Identity Security Platform

Identity control for Agentic AI and MCP

Secure, govern, and monitor AI agents, MCP servers, and tools across your entire identity stack. Unosecur delivers real-time visibility, policy-driven control, and instant response, purpose-built for the age of agentic AI.

The Problem

Agentic AI introduces a new identity risk

Autonomous 
AI Agents

AI agents act, decide, and access systems independently.

Ungoverned 
Tool Access

MCP standardizes tool 
calls, not who can make them.

Zero 
Agent Visibility

Legacy identity tools have 
no awareness of 
agent actions.

Rapid 
Permission Sprawl

Tokens and entitlements 
multiply faster than any team can track.

Our Approach

The Unosecur Platform for Agentic AI and MCP

01.

Built for agentic identity

Native identity security for AI agents and NHIs with fine-grained, context-aware access control.

Purpose-built for the unique challenges of agentic AI. Unlike traditional IAM tools designed for human users, Unosecur understands agent behavior patterns, API-driven workflows, and the high-velocity access needs of autonomous systems. Secure agents without slowing them down.

02.

Centralized Control 
for MCP

The Unosecur MCP Gateway acts as a single control plane for all AI agent interactions with your infrastructure.


Define policies once and enforce them uniformly across every MCP server, tool, and resource. Agents request access, policies are evaluated in real time, and actions are permanently logged. Manual approvals, policy drift, and blind spots are eliminated entirely.

03.

Risk closed before it becomes a breach.

Every agent interaction is captured in tamper-proof audit trails.

When an agent behaves unexpectedly or accesses a restricted resource, you see the agent, the action, the timing, and exactly why the policy allowed or blocked it. Instant revocation stops suspicious agents before damage spreads.

Get a personalized demo

Ready to see Unosecure in action?

Bring Identity Control to Agentic AI

See how Unosecur secures AI agents and MCP in real environments.

FAQs

Everything you Need to Know

How to secure AI agents against unauthorised access and privilege escalation?

AI agents need scoped, ephemeral credentials, not shared service accounts. Authenticate every agent at the point of access, enforce just-in-time permissions tied to the requesting user or task, and log every tool call and resource touched. Behavioural baselining flags privilege escalation attempts. The MCP Auth Gateway sits between agents and downstream systems, so authorisation decisions happen at every hop rather than once at session start.

What are the security implications of AI agents accessing SaaS applications?

AI agents typically authenticate with broad OAuth scopes or static API keys, which means a compromised agent has standing access to whatever the connected SaaS account can do. Most SaaS apps cannot distinguish agent traffic from human user activity, so audit trails are misleading. The MCP Auth Gateway adds agent identity, scoped permissions, and per-call authorisation at the gateway layer instead.

How to detect unauthorised AI agent connections?

Maintain an inventory of approved agents and their expected behaviour. Monitor every MCP endpoint, OAuth grant, and API key issuance for new agent identities. Behavioural analytics flag agents calling tools outside their scope or accessing resources outside their normal pattern. The MCP Auth Gateway logs every connection attempt, so shadow agents surface the moment they try to reach a protected system.

How to prevent credential leakage in automated workflows?

Stop using long-lived static credentials in scripts and CI/CD pipelines. Issue short-lived tokens scoped to the specific task, rotated automatically. Inject secrets at runtime rather than embedding them in code or environment files. For AI agent workflows, the MCP Auth Gateway brokers credentials per call, so no agent or pipeline holds a token longer than the operation needs.

What are the risks of shadow AI agents in the enterprise?

Shadow agents run with credentials nobody is tracking, often pulled from a developer's personal account or a shared API key. They access production data, modify records, and call external APIs without governance, audit, or rate limits. When something breaks or leaks, attribution is impossible. The MCP Auth Gateway forces every agent through a known authorisation point, which removes the shadow path.

How to secure API-based communication between microservices?

Use mutual authentication between services with short-lived tokens, scoped to the specific operation, with every call authorised against a central policy. Static API keys shared across services are the most common failure mode. Workload identity, mTLS, and per-call authorisation through a gateway layer remove the shared-secret problem. The MCP Auth Gateway extends this pattern to agent-driven calls.

How to secure API-based communication between microservices?

Use mutual authentication between services with short-lived tokens, scoped to the specific operation, with every call authorised against a central policy. Static API keys shared across services are the most common failure mode. Workload identity, mTLS, and per-call authorisation through a gateway layer remove the shared-secret problem. The MCP Auth Gateway extends this pattern to agent-driven calls.