permissions error
  2. Admin monitors all activity on the Humans and Agents pages in app.agent.security

Agent Security delivers the visibility and control you need to safely enable AI innovation. The centralized gateway enforces policy, logs actions, and ensures compliance — all with minimal setup.

Ready to secure your AI operations? Get in touch:

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